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andreworia/claude-finance-skills
12 Claude skills for investment banking, private equity and corporate finance: valuation, trading comps, LBO returns, diligence and IC memos. Built by Oria.
History
Review weekly changes to SKILL.md before updating. Dates mark the weeks in which we observed each version; checks apply to the recorded commits.
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packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md
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packs/investment-banking/skills/buyer-targeting/SKILL.md
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packs/investment-banking/skills/capital-structure/SKILL.md
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packs/investment-banking/skills/carve-out-analysis/SKILL.md
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packs/investment-banking/skills/cim-pitchbook/SKILL.md
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packs/investment-banking/skills/company-research/SKILL.md
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packs/investment-banking/skills/comparable-analysis/SKILL.md
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packs/investment-banking/skills/compliance/SKILL.md
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packs/investment-banking/skills/covenant-package-analysis/SKILL.md
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packs/investment-banking/skills/cross-border-deal-considerations/SKILL.md
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packs/investment-banking/skills/data-room/SKILL.md
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packs/investment-banking/skills/dcf-modeling/SKILL.md
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packs/investment-banking/skills/deal-pipeline-tracker/SKILL.md
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packs/investment-banking/skills/deal-structuring/SKILL.md
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packs/investment-banking/skills/debt-sourcing/SKILL.md
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packs/investment-banking/skills/due-diligence/SKILL.md
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packs/investment-banking/skills/earnout-structuring/SKILL.md
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packs/investment-banking/skills/equity-sourcing/SKILL.md
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packs/investment-banking/skills/equity-story-development/SKILL.md
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packs/investment-banking/skills/escrow-and-indemnity/SKILL.md
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packs/investment-banking/skills/fairness-opinion/SKILL.md
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packs/investment-banking/skills/financial-modeling/SKILL.md
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packs/investment-banking/skills/financing-strategy/SKILL.md
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packs/investment-banking/skills/industry-analysis/SKILL.md
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packs/investment-banking/skills/investor-targeting/SKILL.md
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packs/investment-banking/skills/ipo-readiness-assessment/SKILL.md
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packs/investment-banking/skills/knowledge-base/SKILL.md
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packs/investment-banking/skills/lbo-modeling/SKILL.md
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packs/investment-banking/skills/management-deck/SKILL.md
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packs/investment-banking/skills/management-incentive-plan/SKILL.md
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packs/investment-banking/skills/market-intelligence/SKILL.md
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packs/investment-banking/skills/merger-analysis/SKILL.md
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packs/investment-banking/skills/nda-tracking/SKILL.md
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packs/investment-banking/skills/negotiation-support/SKILL.md
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packs/investment-banking/skills/objection-handling/SKILL.md
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packs/investment-banking/skills/offer-evaluation/SKILL.md
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packs/investment-banking/skills/outreach-email/SKILL.md
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packs/investment-banking/skills/post-deal-monitoring/SKILL.md
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packs/investment-banking/skills/precedent-transactions/SKILL.md
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packs/investment-banking/skills/purchase-price-allocation/SKILL.md
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packs/investment-banking/skills/qa-preparation/SKILL.md
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packs/investment-banking/skills/quality-control/SKILL.md
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packs/investment-banking/skills/rating-agency-presentation/SKILL.md
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packs/investment-banking/skills/regulatory-and-antitrust-review/SKILL.md
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packs/investment-banking/skills/reporting/SKILL.md
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packs/investment-banking/skills/risk-assessment/SKILL.md
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packs/investment-banking/skills/roadshow/SKILL.md
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packs/investment-banking/skills/scenario-analysis/SKILL.md
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packs/investment-banking/skills/sell-side-process-letter/SKILL.md
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packs/investment-banking/skills/sensitivity-analysis/SKILL.md
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packs/investment-banking/skills/sum-of-the-parts-valuation/SKILL.md
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packs/investment-banking/skills/syndication/SKILL.md
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packs/investment-banking/skills/synergy-quantification/SKILL.md
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packs/investment-banking/skills/task-management/SKILL.md
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packs/investment-banking/skills/teaser-one-pager/SKILL.md
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packs/investment-banking/skills/term-sheet/SKILL.md
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packs/investment-banking/skills/timeline-milestones/SKILL.md
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packs/investment-banking/skills/valuation-analysis/SKILL.md
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packs/investment-banking/skills/working-capital-adjustment/SKILL.md
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packs/investment-banking/skills/workstream-coordinator/SKILL.md
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packs/private-equity/skills/add-on-acquisition-pipeline/SKILL.md
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packs/private-equity/skills/buyer-narrative-and-positioning/SKILL.md
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packs/private-equity/skills/cim-teardown/SKILL.md
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packs/private-equity/skills/commercial-analysis/SKILL.md
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packs/private-equity/skills/competitive-moat-review/SKILL.md
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packs/private-equity/skills/customer-cohort-analysis/SKILL.md
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packs/private-equity/skills/deal-screening/SKILL.md
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packs/private-equity/skills/debt-package-sizing/SKILL.md
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packs/private-equity/skills/diligence-architecture/SKILL.md
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packs/private-equity/skills/diligence-workstream-plan/SKILL.md
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packs/private-equity/skills/exit-options-review/SKILL.md
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packs/private-equity/skills/exit-preparation/SKILL.md
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packs/private-equity/skills/financial-scenario-modelling/SKILL.md
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packs/private-equity/skills/hundred-day-plan/SKILL.md
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packs/private-equity/skills/ic-memo-drafting/SKILL.md
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packs/private-equity/skills/information-gap-log/SKILL.md
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packs/private-equity/skills/investment-committee-qa/SKILL.md
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packs/private-equity/skills/lbo-structuring/SKILL.md
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packs/private-equity/skills/management-presentation-review/SKILL.md
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packs/private-equity/skills/market-map-and-sourcing/SKILL.md
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packs/private-equity/skills/operating-kpi-cadence/SKILL.md
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packs/private-equity/skills/portfolio-value-creation/SKILL.md
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packs/private-equity/skills/pricing-power-assessment/SKILL.md
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packs/private-equity/skills/proprietary-angle-assessment/SKILL.md
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packs/private-equity/skills/red-flag-register/SKILL.md
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packs/private-equity/skills/returns-sensitivity/SKILL.md
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packs/private-equity/skills/risk-and-mitigant-register/SKILL.md
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packs/private-equity/skills/thesis-development/SKILL.md
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packs/private-equity/skills/third-party-advisor-brief/SKILL.md
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packs/private-equity/skills/vendor-due-diligence/SKILL.md
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skills/accretion-dilution-tester/SKILL.md
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skills/capital-allocation-advisor/SKILL.md
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skills/cim-red-flag-reviewer/SKILL.md
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skills/company-teardown/SKILL.md
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skills/earnings-and-filings-teardown/SKILL.md
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skills/ic-memo-drafting/SKILL.md
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skills/lbo-returns-analysis/SKILL.md
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skills/precedent-transaction-screener/SKILL.md
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skills/priced-round-dilution/SKILL.md
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skills/startup-valuation-brief/SKILL.md
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skills/trading-comps-builder/SKILL.md
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skills/valuation-triangulator/SKILL.md
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Heat
0.3- Star growth, last 7 daysNot available
- Star growth, last 24 hoursNot available
- Rank movement, last 7 daysNot available
- Commits, last 30 daysNot available
- Accounts asking about it through MCP, last 7 daysNot available
- Hot votes this weekNot available
Heat never changes the order by stars, and sponsorship never touches it. How heat works
Stars over time
30-day change not yet available: not enough history.
Individual skills in this repository
- bridge-and-acquisition-financing
packs/investment-banking/skills/bridge-and-acquisition-financing - buyer-targeting
packs/investment-banking/skills/buyer-targeting - capital-structure
packs/investment-banking/skills/capital-structure - carve-out-analysis
packs/investment-banking/skills/carve-out-analysis - cim-pitchbook
packs/investment-banking/skills/cim-pitchbook - company-research
packs/investment-banking/skills/company-research - comparable-analysis
packs/investment-banking/skills/comparable-analysis - compliance
packs/investment-banking/skills/compliance - covenant-package-analysis
packs/investment-banking/skills/covenant-package-analysis - cross-border-deal-considerations
packs/investment-banking/skills/cross-border-deal-considerations - data-room
packs/investment-banking/skills/data-room - dcf-modeling
packs/investment-banking/skills/dcf-modeling - deal-pipeline-tracker
packs/investment-banking/skills/deal-pipeline-tracker - deal-structuring
packs/investment-banking/skills/deal-structuring - debt-sourcing
packs/investment-banking/skills/debt-sourcing - due-diligence
packs/investment-banking/skills/due-diligence - earnout-structuring
packs/investment-banking/skills/earnout-structuring - equity-sourcing
packs/investment-banking/skills/equity-sourcing - equity-story-development
packs/investment-banking/skills/equity-story-development - escrow-and-indemnity
packs/investment-banking/skills/escrow-and-indemnity - fairness-opinion
packs/investment-banking/skills/fairness-opinion - financial-modeling
packs/investment-banking/skills/financial-modeling - financing-strategy
packs/investment-banking/skills/financing-strategy - industry-analysis
packs/investment-banking/skills/industry-analysis - investor-targeting
packs/investment-banking/skills/investor-targeting - ipo-readiness-assessment
packs/investment-banking/skills/ipo-readiness-assessment - knowledge-base
packs/investment-banking/skills/knowledge-base - lbo-modeling
packs/investment-banking/skills/lbo-modeling - management-deck
packs/investment-banking/skills/management-deck - management-incentive-plan
packs/investment-banking/skills/management-incentive-plan - market-intelligence
packs/investment-banking/skills/market-intelligence - merger-analysis
packs/investment-banking/skills/merger-analysis - nda-tracking
packs/investment-banking/skills/nda-tracking - negotiation-support
packs/investment-banking/skills/negotiation-support - objection-handling
packs/investment-banking/skills/objection-handling - offer-evaluation
packs/investment-banking/skills/offer-evaluation - outreach-email
packs/investment-banking/skills/outreach-email - post-deal-monitoring
packs/investment-banking/skills/post-deal-monitoring - precedent-transactions
packs/investment-banking/skills/precedent-transactions - purchase-price-allocation
packs/investment-banking/skills/purchase-price-allocation - qa-preparation
packs/investment-banking/skills/qa-preparation - quality-control
packs/investment-banking/skills/quality-control - rating-agency-presentation
packs/investment-banking/skills/rating-agency-presentation - regulatory-and-antitrust-review
packs/investment-banking/skills/regulatory-and-antitrust-review - reporting
packs/investment-banking/skills/reporting - risk-assessment
packs/investment-banking/skills/risk-assessment - roadshow
packs/investment-banking/skills/roadshow - scenario-analysis
packs/investment-banking/skills/scenario-analysis - sell-side-process-letter
packs/investment-banking/skills/sell-side-process-letter - sensitivity-analysis
packs/investment-banking/skills/sensitivity-analysis - sum-of-the-parts-valuation
packs/investment-banking/skills/sum-of-the-parts-valuation - syndication
packs/investment-banking/skills/syndication - synergy-quantification
packs/investment-banking/skills/synergy-quantification - task-management
packs/investment-banking/skills/task-management - teaser-one-pager
packs/investment-banking/skills/teaser-one-pager - term-sheet
packs/investment-banking/skills/term-sheet - timeline-milestones
packs/investment-banking/skills/timeline-milestones - valuation-analysis
packs/investment-banking/skills/valuation-analysis - working-capital-adjustment
packs/investment-banking/skills/working-capital-adjustment - workstream-coordinator
packs/investment-banking/skills/workstream-coordinator - Add-On Acquisition Pipeline
packs/private-equity/skills/add-on-acquisition-pipeline - Buyer Narrative and Positioning
packs/private-equity/skills/buyer-narrative-and-positioning - CIM Teardown
packs/private-equity/skills/cim-teardown - Commercial Analysis
packs/private-equity/skills/commercial-analysis - Competitive Moat Review
packs/private-equity/skills/competitive-moat-review - Customer Cohort Analysis
packs/private-equity/skills/customer-cohort-analysis - Deal Screening
packs/private-equity/skills/deal-screening - Debt Package Sizing
packs/private-equity/skills/debt-package-sizing - Diligence Architecture
packs/private-equity/skills/diligence-architecture - Diligence Workstream Plan
packs/private-equity/skills/diligence-workstream-plan - Exit Options Review
packs/private-equity/skills/exit-options-review - Exit Preparation
packs/private-equity/skills/exit-preparation - Financial Scenario Modelling
packs/private-equity/skills/financial-scenario-modelling - Hundred-Day Plan
packs/private-equity/skills/hundred-day-plan - IC Memo Drafting
packs/private-equity/skills/ic-memo-drafting - Information Gap Log
packs/private-equity/skills/information-gap-log - Investment Committee Q&A
packs/private-equity/skills/investment-committee-qa - LBO Structuring
packs/private-equity/skills/lbo-structuring - Management Presentation Review
packs/private-equity/skills/management-presentation-review - Market Map and Sourcing
packs/private-equity/skills/market-map-and-sourcing - Operating KPI Cadence
packs/private-equity/skills/operating-kpi-cadence - Portfolio Value Creation
packs/private-equity/skills/portfolio-value-creation - Pricing Power Assessment
packs/private-equity/skills/pricing-power-assessment - Proprietary Angle Assessment
packs/private-equity/skills/proprietary-angle-assessment - Red Flag Register
packs/private-equity/skills/red-flag-register - Returns Sensitivity
packs/private-equity/skills/returns-sensitivity - Risk and Mitigant Register
packs/private-equity/skills/risk-and-mitigant-register - Thesis Development
packs/private-equity/skills/thesis-development - Third-Party Advisor Brief
packs/private-equity/skills/third-party-advisor-brief - Vendor Due Diligence
packs/private-equity/skills/vendor-due-diligence - accretion-dilution-tester
skills/accretion-dilution-tester - capital-allocation-advisor
skills/capital-allocation-advisor - cim-red-flag-reviewer
skills/cim-red-flag-reviewer - company-teardown
skills/company-teardown - earnings-and-filings-teardown
skills/earnings-and-filings-teardown - ic-memo-drafting
skills/ic-memo-drafting - lbo-returns-analysis
skills/lbo-returns-analysis - precedent-transaction-screener
skills/precedent-transaction-screener - priced-round-dilution
skills/priced-round-dilution - startup-valuation-brief
skills/startup-valuation-brief - trading-comps-builder
skills/trading-comps-builder - valuation-triangulator
skills/valuation-triangulator
How it works
bridge-and-acquisition-financing
When your agent uses it
Structures the committed acquisition financing behind a bid, sizing the bridge and its takeout and pricing the fee drag, when you need certainty of funds to sign a deal.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
1,277 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore5,675 bytesSKILL.mdcore5,675 bytes
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# Bridge And Acquisition Financing Agent
## When to use
Use this when a bidder must show certain funds at signing but cannot raise the permanent capital until after announcement. Typical triggers: a public bid whose offer document must state the cash is committed, an auction where the seller scores certainty as heavily as price, or a board asking what the financing costs if the bond market shuts. Reach for it when the question is whether the buyer can credibly sign, not what the target is worth.
## What it does
It produces a financing structure: sources and uses, the committed facilities sized by tranche, the bridge with its securities demand and flex provisions, the takeout into permanent capital, and a cost bridge for what the bridge costs if it funds and stays outstanding.
## Method
1. Size the funding need. Start from uses, not from what the banks will lend.
- Uses are purchase equity value, target debt refinanced on change of control, and fees. Sources are cash, committed debt, and any equity or disposal proceeds; the two must tie.
2. Split permanent from bridged capital. Bridge only what cannot be raised at signing.
- Term loans, revolvers, and cash fund at close and need no bridge. The bond tranche, the equity issue, and unsigned disposals do, because none can execute before the deal is public.View the complete source on GitHubbuyer-targeting
When your agent uses it
Builds a tiered list of strategic and financial buyers with fit rationale to focus a sell-side outreach effort.
What it loads into context
Frontmatter
29 tokensAlways available to the agent
SKILL.md
793 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore3,851 bytes
Read SKILL.md
# Buyer Targeting Agent
## When to use
Use this when you need the right strategic and financial buyers for a sell-side process and must decide who to approach and in what order. It is the step between mandate and outreach. Reach for it whenever you need to convert a universe of potential acquirers into a focused, defensible target list.
## What it does
It produces a tiered buyer list with fit rationale: strategic and financial buyers screened against clear criteria, ranked into tiers, each with a short reason they belong and an initial read on their ability and appetite to transact.
## Method
Strategic versus financial buyer screening, worked step by step.
1. Split the universe into two pools.
- Strategic buyers: operating companies seeking synergy or market access. Financial buyers: sponsors and institutional investors seeking returns.
- The two pools value the asset differently, so they need different fit logic.View the complete source on GitHubcapital-structure
When your agent uses it
Reads and reshapes the mix of debt and equity with leverage and cost-of-capital metrics, use it when you need to analyze or optimize a capital structure.
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
958 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,233 bytes
Read SKILL.md
# Capital Structure Agent
## When to use
Use this when you need to read a company's existing mix of debt and equity or reshape it toward a target. This comes up when assessing debt capacity for an acquisition, evaluating a refinancing, or advising on whether a balance sheet is under or over-levered. This agent builds the current structure, the key ratios, and a comparison to a target.
## What it does
It produces a capital structure view: the current debt and equity mix built out by instrument, net debt and leverage metrics, interest coverage, a weighted average cost of capital estimate, and a side-by-side comparison to a proposed target structure.
## Method
1. Build the current structure by instrument.
- List each debt tranche (revolver, term loans, senior notes, subordinated debt) with balance, coupon, maturity, and security, then equity by class.
- This priority-ordered picture is the base for every ratio that follows.
2. Compute net debt.View the complete source on GitHubcarve-out-analysis
When your agent uses it
Builds standalone carve-out EBITDA and the separation economics for a business being sold out of a parent, for use when you must value a divestiture rather than a whole company.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
1,021 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,679 bytes
Read SKILL.md
# Carve-Out Analysis Agent
## When to use
Use this when what is being sold is a division, a segment, or a set of assets inside a larger group rather than a company that already stands alone. Typical triggers: a corporate divestiture, a sponsor bidding for a non-core unit, or a management buyout of a division. Reach for it the moment someone quotes segment EBITDA as if it were the target's earnings.
## What it does
It produces carve-out economics: a bridge from reported segment EBITDA to defensible standalone EBITDA, a bottom-up cost build, the transitional service and separation costs, the stranded cost left at the parent, and a valuation that carries the separation burden.
## Method
1. Define the perimeter first. Say exactly what is being sold.
- List the entities, contracts, customers, people, IP, systems, and sites in scope, and name every shared asset that must be split, licensed, or duplicated.
- A perimeter that moves later invalidates every number below it. Lock it first.
2. Reverse the parent's allocations. Add back the charge, then forget it.View the complete source on GitHubcim-pitchbook
When your agent uses it
Builds the full sell-side marketing book with a CIM outline, investment highlights, and financials mapped to the process.
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
834 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,147 bytes
Read SKILL.md
# CIM / Pitchbook Agent
## When to use
Use this when you need the full marketing book for a sell-side process and must move from a signed engagement to a document that goes to buyers. It is the workhorse deliverable after the teaser sparks interest and buyers sign NDAs. Reach for it whenever you need to structure a Confidential Information Memorandum or the supporting pitchbook narrative.
## What it does
It produces a CIM outline with investment highlights and financials: a complete section map, the equity story, and a clear read on how each section maps to the stages of the sale process.
## Method
CIM and pitchbook structure, worked step by step.
1. Open with the executive summary.
- The company in one page, the opportunity, transaction rationale, and the ask (what is being sold and the process type, broad auction or targeted).
- This page must stand alone; many buyers decide whether to engage on it.View the complete source on GitHubcompany-research
When your agent uses it
Builds a fast, deep company profile across financials, drivers, and positioning, for when you need a baseline on a target or client before deeper work.
What it loads into context
Frontmatter
39 tokensAlways available to the agent
SKILL.md
1,083 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore5,444 bytes
Read SKILL.md
# Company Research Agent
## When to use
Use this agent when you need a fast, deep baseline on a target or client before valuation, diligence, or a pitch. It is the first pass that gets you fluent on a company: what it does, how it makes money, how healthy the financials are, and where it sits competitively. Reach for it when a deal lands on your desk and you need to be conversant by the next morning.
## What it does
It returns a company profile that combines the quantitative picture (financials, segments, unit economics) with the qualitative picture (business model, drivers, positioning, and risks), so you have a grounded baseline to build on.
## Method
The agent runs a company-profiling routine, quantitative and qualitative:
1. Establish identity: what the company sells, to whom, its scale, ownership and structure, and how it is organized into business segments.
- Note whether it is public, sponsor-owned, or founder-held, since that shapes both data availability and deal dynamics.
View the complete source on GitHubcomparable-analysis
When your agent uses it
Builds a trading comparables set with spread multiples and a benchmark when you need a market read from public peers.
What it loads into context
Frontmatter
29 tokensAlways available to the agent
SKILL.md
1,024 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,446 bytes
Read SKILL.md
# Comparable Analysis Agent
## When to use
Use this when you need a market read from trading peers rather than an intrinsic estimate. Typical triggers: sizing where the market prices a business today, sanity-checking a DCF, or setting an IPO or offer range. Reach for it when the question is what comparable public companies are currently worth on a multiples basis.
## What it does
It produces a trading comps set: a screened peer group with EV/EBITDA, EV/EBIT, and P/E spread on a like-for-like basis, and a benchmark (median and mean) applied to the subject to imply a value range.
## Method
1. Define the subject and screen peers. Build a tight, defensible set.
- Fix the subject's sector, size, growth, and margin profile, then screen for public companies with similar business models; a short, clean set beats a long, loose one.
2. Pull market and financial data. Gather what each multiple needs.
- For each peer collect share price, diluted shares, and net debt for equity value and enterprise value, plus LTM and forward EBITDA, EBIT, and EPS.View the complete source on GitHubcompliance
When your agent uses it
Builds a compliance checklist covering information barriers and conflicts of interest so a deal process respects the firm's information and conflict rules.
What it loads into context
Frontmatter
29 tokensAlways available to the agent
SKILL.md
969 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,917 bytes
Read SKILL.md
# Compliance Agent
## When to use
Use this agent when a process must respect information and conflict rules: a new mandate is being taken on, a live deal is moving material non-public information between teams, or a wall-crossing is being contemplated. Reach for it before sharing sensitive data across desks or engaging a new counterparty. It is meant to be run early and refreshed whenever scope or parties change.
## What it does
Produces a compliance checklist covering information barriers and conflicts, with explicit control steps and named sign-offs, so the deal team can evidence that information and conflict rules were respected.
## Method
1. Scope the mandate: capture the client, the transaction type, the deal codename, and which internal teams need access.
- Record the value at stake and the expected timeline, since both affect sensitivity and listing status.
- Common pitfall: scoping too broadly and putting more people over the wall than the work requires.
2. Map information barriers between the public side and the private side.View the complete source on GitHubcovenant-package-analysis
When your agent uses it
Rebuilds covenant EBITDA, maps the debt and restricted-payment baskets, and tests headroom under a downside case, when you need to know what a credit agreement actually permits.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
1,264 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore5,927 bytes
Read SKILL.md
# Covenant Package Analysis Agent
## When to use
Use this when the question is not what a borrower has done but what the documents let it do next. Typical triggers: sizing incremental debt for an acquisition, testing whether a dividend or sponsor recap fits the baskets, underwriting a credit whose leverage looks fine on the marketed number, or working out how far EBITDA can fall before a lender gets a seat at the table. Reach for it whenever a leverage ratio is quoted without saying whose definition of EBITDA it uses.
## What it does
It produces a covenant analysis: the credit perimeter, the maintenance and incurrence tests and when each is live, a rebuilt Consolidated EBITDA with every addback identified, capacity in each debt and restricted-payment basket, and a headroom schedule naming the first breach under a downside case.
## Method
1. Draw the perimeter. Know who is actually on the hook.
- Identify the borrower, guarantors, restricted subsidiaries, and any unrestricted or excluded entities, and note what share of EBITDA sits outside the guarantee.
- EBITDA at non-guarantors flatters every ratio while being structurally unavailable to the lenders testing it.
2. Classify the regime. Maintenance and incurrence are different animals.View the complete source on GitHubcross-border-deal-considerations
When your agent uses it
Produces a cross-border deal assessment covering price currency and hedging, withholding structure, repatriation, and the approval sequence when you need to run a transaction across jurisdictions.
What it loads into context
Frontmatter
47 tokensAlways available to the agent
SKILL.md
1,001 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,667 bytes
Read SKILL.md
# Cross-Border Deal Considerations Agent
## When to use
Use this when buyer, target, or financing sit in more than one jurisdiction and the domestic playbook stops being sufficient. Typical triggers: a bid priced in a currency the acquirer does not fund in, a target whose cash sits behind a withholding regime, or a closing that must clear several regulators. Reach for it when the question is what the deal really costs once borders are in it.
## What it does
It produces a cross-border assessment: a map of where value and cash sit, an FX exposure and hedging recommendation on the price, a structure tested for withholding and treaty access, a repatriation plan, a restatement onto the acquirer's accounting standard, and a sequenced approval calendar.
## Method
1. Map the footprint. Know where value and risk sit.
- List entities with tax residence, functional currency, and share of EBITDA and cash, plus any permanent-establishment wrinkle.
2. Fix the currency of the price. Decide who bears FX.
- Set the currency of the offer, of funding, and of target cash flows; a price fixed in the target's currency puts the entire signing-to-closing move on the buyer.View the complete source on GitHubdata-room
When your agent uses it
Structures a virtual data room with a full folder taxonomy and staged access tiers, use it when you must organize diligence materials for buyers.
What it loads into context
Frontmatter
33 tokensAlways available to the agent
SKILL.md
967 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,905 bytes
Read SKILL.md
# Data Room Agent
## When to use
Use this when preparing a sell-side process and you must organize diligence materials so multiple buyers can review them in a controlled way. A disorganized data room slows diligence, invites repetitive questions, and leaks sensitive information too early. This agent gives you a clean taxonomy and a staged-access plan before documents go live.
## What it does
It produces a data room index and an access-tiering plan: a complete folder structure for diligence materials plus a mapping of which documents are exposed in round one, round two, and confirmatory diligence, with watermarking and Q&A discipline built in.
## Method
1. Build the top-level folder taxonomy.
- Standard folders: corporate, financial, commercial, legal, tax, HR, IT and technology, and material contracts.
- Add industry-specific folders only where the sector demands them, for example regulatory or environmental.
2. Populate each folder with standard subfolders.View the complete source on GitHubdcf-modeling
When your agent uses it
Builds a discounted cash flow model with WACC, dual terminal value, and sensitivities when you need an intrinsic value from cash flows.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
1,038 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,402 bytes
Read SKILL.md
# DCF Modeling Agent
## When to use
Use this when you need an intrinsic value based on cash flows rather than a market read. Typical triggers: the peer set is thin or noisy, the business is undergoing a transition the multiples miss, or you want a fundamentals-anchored cross-check on comps. Reach for it when value should be driven by what the business generates, not what the market currently pays.
## What it does
It produces a DCF: projected unlevered free cash flows discounted at WACC to an enterprise value, a terminal value computed two ways, an EV-to-equity bridge, and a sensitivity grid on WACC and growth.
## Method
1. Project unlevered free cash flow. Build FCF independent of financing.
- Start from EBIT, tax it at the marginal rate to get NOPAT, add back D&A, subtract capex, and subtract the increase in net working capital, for each explicit year (usually 5 to 10).
2. Build the cost of equity via CAPM. Price the equity risk.
- Cost of equity equals the risk-free rate plus beta times the equity risk premium; relever beta to the subject capital structure if it was drawn from peers.View the complete source on GitHubdeal-pipeline-tracker
When your agent uses it
Runs origination as a managed funnel with stage criteria, cohort conversion, and capacity limits when you need a pipeline that forecasts rather than a list that flatters.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,033 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,783 bytes
Read SKILL.md
# Deal Pipeline Tracker Agent
## When to use
Use this when origination is run off a list of names and nobody can say what will close. Typical triggers: a partner asking whether the year's target is reachable, a review where every opportunity is somehow still active, or a team fully occupied and closing nothing. Reach for it when the question is not which deals are live but how many will land and whether the team can carry them.
## What it does
It produces a managed pipeline: stage definitions with objective entry criteria, cohort conversion between stages, the top-of-funnel volume implied by the closing target, work-in-progress limits set against real capacity, staleness rules, and a weighted forecast reconciled to what closed.
## Method
1. Define the stages MECE. One opportunity, one stage, no overlaps.
- Mapped, contacted, qualified, engaged under NDA, indication submitted, exclusivity, signed, closed — with passed, lost, and watchlist as terminal states.
2. Make each entry criterion an observable event. Not a feeling.
- "Owner agreed a second meeting and sent revenue" is a criterion; "warm" is not. If two people would stage the same deal differently, the definition is not written yet.View the complete source on GitHubdeal-structuring
When your agent uses it
Designs a deal structure across consideration mix, earnouts, and protections, showing how each element shifts risk and value, for use when the economics and mechanics are still open.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
1,128 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore5,642 bytes
Read SKILL.md
# Deal Structuring Agent
## When to use
Use this agent when the economics and mechanics of the deal are still open and both sides are trying to bridge a valuation gap or allocate risk. It is most valuable when a straight cash price will not close the deal, when future performance is uncertain, or when the buyer needs protection against what diligence could not fully resolve.
## What it does
It produces a deal structure: a designed combination of consideration mix, earnout terms, and buyer and seller protections, with an explanation of how each element shifts risk and value between the parties.
## Method
This agent designs a deal structure across consideration, earnouts, and protections.
1. Set the objective. Clarify what the structure must actually solve.
- Name the problem: a valuation gap, uncertainty about future earnings, buyer risk from a thin diligence area, or a seller demand for certainty and speed.
- The structure follows the problem; do not add contingent mechanics where a clean cash deal would close.View the complete source on GitHubdebt-sourcing
When your agent uses it
Sizes a company's debt need, maps the lender universe, and returns a shortlist of lenders with indicative terms. Use when you need lenders and indicative debt terms for a financing.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,119 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore5,573 bytes
Read SKILL.md
# Debt Sourcing Agent
## When to use
Use this agent when a company or sponsor needs to raise debt and you must identify who can provide it and on what terms. The trigger is a live or near-term financing need where the borrower wants a realistic view of the lender universe and indicative pricing before formally launching a process.
## What it does
It produces a lender shortlist with indicative terms: the credible providers for the situation, the structure each is likely to offer, and the pricing, leverage, covenant, and tenor ranges to expect from each.
## Method
This agent runs a structured debt financing sourcing process.
1. Size the debt need. Establish uses (acquisition, refinancing, growth capex, dividend recap) and the funding gap after equity.
- Anchor capacity to EBITDA, free cash flow, and asset base, and compute target leverage as total debt to EBITDA.
- Sanity-check serviceability with interest coverage (EBITDA to interest) and fixed-charge coverage; a deal that prices tightly on leverage can still fail on coverage.View the complete source on GitHubdue-diligence
When your agent uses it
Structures and runs a diligence process with a workstream request list, a findings tracker, and a red-flag log.
What it loads into context
Frontmatter
33 tokensAlways available to the agent
SKILL.md
917 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore4,343 bytes
Read SKILL.md
# Due Diligence Agent
## When to use
Use this when you must structure and run a diligence process on a target, whether buy-side confirmatory diligence or sell-side vendor diligence. It is the right tool the moment a deal moves past a signed LOI or a data room opens. Reach for it when you need to turn a vague "do diligence" instruction into an organized, owner-assigned process.
## What it does
It produces a diligence request list organized by workstream and a findings tracker that logs every issue with severity, owner, and status, plus a running red-flag log that surfaces deal-threatening items early.
## Method
Diligence checklist and findings log, worked step by step.
1. Frame the scope.
- Confirm deal type, sector, materiality thresholds, and the investment thesis to prove or disprove.
- Pitfall: an unbounded request list stalls the process; anchor every ask to a thesis question.View the complete source on GitHubearnout-structuring
When your agent uses it
Designs an earnout that bridges a valuation gap, with its metric, measurement period, cap, and seller governance, for use when contingent consideration is what closes a price disagreement.
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
1,013 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Earnout Structuring Agent
## When to use
Use this when buyer and seller agree on the business but not the price, and the gap rests on future performance neither side can prove today. Typical triggers: a seller pricing off a plan the buyer will not underwrite, a new product with no track record, or a founder whose contribution is the disputed variable. Reach for it once a cash price has stalled.
## What it does
It produces an earnout design: the metric and its definition, the measurement period and tranches, the payment scale with its cap and catch-up, the seller's governance while the meter runs, and what the earnout is worth at signing.
## Method
1. Size the gap. Know what the structure must bridge.
- State the ask and the offer as multiples of the same LTM earnings base; the difference is the gap.
- Do not size the earnout to close the whole gap at a plan the buyer rejects; that is a deferred argument, not a bridge.
2. Choose the metric. Pick what cannot be argued about.View the complete source on GitHubequity-sourcing
When your agent uses it
Defines an equity raise, maps investors by mandate and check size, scores fit, and returns a shortlist with rationale. Use when you need equity investors that fit the raise.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,042 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Equity Sourcing Agent
## When to use
Use this agent when a company is raising equity and you must identify which investors are the right fit. The trigger is a defined or forming equity round where the issuer wants a targeted list of investors whose mandate, stage, and check size match the raise, rather than a broad untargeted outreach.
## What it does
It produces an equity investor shortlist with fit rationale: the investors most likely to lead or participate, why each fits, and the angle to use with each.
## Method
This agent runs a structured equity investor sourcing process.
1. Define the raise and stage. Fix the amount, the round type (growth, late-stage private, pre-IPO, PIPE), the use of proceeds, and the valuation expectation.
- Establish whether the round needs a lead and how much room is left for co-investors after the lead is set.
- Pitfall: sizing the round without a use-of-proceeds bridge, which makes the valuation ask hard to defend.View the complete source on GitHubequity-story-development
When your agent uses it
Builds the equity story an investor will underwrite, with a bottom-up market, a right to win, a financial algorithm, and the three objections answered before they are asked, when you need a narrative that survives an investor meeting.
What it loads into context
Frontmatter
54 tokensAlways available to the agent
SKILL.md
1,045 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Equity Story Development Agent
## When to use
Use this when a company must be explained to public or crossover investors and the current version is a product pitch with financials attached. Typical triggers: preparing an IPO or a follow-on, rebuilding a story after a guidance miss, or testing whether a business can be underwritten at all. Reach for it once the numbers are auditable, not before.
## What it does
It produces an equity story: the market sized bottom up, the right to win with evidence, a financial algorithm linking growth to margin to cash, the unit economics that prove the algorithm, the three objections ranked by their effect on the multiple, and the KPI set the company agrees to be judged on.
## Method
1. Fix the audience. Decide who is meant to buy this.
- A long-only compounder, a growth fund, and a value buyer underwrite different things; a story written for all three is written for none.
2. Size the market bottom up. TAM must be arithmetic.
- Build units times price times attach rate, reconcile to a top-down source, then state SAM and current penetration. A TAM the company holds one percent of invites the question of why.View the complete source on GitHubescrow-and-indemnity
When your agent uses it
Sizes escrow and indemnity against the diligence risk register, with caps, baskets, and survival periods, for use when post-close risk has to be allocated in the purchase agreement.
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
1,029 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Escrow and Indemnity Agent
## When to use
Use this when diligence has produced findings and someone must turn them into contractual protection. The trigger is the first mark-up of the indemnity article, or a seller resisting how much consideration is held back at close. Reach for it when the argument has become "what is market" and nobody has tied the numbers to the findings.
## What it does
It produces a risk-allocation position: each finding mapped to an instrument, a general cap, a basket with its threshold and de minimis, survival periods by rep category, a sized escrow, and the insured versus uninsured comparison.
## Method
1. Start from the diligence register, then split it. Known and unknown risk take different instruments.
- Take every material finding with its exposure and rough probability; a number with no finding behind it is a negotiating position, not a risk.
- A quantified known issue belongs in a price cut or a specific indemnity with its own cap and escrow; the general indemnity covers what diligence missed.
- Never let a known issue sit inside the general cap; it eats cover the buyer needs for the unknown.
View the complete source on GitHubfairness-opinion
When your agent uses it
Builds the analysis supporting a fairness opinion, showing the range under each valuation method and where the offer sits against it, when a board needs a documented basis for a price.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,026 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Fairness Opinion Agent
## When to use
Use this when a board or special committee must approve a transaction and needs the analysis sitting underneath a fairness opinion: a proposed merger agreement, a going-private deal, or a related-party transaction where the record must show the price was tested. Reach for it when the question is whether one specific number is inside a defensible range.
## What it does
It produces the supporting analysis: the range implied by each valuation method, the consideration placed against every range, the premium over the unaffected price, and the documented basis of materials, assumptions, and limitations. It prepares supporting analysis only; it does not constitute a fairness opinion and does not replace one issued by a firm.
## Method
1. Fix the mandate. Name what is being tested.
- State the parties, the transaction, the valuation date, the security, and the holders from whose point of view fairness is assessed, usually those other than the acquirer and its affiliates.
- Fairness here is financial only, never process, legal, or tax; say so at the top or the work gets read as more than it is.
2. Lock the consideration. Reduce the offer to one number.View the complete source on GitHubfinancial-modeling
When your agent uses it
Builds an integrated three-statement financial model with drivers, linkages, and checks when you need a working model of a business.
What it loads into context
Frontmatter
34 tokensAlways available to the agent
SKILL.md
1,094 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Financial Modeling Agent
## When to use
Use this when you need an integrated model of the business rather than a single isolated schedule. Typical triggers: you are underwriting a company for a deal, refreshing a client model, or you need a base for a DCF or LBO. Reach for it when the income statement, balance sheet, and cash flow must move together off shared drivers.
## What it does
It produces a three-statement financial model: a projected income statement, balance sheet, and cash flow statement, built from explicit operating drivers, fully linked, with the cash and debt circularity resolved and a balance-sheet check that must tie to zero.
## Method
1. Set the model spine. Lock the historical period, the forecast horizon, and the periodicity.
- Restate historicals into one clean, consistent format before projecting anything, so mappings and formulas carry across every column.
- Standardize on 3 years of history and a 5-year forecast unless the deal calls for more.
2. Build the income statement from drivers. Work top to bottom off explicit assumptions.View the complete source on GitHubfinancing-strategy
When your agent uses it
Builds a financing plan across sources, sizing, and sequence for a deal, use it when a transaction needs a plan for how it gets funded.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
1,026 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Financing Strategy Agent
## When to use
Use this when a transaction needs a concrete plan for how it gets funded, such as an acquisition, a leveraged buyout, a growth raise, or a recapitalization. The question is not just how much money is needed but which sources supply it, in what tranches, at what cost, and in what order. This agent lays that out end to end.
## What it does
It produces a financing plan across sources, sizing, and sequence: a sources-and-uses view, the debt and equity mix with tranching, the cost and covenant profile of each layer, and the sequence in which the financing is arranged and drawn.
## Method
1. Size the need with a sources-and-uses view.
- Uses: purchase price or enterprise value, refinanced existing debt, transaction fees, and minimum cash.
- Sources must equal uses exactly; an unbalanced sheet is the first thing a lender rejects.
2. Set the target leverage.View the complete source on GitHubindustry-analysis
When your agent uses it
Runs a Porter Five Forces read on an industry to judge how attractive and contested it is, for when you need to gauge structural profitability and risk.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
1,043 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Industry Analysis Agent
## When to use
Use this agent when you need to judge how attractive and contested an industry is before backing a thesis, pricing a deal, or advising a client on entry, exit, or expansion. It fits diligence on a target's home market, a sector deep-dive for a pitch, or a sanity check on whether strong current margins are structurally defensible.
## What it does
It returns an industry structure read that scores attractiveness force by force, surfaces the key risks, and states where structural profit pools sit and how durable they are.
## Method
The agent applies the Porter Five Forces framework with explicit scoring:
1. Define the industry boundary: the product or service, the relevant value-chain stage, the geography, and the buyer set, so the analysis does not blur adjacent markets.
- Pitfall: defining the boundary too broadly imports forces from adjacent markets and muddies every rating that follows.
View the complete source on GitHubinvestor-targeting
When your agent uses it
Prioritizes which investors to approach first by tiering candidates, assigning an angle to each, and sequencing outreach. Use when you need to prioritize who to approach first.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,004 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Investor Targeting Agent
## When to use
Use this agent when you have a pool of possible investors and must decide who to approach first. The trigger is the point after a broad universe exists but before outreach begins, when you need a disciplined priority order rather than contacting everyone at once.
## What it does
It produces a tiered investor target list with angles: candidates sorted into priority tiers, the specific angle to use with each, and the sequence in which to approach them.
## Method
This agent runs a structured investor targeting and tiering process.
1. Confirm the raise parameters. Restate the amount, instrument, valuation or pricing, and timeline so targeting is judged against a fixed goal.
- A moving target on size or valuation makes any prioritization unstable, so lock these first.
View the complete source on GitHubipo-readiness-assessment
When your agent uses it
Produces an IPO readiness assessment covering audit history, controls, board composition, and KPI discipline, plus a gap list with an honest timeline, when you need to know whether a company can survive public-company scrutiny.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
1,027 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# IPO Readiness Assessment Agent
## When to use
Use this when a company is considering a listing and someone must say, without flattery, whether it is ready. Typical triggers: a board asking for a listing window, a sponsor testing IPO against a sale, or a company told it is twelve months away for three years running. Do it before the equity story, since a good story on an unauditable base fails in diligence.
## What it does
It produces a readiness assessment across five dimensions: audit history, the control environment, reporting capability, board and governance, and KPI definition discipline, closing with a gap list carrying an owner, a cost, and a duration per gap, and a critical path to a filing-ready state.
## Method
1. Count the audit runway. Establish what is actually audited.
- Confirm how many years exist on the listing standard and by whom. A review is not an audit, and re-auditing an early year is a long-lead item.
2. Test the control environment. Assume the auditor will name every weakness.
- Segregation of duties, entity-level controls, revenue cut-off, and IT general controls, each classified as a deficiency, a significant deficiency, or a material weakness.View the complete source on GitHubknowledge-base
When your agent uses it
Captures precedents, multiples, lessons, and reusable templates from a completed deal into a structured, searchable form so each deal makes the next one faster.
What it loads into context
Frontmatter
38 tokensAlways available to the agent
SKILL.md
871 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Knowledge Base Agent
## When to use
Use this agent when you want each deal to make the next one faster: at the end of a transaction to capture what was learned before the team disperses, or when building a reusable library of precedents and multiples across many deals. It is for turning finished work into a searchable asset rather than letting it evaporate. Run it while memories are fresh, ideally within days of close.
## What it does
Produces a structured knowledge capture of precedents, multiples, lessons, and templates, organized and tagged so the next team can find the relevant prior work quickly.
## Method
1. Capture the deal fact sheet.
- Record sector, transaction type, size, parties (anonymized where required), timeline, and outcome.
- Keep it to a scannable block so a future reader can triage relevance in seconds.
2. Record the precedent transaction data.View the complete source on GitHublbo-modeling
When your agent uses it
Builds an LBO model with sources and uses, a debt schedule, and returns when you need to test a sponsor buyout and its economics.
What it loads into context
Frontmatter
38 tokensAlways available to the agent
SKILL.md
1,059 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# LBO Modeling Agent
## When to use
Use this when you need to test a sponsor buyout and its returns rather than a strategic or intrinsic value. Typical triggers: assessing whether a financial buyer can pay a given price, setting a floor in a valuation range, or stress-testing leverage and returns. Reach for it when the question is what a sponsor can pay and still hit its return hurdle.
## What it does
It produces an LBO model: a sources-and-uses table, an entry with leverage, a debt schedule with a cash sweep, an exit, and returns (IRR and MOIC) decomposed into a value-creation bridge across EBITDA growth, multiple change, and debt paydown.
## Method
1. Set the entry. Fix price and hold.
- Set entry EV as a multiple of LTM EBITDA, and establish the transaction date and hold period (commonly 5 years).
2. Build sources and uses. Make them tie.
- Uses: purchase equity value, refinanced debt, and transaction fees. Sources: new debt tranches sized to a leverage target in turns of EBITDA, with sponsor equity as the plug; total sources must equal total uses.View the complete source on GitHubmanagement-deck
When your agent uses it
Designs a management presentation outline and talk track for the equity story, use it when management must present to buyers.
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
890 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Management Deck Agent
## When to use
Use this when a company's management team must present its equity story to prospective buyers during a sale process, whether in person or by video. The management presentation is often the first live impression buyers form, so the narrative arc, page flow, and delivery all matter. This agent structures the deck and the words behind it.
## What it does
It produces a management presentation outline and talk track: a page-by-page flow that carries the equity story from company overview to financial outlook, plus the spoken narrative for each section and the questions management should be ready to field.
## Method
1. Frame the equity story spine before any pages.
- Answer four things: what the company is, why it wins, why now, and why this is the buyer's opportunity.
- Every page must serve that spine; cut any page that does not.
2. Open with a company overview.View the complete source on GitHubmanagement-incentive-plan
When your agent uses it
Designs the post-close management equity pool, its vesting, ratchet, and leaver terms when you need to align the team without repricing the sponsor's return.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
1,140 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Management Incentive Plan Agent
## When to use
Use this when a buyout is nearing signing and the post-close equity for management has to be sized, split, and papered. Typical triggers: an IC asking what the pool costs in returns, a CEO negotiating sweet equity, or refreshing a pool after a departure. Reach for it when the question is what management gets and what that does to the sponsor's return.
## What it does
It produces a management incentive plan: pool size against fully diluted equity, allocation by role, the split between time and performance vesting, a ratchet with a defined hurdle, leaver mechanics, and a dilution bridge showing sponsor returns gross and net of it.
## Method
1. Size the pool. Anchor it to the deal, not a rule of thumb.
- Ten to fifteen percent of fully diluted equity is the mid-market norm, eight to twelve on larger deals; hold fifteen to twenty percent unallocated or the first new hire forces a dilutive top-up.
2. Allocate by role. Concentrate it.
- CEO a third to a half of the pool, CFO about half the CEO's, the rest across the team. Spread thin, it buys goodwill and changes no behaviour.View the complete source on GitHubmarket-intelligence
When your agent uses it
Produces a live market intelligence brief on sector deal drivers and capital flows, for when you need a fast read before a pitch, call, or screen.
What it loads into context
Frontmatter
39 tokensAlways available to the agent
SKILL.md
1,086 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Market Intelligence Agent
## When to use
Reach for this agent when you need a live read on deal drivers and capital flows in a sector and cannot wait days for a formal research package. Typical triggers are prepping for a client call, framing a pitch, or sizing whether a sector is heating up or cooling off. It is built for the moment when a banker asks "what is actually moving in this space right now?"
## What it does
It returns a market intelligence brief that names the current catalysts, traces where capital is flowing, and spells out the implications for deal activity and for a specific client or target. The output is decision-grade context, not a data dump.
## Method
The agent runs a structured market and deal-driver scan:
1. Fix the scope: define the sector, the sub-segments in play, the geography, and the time window (typically trailing 6 to 12 months plus a forward look).
- Name the specific value-chain stage so upstream and downstream signals are not blurred together.
- Pitfall: a scope drawn too wide averages away the very signal you are hunting for.View the complete source on GitHubmerger-analysis
When your agent uses it
Tests whether a proposed combination creates value by running accretion and dilution analysis on pro-forma EPS.
What it loads into context
Frontmatter
28 tokensAlways available to the agent
SKILL.md
1,072 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Merger Analysis Agent
## When to use
Use this when a client or deal team is weighing an acquisition and needs to know whether the combination lifts or hurts earnings per share. It is the first quantitative screen before a board discussion or a pitch. Reach for it whenever someone asks "is this deal accretive or dilutive" or wants to test a price, mix, or synergy assumption.
## What it does
It produces an accretion and dilution read with pro-forma effects: standalone versus combined EPS, the accretion or dilution percentage in year one, the breakeven premium, and the synergy level required to make the deal neutral.
## Method
Accretion and dilution analysis, worked step by step.
1. Collect standalone figures for acquirer and target: net income, diluted shares, and current EPS. Confirm the tax rate and the target purchase price.
- Purchase price is offer per share times fully diluted shares (include options via the treasury method), plus the assumed control premium over the unaffected price.
- Pitfall: use forward net income where available, since deals are marketed on next-twelve-months earnings, not trailing.View the complete source on GitHubnda-tracking
When your agent uses it
Tracks NDA status across every counterparty in a live deal, use it when multiple parties are signing and accessing confidential information.
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
996 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# NDA Tracking Agent
## When to use
Use this when a sell-side or buy-side process has multiple parties signing confidentiality agreements and requesting access to information at different times. As the counterparty list grows, verbal recall of who signed what, and when, breaks down. This agent keeps a single source of truth for NDA status so no party gets access before their agreement is executed.
## What it does
It produces an NDA status log that tracks every counterparty from first contact through executed agreement, including access tier granted and expiry, so the deal team always knows exactly who is cleared for what and which items still need chasing.
## Method
1. List every counterparty in the outreach, one row each.
- Capture legal entity name, party type (strategic buyer, sponsor, lender, adviser), and primary contact plus their adviser.
- Assign a stable counterparty ID so the same party is not double-counted across an affiliate and its fund.
2. Record the NDA version sent to each party.View the complete source on GitHubnegotiation-support
When your agent uses it
Builds a negotiation plan mapping each side's interests, BATNA, and the ZOPA, with a concession and sequencing strategy, for use before entering a negotiation.
What it loads into context
Frontmatter
39 tokensAlways available to the agent
SKILL.md
1,062 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Negotiation Support Agent
## When to use
Use this agent when you need a strategy going into a negotiation and want more than instinct: a mapped view of both sides' interests, walk-away points, and the zone where a deal is possible. It is most valuable before a pricing round, a terms negotiation, or a final push to signing, when preparation determines who captures value.
## What it does
It produces a negotiation plan: a map of each side's interests, a defined BATNA for both parties, an estimated ZOPA with reservation prices and targets, and a planned set of concessions, levers, and sequencing.
## Method
This agent builds a negotiation strategy grounded in BATNA and ZOPA analysis.
1. Map the interests, not just the positions. List what each side truly wants beneath the stated ask.
- Look past price to certainty, speed, control, employee continuity, reputation, and tax treatment.
- Positions clash, but interests often align and reveal trades neither side priced into its opening ask.View the complete source on GitHubobjection-handling
When your agent uses it
Builds an objection playbook that catalogs buyer pushback on price, risk, and terms and gives each a structured response with proof, for use when a counterparty is resisting the deal.
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
1,037 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Objection Handling Agent
## When to use
Use this agent when buyers or investors are pushing back on price, risk, terms, or timing and the deal team needs ready responses that hold up under pressure. It is most useful heading into a negotiation round, responding to a lowball indication, or preparing a banker to defend a valuation in a live conversation.
## What it does
It produces an objection playbook: a catalog of the objections most likely to arise, and for each one a structured response pattern with the supporting proof the team can point to.
## Method
This agent builds an objection handling playbook.
1. Catalog the objections. List every objection you expect, grouped into four buckets.
- Price: "the multiple is too high," "comps trade lower," "your growth is already priced in."
- Risk, terms, and timing: concentration and margin durability; escrow and earnout size; "we need more diligence" or "let us revisit next quarter."View the complete source on GitHuboffer-evaluation
When your agent uses it
Compares competing bids on more than price by scoring each on certainty of close, financing, conditionality, terms, and fit, for use when choosing among offers.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,044 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Offer Evaluation Agent
## When to use
Use this agent when you have received more than one offer and must compare them on dimensions beyond the headline price. It is essential in a competitive sale process where a higher nominal bid may carry more financing risk, more conditionality, or worse terms than a lower one, and the seller needs a clear-eyed, apples-to-apples view.
## What it does
It produces a bid comparison: each offer scored across price, certainty of close, financing, conditionality, deal terms, and strategic or cultural fit, rolled into a weighted score and a risk-adjusted view of value.
## Method
This agent runs a bid comparison and offer scoring process.
1. Normalize the price. Restate every bid on a common basis before anything else.
- Reconcile enterprise value, treatment of cash and debt, and the working capital peg so headline numbers are comparable.
- Discount a stock component for volatility and risk-adjust an earnout for the probability it is actually paid, so contingent value is not counted at face.View the complete source on GitHuboutreach-email
When your agent uses it
Builds a tiered buyer outreach sequence with message templates, cadence, and follow-up logic keyed to buyer tiers.
What it loads into context
Frontmatter
29 tokensAlways available to the agent
SKILL.md
797 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Outreach Email Agent
## When to use
Use this when you need to reach buyers or investors cleanly at the start of a process and want disciplined, professional contact rather than ad hoc emails. It follows directly from a tiered buyer list. Reach for it whenever you need to sequence outreach so the right buyers get the right message at the right time.
## What it does
It produces an outreach sequence keyed to buyer tiers: message templates for each tier, a contact cadence, and follow-up logic that keeps momentum without over-contacting.
## Method
Buyer outreach sequencing, worked step by step.
1. Align outreach with the buyer tiers.
- Tier 1 goes out first as a coordinated wave; Tier 2 follows once initial responses land; Tier 3 is held for backfill.
- Sending all tiers at once loses the ability to learn from early responses and reprice the pitch.View the complete source on GitHubpost-deal-monitoring
When your agent uses it
Builds a post-close tracker of synergy realization, integration milestones, and value creation against the deal thesis once a transaction has closed.
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
896 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Post-Deal Monitoring Agent
## When to use
Use this agent when the deal is closed and value must be tracked: in the first weeks after close to stand up a monitoring framework, or at each subsequent review to check whether the transaction is delivering what was underwritten. It is for the value-capture phase, after signing and close are done. Run it on a fixed cadence so drift is caught early enough to correct.
## What it does
Produces a post-close tracker of synergies, integration milestones, and value creation measured against the deal thesis, so the team can see early whether the acquisition is on plan and where it is drifting.
## Method
1. Restate the deal thesis.
- Capture the value drivers underwritten at close, the synergy target, and the return the base case assumed.
- This is the yardstick; everything downstream is measured against it.
2. Break synergies into cost and revenue categories.View the complete source on GitHubprecedent-transactions
When your agent uses it
Builds a precedent deal set with paid multiples and control premia when you need what buyers have actually paid in past transactions.
What it loads into context
Frontmatter
32 tokensAlways available to the agent
SKILL.md
1,029 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Precedent Transactions Agent
## When to use
Use this when you need what buyers actually paid in past deals rather than where public peers trade today. Typical triggers: setting an offer or defense range in an M&A process, or grounding a control-value view that trading comps miss. Reach for it when the relevant benchmark is the price a real acquirer paid, including the control premium.
## What it does
It produces a precedent deal set: comparable historical transactions with paid EV/EBITDA (and EV/revenue where relevant), computed control premia, adjusted for cycle and synergy, and applied to the subject to imply a value range.
## Method
1. Define the screen. Target deals that resemble the subject situation.
- Screen for transactions involving similar targets by sector, size, geography, and deal type over a relevant lookback window, often 3 to 5 years to stay cycle-relevant.
2. Assemble deal facts. Capture what each multiple and premium needs.
- For each deal record the announcement date, target and acquirer type (strategic or sponsor), deal value, target LTM EBITDA and revenue at announcement, and the consideration mix.View the complete source on GitHubpurchase-price-allocation
When your agent uses it
Allocates consideration across identifiable assets, intangibles, and goodwill under the acquisition method and shows the amortization drag on reported post-deal earnings.
What it loads into context
Frontmatter
39 tokensAlways available to the agent
SKILL.md
1,054 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Purchase Price Allocation Agent
## When to use
Use this when a deal is signed or modeled and the accounting consequence of the price has to be shown: the opening balance sheet, pro-forma earnings, or the gap between reported and adjusted EPS. Reach for it when a merger model needs deal amortization, or a board asks why accretion on cash earnings becomes dilution on reported earnings.
## What it does
It produces an allocation of consideration under the acquisition method: tangible assets and assumed liabilities stepped to fair value, identifiable intangibles valued and given lives, deferred tax on the step-up, goodwill as the residual, and the amortization charge run through post-deal earnings.
## Method
1. Measure the consideration at fair value. Total what was transferred.
- Cash, stock at the closing price on the acquisition date, contingent consideration at fair value, and the pre-combination portion of replacement awards, measured by the accounting acquirer, which in a reverse acquisition is not the legal one.
- Transaction costs are expensed, never capitalized into consideration; it is the commonest error in a first-pass allocation.
2. Step tangible assets and assumed liabilities to fair value. Restate the balance sheet.View the complete source on GitHubqa-preparation
When your agent uses it
Builds a management Q&A preparation pack of the hardest buyer and investor questions with crisp, evidence-backed answers, for use when management faces tough diligence or roadshow questioning.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,068 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Q&A Preparation Agent
## When to use
Use this agent when management is about to face tough questions from a buyer, a sponsor, or an institutional investor: a management presentation, a diligence session, a roadshow, or an investor call. It is most valuable in the days before a live meeting when the team needs to be sharp under pressure and cannot afford a fumbled answer on a sensitive topic.
## What it does
It produces a Q&A prep pack: a structured set of the hardest anticipated questions, organized by theme, each paired with a crisp draft answer, the supporting proof points, and a bridging line to steer back to the equity story.
## Method
This agent runs a structured management Q&A preparation process.
1. Frame the audience and their agenda. Identify who is asking, what they are trying to disprove, and the two or three concerns most likely to move price or certainty of close.
- A strategic buyer probes synergy and integration; a sponsor probes cash generation and the exit; a lender probes downside and covenants.
- Good framing names the single question that, answered badly, kills the deal, and builds the pack backward from it.View the complete source on GitHubquality-control
When your agent uses it
Runs a structured quality-control pass over client-facing materials and logs every finding to resolution, for use when deliverables must go out error-free.
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
870 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Quality Control Agent
## When to use
Use this agent when client-facing materials must be error-free before they leave the building. It is built for the final pass on a pitch book, model, memo, or fairness presentation, when a single wrong number or stale disclaimer would damage credibility. Reach for it before anything goes to a client, a board, or a counterparty.
## What it does
It produces a QC checklist run across the deliverable and a review log that records each finding, its reviewer, and how it was resolved, so nothing goes out unchecked and every issue has an audit trail.
## Method
The agent uses a quality control review method:
1. Numbers tie. Check that every number foots and cross-foots.
- Confirm totals equal the sum of parts, that figures repeated across pages match, and that model outputs agree with the numbers quoted in the narrative.
View the complete source on GitHubrating-agency-presentation
When your agent uses it
Builds the rating agency case with agency-adjusted metrics, a peer set, a deleveraging path, and committee Q&A, when you need to defend or win a rating on a financing or acquisition.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
1,202 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Rating Agency Presentation Agent
## When to use
Use this when a rating decides whether a financing works: an acquisition pushing leverage through a threshold, a debut issuer seeking a first rating, a refinancing where one notch moves the coupon materially, or a review for downgrade that has to be argued down. Reach for it once the capital structure depends on holding a given rating, because the agency's view of your numbers, not management's, is what sets it.
## What it does
It produces the agency case: the applicable methodology and the metrics that drive the notch, agency-adjusted debt and EBITDA, the peer set the committee will benchmark against, a pro forma leverage path with explicit deleveraging commitments, expected instrument notching, and a rehearsed Q&A on the points the committee will press.
## Method
1. Fix the objective and the audience. Know which rating you are arguing for.
- State the target issuer rating and outlook at each agency, and whether the ask is an affirmation, an upgrade, or a downgrade avoided.
2. Work the published methodology. Argue inside their framework, not yours.
- S&P sets a business risk profile against a financial risk profile to reach an anchor, then applies modifiers; Moody's runs a sector scorecard of weighted factors; Fitch uses its navigator. Score yourself on their grid first.View the complete source on GitHubregulatory-and-antitrust-review
When your agent uses it
Produces an antitrust assessment with filing requirements, concentration screens, theories of harm, remedy scenarios, and a timing-to-clearance estimate when you need to know whether a deal clears and by when.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
1,024 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Regulatory And Antitrust Review Agent
## When to use
Use this when a transaction has a plausible competition issue and the answer changes deal terms, not just the closing checklist. Typical triggers: two overlapping competitors, a vertical acquisition of a supplier, or an acquirer buying a small rival with an outsized future position. Reach for it when you must say whether the deal clears, on what conditions, and by when.
## What it does
It produces a regulatory assessment: the filing map, a defined market with concentration screens, the theories of harm an agency is likely to run, a remedy ladder, a timing-to-clearance estimate, and what that timing implies for the break fee and long-stop date.
## Method
1. Map the filings. Find every regime that catches the deal.
- Test merger-control thresholds by turnover, assets, and local nexus, then the separate investment, foreign-subsidy, and sector regimes, marking which are suspensory and which are voluntary but risky to skip.
2. Define the relevant market. This is where the argument is won.
- Run the hypothetical monopolist test on product and geographic scope, demand substitution first, and state the narrower market you would concede if pressed.View the complete source on GitHubreporting
When your agent uses it
Produces a recurring deal status report covering progress, workstream status, key risks, decisions needed, and next steps for stakeholders who need a clear regular view.
What it loads into context
Frontmatter
38 tokensAlways available to the agent
SKILL.md
848 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Reporting Agent
## When to use
Use this agent when stakeholders need a clear, regular status view: a weekly deal update to the client or internal committee, a checkpoint before a milestone, or any moment when scattered workstream updates need to be pulled into one readable picture. It is built for recurring cadence, not one-off memos. Use the same format every period so readers learn where to look.
## What it does
Produces a deal status report with progress against plan, workstream status, key risks, decisions needed, and next steps, in a consistent format that reads the same way week after week.
## Method
1. Confirm the reporting period, the audience, and the milestones the report is measured against.
- Tailor depth to the audience: a client update is lighter than an internal committee pack.
- Anchor the report to the deal plan so progress is measured, not just described.
2. Open with a headline.View the complete source on GitHubrisk-assessment
When your agent uses it
Builds a deal risk register with likelihood, impact, owners, and mitigations for transactions that carry risks needing clear ownership and response.
What it loads into context
Frontmatter
34 tokensAlways available to the agent
SKILL.md
900 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Risk Assessment Agent
## When to use
Use this agent when a deal carries risks that need owners and responses: at kickoff to establish a baseline register, before a key committee, or when new diligence findings change the risk picture. It is the right tool whenever risks are being tracked informally and need to be made explicit and owned. Run it again whenever a milestone or finding materially shifts the picture.
## What it does
Produces a deal risk register that captures each material risk with its category, likelihood, impact, an assigned owner, a mitigation, and a residual risk rating after mitigation.
## Method
1. Frame the transaction: capture the deal, the parties, the timeline, and the value at stake.
- Severity only means something in context, so record what a bad outcome would cost in money, time, or reputation.
- Note the hurdle or return the base case assumes, since some risks threaten it directly.
2. Identify risks by category so nothing is missed.View the complete source on GitHubroadshow
When your agent uses it
Plans a structured investor roadshow with schedule, narrative, materials, logistics, and feedback capture. Use when you must run a structured investor roadshow.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
941 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Roadshow Agent
## When to use
Use this agent when you must run a structured roadshow to present a raise or transaction to investors. The trigger is the marketing phase of a financing or offering, when management must meet investors in an organized sequence to build the book and you need a plan that ties schedule, message, and materials together.
## What it does
It produces a roadshow plan with schedule, message, and materials: the meeting calendar, the core narrative, the deck and supporting documents, the logistics, and the mechanism for capturing and acting on investor feedback.
## Method
This agent runs a structured roadshow planning process.
1. Set objectives and audience. Define what the roadshow must achieve (cover the book, set price, build conviction) and segment the audience into anchor targets, core institutional buyers, and broader demand.
- Tie each objective to a metric, such as target subscription level, so success is measurable.
View the complete source on GitHubscenario-analysis
When your agent uses it
Builds a coherent set of base, upside, and downside scenarios on the few key drivers, with value and decision implications, when an outcome depends on a small number of uncertainties.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
856 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Scenario Analysis Agent
## When to use
Use this agent when the outcome depends on a few uncertain drivers: entering a market whose growth is unclear, pricing a deal where volume and margin could swing widely, or presenting a recommendation whose merit turns on how a small set of assumptions resolve. It is for full alternative worlds, not single-variable sensitivity. Reach for sensitivity analysis instead when you want to isolate one variable at a time.
## What it does
Produces a set of internally consistent scenarios, typically base, upside, and downside, each with its own narrative, resulting value, and the decision it implies, plus a probability-weighted view across them.
## Method
1. Identify the few drivers that actually move the outcome.
- Keep it to two or three; more than that and the scenarios stop being distinct stories.
- Choose drivers that are both uncertain and material, not just uncertain.
2. Anchor the base case first.View the complete source on GitHubsell-side-process-letter
When your agent uses it
Drafts the instructions governing a competitive auction round when you need bids on a comparable basis without losing the credible bidders to deadline pressure.
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
1,044 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Sell-Side Process Letter Agent
## When to use
Use this when a sell-side process is moving into a bid round and the instructions to bidders have to be written. Typical triggers: calling for first-round indications after the information memorandum, or setting terms for final bids before exclusivity. Reach for it when the risk is offers arriving on incomparable bases, or a deadline that turns tension into a collapsed field.
## What it does
It produces a process letter for a named round: what each bidder must submit and in what form, the price basis, the funding evidence and conditionality required, the expected mark-up of the draft agreement, the submission mechanics, and the seller's reserved rights.
## Method
1. Fix the round and what it buys. Round one buys information, round two buys certainty.
- A first-round indication should cost days, not weeks; loading it with legal work thins the field before you know who is real.
2. Define the price basis. Make offers comparable or they are not offers.
- Enterprise value on a cash-free, debt-free basis against a stated normalized working capital target, on a locked box with a ticker or on completion accounts.View the complete source on GitHubsensitivity-analysis
When your agent uses it
Builds two-variable data tables around a base case to show which drivers move value the most, expressed as swing in value, IRR, or EPS.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
964 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Sensitivity Analysis Agent
## When to use
Use this agent when you need to see what moves value the most: after a base-case model is built and you want to know which assumptions to defend hardest, or before a committee that will ask how robust the number is. Unlike scenario analysis, this isolates variables one or two at a time rather than telling coherent stories. Reach for it once the base case is stable enough to flex.
## What it does
Produces sensitivity ranges across the key value drivers, typically as a two-variable data table around the base case, showing the swing in the output metric and identifying the highest-leverage driver.
## Method
1. Fix the base case and the single output metric that matters.
- Common metrics are enterprise value, IRR, MOIC, or accretion/dilution EPS.
- Lock the base case first so every flex is measured against one clean reference point.
2. List the candidate drivers and rank them by expected leverage.View the complete source on GitHubsum-of-the-parts-valuation
When your agent uses it
Values a multi-segment business segment by segment and bridges to equity through corporate cost, net debt, and a stated holding-company discount, when a single group multiple hides where the value sits.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
1,050 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Sum-Of-The-Parts Valuation Agent
## When to use
Use this when a target runs businesses a buyer would not value the same way: a conglomerate, a fast-growing division inside a slow group, or a company facing break-up or activist pressure. Reach for it when a blended multiple on group EBITDA would average away the answer, or when the question is which piece carries the company.
## What it does
It produces a segment-by-segment valuation: each segment valued on its own peers and basis, summed to a gross value, then bridged to equity through unallocated corporate cost, net debt and debt-like items, and a stated holding-company discount, with a read on which segment carries the value.
## Method
1. Cut the company into segments. Split where the economics differ.
- Use reported segments only if they match how a buyer would buy the business; otherwise recut by end market, margin, and growth, and say what you changed.
2. Rebuild the segment financials. Get to EBITDA before corporate.
- Push allocated corporate charges back out so each segment shows standalone revenue, EBITDA, and capex, and flag arbitrary allocations.View the complete source on GitHubsyndication
When your agent uses it
Builds a plan to spread a financing across multiple providers, defining roles, allocations, underwriting basis, and flex. Use when a financing is too large or risky for one provider.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
996 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Syndication Agent
## When to use
Use this agent when a financing is too large or too risky for a single provider to hold and it must be spread across several. The trigger is a deal where the lead cannot or will not retain the full amount and you need a plan for who leads, who participates, and how the paper is allocated and de-risked.
## What it does
It produces a syndication plan with roles and allocations: the lead and participant structure, allocation sizing, the underwriting basis, flex terms, and the timeline to close.
## Method
This agent runs a structured syndication strategy.
1. Define the syndication need. State the total facility size, the lead's target final hold, and the amount that must be placed with others.
- Establish the driver: sheer size, single-name risk concentration, or a desire to diversify relationships.
View the complete source on GitHubsynergy-quantification
When your agent uses it
Sizes cost and revenue synergies separately, phases them net of cost to achieve, discounts them to a present value, and states the synergy a buyer must believe to justify the premium paid.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
1,094 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Synergy Quantification Agent
## When to use
Use this when a combination is being priced or defended and someone has quoted a synergy number without showing where it comes from: setting the premium in a live process, testing a management case before a board, or preparing the synergy page of an announcement deck. Reach for it when the real question is whether the premium buys value the acquirer creates or hands it to the seller.
## What it does
It produces a synergy build: cost synergies sized bottom-up, revenue synergies sized separately and haircut, both phased over a realistic ramp, net of cost to achieve, tax-effected and discounted to a present value, then set against the premium paid to state the run-rate the buyer must deliver to break even.
## Method
1. Split the two buckets. Never quote a single number.
- Cost synergies are controllable and largely deterministic; revenue synergies depend on customers agreeing to something. Blending them lets the soft half hide inside the hard half.
2. Build cost synergies bottom-up. Line by line, role by role.
- Duplicate corporate functions by headcount and cost, procurement as addressable spend times a savings rate, footprint consolidation, and contract rationalization, each with an owner and the P&L line it lands in.View the complete source on GitHubtask-management
When your agent uses it
Turns a scattered set of open items into a prioritized task tracker with owners and due dates, for use when action items are slipping across the deal team.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
901 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Task Management Agent
## When to use
Use this agent when open items are slipping across the team and no single list captures what is outstanding, who owns it, and when it is due. It is built for the messy middle of a live deal, when action items are spread across emails, call notes, and memory. Reach for it when the team keeps rediscovering the same overdue task.
## What it does
It produces a prioritized task tracker that captures every open item with an owner, a due date, a priority, and a status, and it flags the items that are slipping so they can be escalated.
## Method
The agent uses a task tracking and prioritization method:
1. Capture open items. Pull every outstanding task from the inputs into a single list.
- Sources include call notes, email threads, prior trackers, and meeting minutes; deduplicate where the same item appears twice.
View the complete source on GitHubteaser-one-pager
When your agent uses it
Writes a blind, identity-safe teaser that conveys the equity story and sparks buyer interest without naming the company.
What it loads into context
Frontmatter
30 tokensAlways available to the agent
SKILL.md
755 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Teaser / One Pager Agent
## When to use
Use this when you need to spark buyer interest without revealing the company's identity, at the very top of a sell-side process before NDAs are signed. It is the first document a potential buyer sees. Reach for it whenever you need a one-page blind profile that markets the opportunity while protecting confidentiality.
## What it does
It produces a blind teaser with the equity story and no company name: an anonymized business description, a financial summary, investment highlights, and process and contact details, all identity-blind.
## Method
Blind teaser writing, worked step by step.
1. Anonymize first.
- Strip the company name, exact location, customer names, and any detail specific enough to identify the target.
- Replace with a category descriptor: "a leading regional provider of..." rather than a named city or client.View the complete source on GitHubterm-sheet
When your agent uses it
Drafts or reads the key economic terms of a financing and explains what each term means for the parties. Use when you must draft or read the key economic terms.
What it loads into context
Frontmatter
40 tokensAlways available to the agent
SKILL.md
1,044 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
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- Method
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- Output format
- Example
Files
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# Term Sheet Agent
## When to use
Use this agent when you must draft a term sheet for a financing or interpret one you have received. The trigger is any point where the key economic terms are on the table and someone needs to understand or set valuation, security, preference, coupon, covenants, governance, anti-dilution, and exit rights before signing.
## What it does
It produces a term sheet with key terms and their implications: the drafted or annotated terms plus a plain explanation of what each one means for the issuer and the investor.
## Method
This agent runs structured term sheet drafting and analysis.
1. Establish the deal frame. Confirm instrument type (equity, preferred, convertible, debt), the amount, the parties, and whether you are drafting or reviewing.
- Note the relative leverage of each side, since that determines which terms are worth contesting.
- Confirm whether the term sheet is binding or non-binding and which provisions (exclusivity, confidentiality) survive if the deal breaks.View the complete source on GitHubtimeline-milestones
When your agent uses it
Builds a credible deal timeline with milestones and a computed critical path, for use when a transaction needs a defensible schedule to the close.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
853 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Timeline & Milestones Agent
## When to use
Use this agent when a deal needs a credible schedule that runs all the way to the close. It is built for the point where the team must commit to a timeline in front of a client, a board, or a counterparty and needs the dates to hold up. Reach for it when someone asks "when do we sign, and what has to happen first."
## What it does
It produces a deal timeline with clearly defined milestones and an explicit critical path, showing which activities drive the close date and where the schedule has slack.
## Method
The agent uses a critical-path deal timeline method:
1. List the activities. Enumerate every activity from kickoff to close.
- Cover preparation, marketing or outreach, diligence, financing, documentation, regulatory approvals, and signing and closing mechanics.
- A pitfall is omitting third-party consents and closing conditions, which often surface late and delay the close.View the complete source on GitHubvaluation-analysis
When your agent uses it
Runs multiple valuation methods and reconciles them into a single defensible football-field range when you need one conclusion across approaches.
What it loads into context
Frontmatter
31 tokensAlways available to the agent
SKILL.md
1,039 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Valuation Analysis Agent
## When to use
Use this when you need one defensible valuation range across methods, not a single point estimate from one approach. Typical triggers: pitching a target, setting a fairness range, or preparing a board discussion where each method must be shown and reconciled. Reach for it when the answer has to survive scrutiny from every angle.
## What it does
It produces a football-field valuation range: a plotted set of value bands, one per method, with the driver behind each band spelled out, reconciled into a single concluded range with a stated rationale.
## Method
1. Frame the subject. Fix what is being valued and how the pieces bridge.
- Confirm enterprise versus equity value, the valuation date, share count and net debt for the bridge, and the metric base (LTM and forward EBITDA, EBIT, EPS).
2. Select the method set. Choose bands that fit the situation.
- Standard bands: trading comparables, precedent transactions, and DCF, plus an LBO-implied floor or a 52-week range for a public target where relevant.View the complete source on GitHubworking-capital-adjustment
When your agent uses it
Sets a normalised working-capital peg and the completion-accounts mechanism that settles it, for use when you need to know how much real money the closing adjustment moves.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
1,006 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Working Capital Adjustment Agent
## When to use
Use this when a deal is priced cash-free debt-free and someone has to say what normal working capital is. The trigger is any signed LOI promising a purchase-price adjustment without defining the peg. Reach for it before drafting starts: the peg is negotiated once and then settled in cash.
## What it does
It produces a working-capital position: a defined net working capital metric, a peg normalised from a trailing monthly average, the completion-accounts mechanism that settles it, and a bridge from enterprise value to the seller's actual proceeds.
## Method
1. Fix the perimeter. Cash-free debt-free, and say what that means.
- The seller keeps all cash and repays all debt at close, so the equity check is enterprise value plus cash, less debt, less any shortfall against the peg.
- Every balance sits in exactly one bucket: cash, debt, debt-like, or working capital. An item in two buckets is paid for twice.
2. Define the metric line by line. Never write "current assets less current liabilities".View the complete source on GitHubworkstream-coordinator
When your agent uses it
Maps every deal workstream to clear owners and dependencies using a RACI backbone, for use when many workstreams and advisors must stay aligned on a live transaction.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,027 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Workstream Coordinator Agent
## When to use
Use this agent when a transaction has multiple parallel workstreams and several internal teams and outside advisors who must stay aligned. It is built for the moment when diligence, legal, financing, and valuation are all running at once and nobody has a single view of who owns what. Reach for it before a workstream starts colliding with another or a handoff quietly drops.
## What it does
It produces a workstream map that lists every workstream, names the owners, and shows the dependencies and handoffs between them, so the deal team and advisors can see the whole picture and act on it.
## Method
The agent uses a workstream RACI coordination method:
1. Define the workstreams. Segment the deal into the standard tracks: diligence, legal, financing, valuation, and communications.
- Diligence splits into commercial, financial, tax, legal, and operational sub-tracks; financing splits into debt commitment and syndication.
- A common pitfall is treating communications as an afterthought, which leaves board and external messaging unowned until it is urgent.View the complete source on GitHubAdd-On Acquisition Pipeline
When your agent uses it
Builds and governs a buy-and-build programme -- consolidation thesis, target criteria, arbitrage arithmetic, integration capacity and a stop rule -- when you need to decide whether the next add-on creates value or destroys it.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
1,265 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Add-On Acquisition Pipeline
## When to use
Use this skill when M&A is a named lever in the value creation plan and the platform is stable enough to absorb a transaction -- typically once the 100-day plan is complete and finance can close a month in under two weeks. Use it again at every annual value creation review, because the arithmetic that made add-on three accretive rarely survives to add-on eight.
## What it does
Produces a consolidation thesis, target criteria with explicit disqualifiers, the arbitrage arithmetic including where it stops being real, an integration capacity assessment stated in deals per year, and a stop rule.
## Method
### Step 1 -- Consolidation thesis
View the complete source on GitHubBuyer Narrative and Positioning
When your agent uses it
Builds the equity story the next owner will actually underwrite -- a de-risking ledger, the runway deliberately left unexploited, and every claim graded by proof type -- when you need a growth case that is evidenced rather than asserted.
What it loads into context
Frontmatter
58 tokensAlways available to the agent
SKILL.md
1,385 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
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- Method
- Inputs
- Output format
- Example
Files
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# Buyer Narrative and Positioning
## When to use
Use this skill once the exit route is chosen and the VDD scope is set, before the CIM and management presentation are drafted. It is also the right skill when indicative bids arrive below expectation: the usual cause is not the asset but a growth case the buyer's investment committee could not underwrite. What is built here is the input to those documents, not a substitute for them.
## What it does
Produces: the three questions the buyer's IC will ask and the answers the evidence supports; a de-risking ledger tracking each entry-date risk to its current state; a statement of the value deliberately left for the next owner, with the proof that it exists; a proof grading of every headline claim; and pre-empted answers to the objections the process will raise.
## Method
### Step 1 -- Write the buyer's IC memo before writing your own story
View the complete source on GitHubCIM Teardown
When your agent uses it
Systematic extraction and critical analysis of a Confidential Information Memorandum, identifying deal thesis, EBITDA bridge, management assertions, and the questions every diligence workstream must answer.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,643 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
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- Method
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- Output format
- Example
Files
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# CIM Teardown
## When to use
Use this skill after you have received a full CIM from a sell-side advisor and before you have convened the internal deal team for the first time. The teardown converts a 60-120 page marketing document into a structured analytical brief: what is the seller claiming, what is verifiable, what is optimistic, and what must be stress-tested in diligence. It is the starting document for your DDQ and your diligence architecture.
## What it does
Produces a CIM teardown memo covering: deal overview, stated investment thesis (in the seller's own terms), business model decomposition, financial analysis with EBITDA bridge reconstruction, management claim tracker, identified risks, and an ordered list of diligence priorities. The output is designed to be shared directly with deal team members as their briefing document for management meetings and workstream kickoffs.
## Method
### Step 1 -- Deal overview extraction
View the complete source on GitHubCommercial Analysis
When your agent uses it
Structured commercial due diligence covering TAM/SAM/SOM sizing, competitive positioning using Porter's Five Forces, customer concentration analysis, and growth thesis validation.
What it loads into context
Frontmatter
36 tokensAlways available to the agent
SKILL.md
1,925 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
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- Output format
- Example
Files
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# Commercial Analysis
## When to use
Use this skill during the commercial diligence workstream -- typically weeks 2-4 of a process. It applies to any business where the investment thesis depends on market growth, competitive positioning, or the ability to expand into adjacent markets. It is particularly important for technology, services, and consumer businesses where the moat is not always visible in the financials. This skill synthesises publicly available information and management inputs; it does not replace primary customer reference interviews, but it structures the framework those interviews should test.
## What it does
Produces a commercial analysis memo covering: market definition and sizing, competitive landscape mapped against Porter's Five Forces, company positioning and differentiation, customer and revenue concentration analysis, growth thesis assessment, and key commercial risks with diligence recommendations.
## Method
### Step 1 -- Market definition
View the complete source on GitHubCompetitive Moat Review
When your agent uses it
Produces a moat review testing a business against the named power structures -- scale economies, network effects, switching costs, counter-positioning, cornered resource, process power -- when you need to identify which one it actually has before an exit multiple is underwritten on the answer.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
1,119 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Competitive Moat Review
## When to use
Use this skill after commercial analysis has mapped the competitive landscape and before the exit multiple is set. Commercial analysis asks how attractive the industry is; this skill asks whether this company holds anything durable inside it. Run it wherever returns depend on margin holding or on exiting at or above entry -- and on every CIM that says "highly defensible".
## What it does
Produces a moat review: each candidate power tested against the evidence it requires, a verdict naming the one or two that survive and how long they last relative to the hold, and the terminal margin and exit multiple those conclusions support.
## Method
### Step 1 -- Apply the benefit-and-barrier test
View the complete source on GitHubCustomer Cohort Analysis
When your agent uses it
Produces a cohort retention memo -- vintage-level NRR, gross revenue retention, and curve shape rebuilt from raw billings -- when you need to test whether blended churn is masking a deteriorating recent cohort before it carries the seller's forecast.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
1,027 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Customer Cohort Analysis
## When to use
Use this skill in the commercial workstream alongside commercial analysis, on any business with recurring or repeat revenue. Commercial analysis sizes the market and stress-tests the growth drivers; this skill tests whether the installed base behaves the way the model assumes. Run it before the returns model is locked: two points of terminal NRR compound straight into the exit EBITDA.
## What it does
Produces a cohort memo: a vintage triangle rebuilt from raw billings, retention split into logo, gross and net revenue components by vintage, an assessment of curve shape and terminal retention, and a reconciliation of that evidence to the revenue line in the seller's model.
## Method
### Step 1 -- Rebuild the triangle, do not accept it
View the complete source on GitHubDeal Screening
When your agent uses it
Rapid triage of inbound or proactively sourced deal opportunities using a structured scoring rubric, TAM logic, and sponsor-fit criteria to prioritise pipeline.
What it loads into context
Frontmatter
35 tokensAlways available to the agent
SKILL.md
1,728 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Deal Screening
## When to use
Use this skill when you receive an inbound teaser or have identified a proactive target and need to decide quickly whether to pursue further diligence. It applies equally to sponsored processes (where a bank or advisor is running a formal auction) and to proprietary sourcing (direct outreach, intermediary referrals, sector screens). The goal is a rapid, defensible go/no-go recommendation -- not a full diligence opinion.
## What it does
Produces a structured screening note that covers: deal summary, thesis fit, market sizing logic, business quality indicators, preliminary financial assessment, key risk flags, and a recommended next action with rationale. The note is written to the standard of a first-stage investment memo -- brief enough to complete in one sitting, rigorous enough to present to a senior deal partner.
## Method
### Step 1 -- Ingest and summarise the opportunity
View the complete source on GitHubDebt Package Sizing
When your agent uses it
Sizes the debt a lender will actually fund -- leverage in turns of the EBITDA credit will accept, with fixed-charge and interest coverage at close and through a downturn -- when you need to separate what can be raised from what can be serviced.
What it loads into context
Frontmatter
56 tokensAlways available to the agent
SKILL.md
1,284 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Debt Package Sizing
## When to use
Use this skill before the financing is fixed in a bid: when a bank has quoted turns off management's adjusted EBITDA, or when the equity cheque is being set. It answers two questions and keeps them apart -- what a credit committee approves today, and what the business services through the downturn its own sector has already had.
## What it does
Produces a sizing note: statutory EBITDA rebuilt addback by addback to the number a lender will credit, debt in turns of that number, tranches with rates and amortisation, interest and fixed-charge coverage at close and at the trough, and the gap between the fundable quantum and the serviceable one.
## Method
### Step 1 -- Rebuild EBITDA the way a lender will
View the complete source on GitHubDiligence Architecture
When your agent uses it
Build a structured due diligence workplan with workstream owners, DDQ templates, key risk checklist, and a risk-ranked issues log ready for the IC memo.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
1,968 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Diligence Architecture
## When to use
Use this skill after completing the CIM teardown and before the first management meeting. The output is the workplan that coordinates your deal team (internal associates, external advisors, specialist consultants) across all diligence workstreams. It ensures nothing material falls through the gaps and that every risk identified in the teardown is owned by a specific workstream with a specific deliverable.
## What it does
Produces: (1) a structured diligence workplan with workstreams, owners, and key deliverables; (2) a due diligence questionnaire (DDQ) tailored to the specific business model and thesis; (3) a key-man and management risk checklist; and (4) a risk-ranked issues log template that tracks findings from first management meeting through final IC memo.
## Method
### Step 1 -- Define workstreams
View the complete source on GitHubDiligence Workstream Plan
When your agent uses it
Produces a dependency-mapped sequence for the commercial, financial, operational, legal, tax and IT workstreams against the exclusivity clock, for when you need the findings that invalidate other work to surface before that work is done.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
1,118 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Diligence Workstream Plan
## When to use
Use this skill once the diligence architecture has named the workstreams, owners and deliverables, and exclusivity has a start and an end date. Architecture answers who does what; sequencing answers in what order, and it is the harder question: a tax structuring finding that lands in week six can invalidate three weeks of modelling built on the wrong acquisition entity, and by then there is no float left to rebuild in.
## What it does
Produces a sequenced workplan built on a critical path -- every workstream mapped to the outputs it consumes and the outputs it produces, ordered so that shape-changing findings arrive before the work they would undo, with float, freeze points and a re-baselining trigger stated on the face of the plan.
## Method
### Step 1 -- Fix the terminal dates and run a backward pass
View the complete source on GitHubExit Options Review
When your agent uses it
Compares the routes out of a portfolio company -- trade sale, sponsor-to-sponsor, IPO, continuation vehicle or continued hold -- on achievable value, certainty, timing and readiness cost, when you need to choose a route rather than justify one.
What it loads into context
Frontmatter
57 tokensAlways available to the agent
SKILL.md
1,324 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Exit Options Review
## When to use
Use this skill at the point where the fund is deciding how to exit, not whether -- usually 12-24 months before the intended realisation, and again whenever something moves the decision: a debt market that reopens or shuts, an unsolicited approach, a fund whose life is running down, or LPs pressing for DPI. Run it before a bank is mandated: once an advisor is appointed the process design is largely fixed, and a route chosen for the wrong reason is expensive to reverse.
## What it does
Produces a like-for-like comparison of five routes -- trade sale, sponsor-to-sponsor, IPO, continuation vehicle, continued hold -- each scored on achievable value net to the fund, certainty of completion, time to liquidity, and the readiness work required. It ends with a primary route, a fallback, and the conditions that would switch between them.
## Method
### Step 1 -- Fix the hold case first
View the complete source on GitHubExit Preparation
When your agent uses it
Structure an exit readiness plan covering vendor due diligence preparation, buyer universe mapping, equity story refinement, management presentation design, and process timeline.
What it loads into context
Frontmatter
34 tokensAlways available to the agent
SKILL.md
2,273 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
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- Output format
- Example
Files
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# Exit Preparation
## When to use
Use this skill 12-18 months before a planned exit. Exit preparation is not something to start when the banker is hired -- by then, it is too late to address the issues that depress valuation. The skill is also useful at the annual value creation review in year 3 of a 5-year hold, when the team needs to assess whether the business is on track for a premium exit or whether specific actions are required to maximise exit value. It is equally applicable to full company sales, secondary sales to other PE firms, and management buyouts.
## What it does
Produces: (1) a vendor due diligence (VDD) readiness assessment identifying the gaps most likely to surface in a buyer's diligence and impair the value; (2) a buyer universe map with strategic and financial buyer categories; (3) an equity story framework for the management presentation; and (4) a process timeline from mandate to close.
## Method
### Step 1 -- VDD readiness assessment
View the complete source on GitHubFinancial Scenario Modelling
When your agent uses it
Build a structured LBO returns analysis with bear/base/bull scenarios, MOIC and IRR sensitivity to entry multiple and leverage, and covenant headroom assessment.
What it loads into context
Frontmatter
41 tokensAlways available to the agent
SKILL.md
2,036 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Financial Scenario Modelling
## When to use
Use this skill when you need to build or stress-test the returns analysis for an LBO acquisition. It is most useful in three situations: (1) ahead of an indicative bid, when you need to establish the range of supportable entry prices; (2) ahead of a final bid, when you need to refine the model with updated diligence data; or (3) ahead of the IC memo, when you need to present returns under clearly defined scenarios with transparent assumptions. This skill structures the logic and the sensitivity analysis -- it does not replace a live Excel model, but it defines what that model must contain and what assumptions to test.
## What it does
Produces: (1) a structured LBO model logic description (sources and uses, capital structure, operating assumptions, exit assumptions); (2) bear/base/bull scenario assumptions clearly differentiated; (3) a returns sensitivity table described in prose (MOIC and IRR vs entry multiple and exit multiple, and vs leverage and interest rate); and (4) a covenant headroom analysis and downside protection assessment.
## Method
### Step 1 -- Sources and uses of funds
View the complete source on GitHubHundred-Day Plan
When your agent uses it
Produces the first hundred days as a bandwidth-budgeted, sequenced plan with the reporting cadence installed in week one and an explicit cut list, when you need a plan management can execute rather than a wish list.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
933 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Hundred-Day Plan
## When to use
Use this skill between signing and completion, when the team converts the investment thesis into what actually happens after the wire clears. It applies equally to a carve-out carrying TSA obligations and to a bolt-on where the hundred days belong to integration. Reach for it when the draft already runs to thirty actions -- the failure mode it exists to fix.
## What it does
Produces a plan in four parts: a bandwidth budget in executive-days, three to five moves priced against it, a dependency-ordered sequence with the week-one reporting cadence, and a published list of what is deliberately not being done.
## Method
1. **Budget the bandwidth before choosing the moves.** Count the executive-days genuinely available: executives who can carry change work, times fourteen weeks, times the share of their week not spent running the business -- usually one day in five. A plan costing more than that budget is a wish list, and saying so now is cheaper than finding out at day sixty.
2. **Choose three to five moves.** Each must protect value acquired, unlock a named lever in the EBITDA bridge, or buy information diligence could not. Anything failing all three waits for the year-one budget. Price each in executive-days and hold back about 20%, because something unforecast always arrives in month one.View the complete source on GitHubIC Memo Drafting
When your agent uses it
Draft an investment committee memo covering deal thesis, business quality summary, diligence findings, risk matrix, returns analysis, and recommendation -- in the format senior investment professionals expect.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
1,919 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# IC Memo Drafting
## When to use
Use this skill after diligence is substantially complete and the deal team has formed a clear view on the opportunity. The IC memo is the written argument for (or against) the investment decision -- it must be complete, balanced, and defensible under cross-examination from senior investment professionals, LPs, and in some cases, internal risk committees. Use it to draft the memo, stress-test the argument, and ensure no material finding from diligence is omitted.
## What it does
Produces a structured IC memo draft covering all standard sections: executive summary, business description, deal overview, market and competitive position, management assessment, diligence findings, financial analysis, returns, risk matrix, and recommendation. The draft is written in institutional investment prose -- direct, evidence-based, no marketing language.
## Method
### Step 1 -- Executive summary (write last, present first)
View the complete source on GitHubInformation Gap Log
When your agent uses it
Produces a live register of every assumption the price rests on but no evidence has confirmed, each with an owner, a need-by date, and the decision it blocks, for when you need every unanswered question at IC to be a deliberate risk rather than a surprise.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
1,119 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
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- Output format
- Example
Files
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# Information Gap Log
## When to use
Use this skill from the moment the CIM teardown produces its diligence priority list, and keep it live until IC papers circulate. The issues log records findings -- things you know and do not like. The gap log records the inverse: assumptions the bid depends on that no document, call, or advisor has yet confirmed. A gap arriving at IC unclosed is acceptable. A gap arriving unnamed is not.
## What it does
Maintains one register of open gaps, each carrying the assumption at risk, the evidence that would close it, the named owner, the need-by date, the decision it blocks, and its effect on QoE EBITDA and turns of entry multiple if it resolves against the base case.
## Method
### Step 1 -- Derive gaps from the thesis, not the data room index
View the complete source on GitHubInvestment Committee Q&A
When your agent uses it
Produces a ranked IC question bank with a written answer to each and a conditions slate for the objections better met with a condition than a defence, when you need the session to test the deal rather than the presenter.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
988 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
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- Example
Files
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# Investment Committee Q&A
## When to use
Use this skill in the 48-72 hours between circulating the IC memo and the committee session. The memo makes the argument; this prepares the interrogation of it. It applies to a first approval, a re-approval after a price move, and follow-on capital requests. Use it especially when the team is confident, because confidence is the condition under which answers get invented in the room.
## What it does
Produces a question bank ranked by return impact, a written answer to each, a labelled list of the questions to which there is no good answer, a pre-agreed conditions slate, and a speaking plan for who answers what.
## Method
1. **Read the memo as an adversary.** Mark every number that moves the return and every sentence that hedges. The recurring three: the QoE haircut, the credibility of the growth bridge, and the exit multiple.
2. **Rank by return impact, not by likelihood of being asked.** State how much MOIC and IRR turn on each answer. A question worth 0.4x of MOIC is prepared before one worth 0.05x, whatever this committee habitually asks.View the complete source on GitHubLBO Structuring
When your agent uses it
Builds the sponsor base case -- sources and uses that tie, leverage in turns, the cash sweep, a flat-multiple exit, and returns as both IRR and MOIC with a value-creation bridge -- when you need to know what a structure pays and where the return comes from.
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
1,263 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# LBO Structuring
## When to use
Use this skill when the entry price is live and you need to know what the structure returns, not what the seller says the business is worth. It fixes one base case -- one entry multiple, one capital structure, one exit -- for sensitivity work to flex against, and belongs before an indicative bid, not after.
## What it does
Produces the sponsor base case: sources and uses that tie to the dollar, leverage in turns of QoE-adjusted EBITDA, an annual cash sweep, a flat-multiple exit, and returns as both IRR and MOIC with a bridge splitting the equity gain into EBITDA growth, multiple change and debt paydown.
## Method
### Step 1 -- Fix the entry and tie sources to uses
View the complete source on GitHubManagement Presentation Review
When your agent uses it
Reviews a management presentation for what it omits -- moved metric definitions, cohorts that stopped being shown, bridges that do not tie -- when you need the questions to ask in the session itself.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
1,007 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Management Presentation Review
## When to use
Use this skill on receipt of the management presentation and before the session is held, and again when a second-round deck must be diffed against the first. The deck is a sales document from the adviser who wrote the CIM: the disclosed numbers have been vendor-checked, so the signal is in what was dropped.
## What it does
Produces a review organised around omission: a page-by-page diff against the CIM, a register of metric definitions that moved, the cohorts that stopped being shown, a bridge tie-out, a realised-versus-annualised EBITDA restatement, and a three-tier question list for the session, the data room and what to hold back.
## Method
### Step 1 -- Diff the deck against the CIM, page by page
View the complete source on GitHubMarket Map and Sourcing
When your agent uses it
Builds the map of a sub-sector -- target universe, ownership status, EBITDA size bands and a shortlist ranked by thesis fit rather than availability -- when you need a pipeline you chose rather than one you were sent.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
967 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Market Map and Sourcing
## When to use
Use this skill once a thesis exists and before any intermediary is called. Use it also as a diagnostic: if the pipeline is entirely banked processes, the map is being assembled from what happens to be for sale, and the fund is bidding on other people's timing.
## What it does
Produces a market map of a defined sub-sector: the target universe with sources, ownership status and vintage, EBITDA size bands, a fit score derived from the thesis conditions, a separately held accessibility score, and a shortlist ranked by fit with an owner and cadence per name.
## Method
### Step 1 -- Build the universe before filtering it
View the complete source on GitHubOperating KPI Cadence
When your agent uses it
Installs the monthly operating review -- a short measure set defined precisely enough to be uncontestable, each with an escalation rule that fires automatically, when you need reporting that changes decisions.
What it loads into context
Frontmatter
45 tokensAlways available to the agent
SKILL.md
939 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Operating KPI Cadence
## When to use
Use this skill in the first weeks of ownership, when the reporting rhythm is set, and whenever the monthly pack has grown to forty pages nobody reads. Reach for it after a covenant scare, when the board finds it was watching the wrong measures a month too late.
## What it does
Produces the operating review as an installed process: a fixed calendar, eight to twelve measures each with a written definition, the reference against which each is read, escalation rules agreed before any variance appears, and an agenda that runs to decisions.
## Method
1. **Fix the calendar first.** Close by working day eight, pack out working day ten, review on working day twelve, actions within two days, published a year ahead. The dates should be boring and immovable; the 100-day plan's reporting rebuild exists to make them achievable.
2. **Choose eight to twelve measures, no more.** Four families: trading in the month, the unit economics behind it, cash and balance sheet, and covenant. Each earns its place by tracking a named lever in the EBITDA bridge or a covenant test; one mapping to neither is interesting, not operational.View the complete source on GitHubPortfolio Value Creation
When your agent uses it
Build a 100-day plan, EBITDA bridge decomposition, value creation workstream design, and KPI dashboard for monitoring portfolio company performance post-acquisition.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
2,121 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Portfolio Value Creation
## When to use
Use this skill in two situations: (1) in the 4-6 weeks before close, when the deal team is developing the 100-day plan and value creation roadmap to present to management at the first board meeting; and (2) quarterly, when reviewing portfolio company performance against plan and refreshing the value creation workstreams. The skill applies to both buy-and-build platforms (where M&A is a core value creation lever) and organic growth businesses.
## What it does
Produces: (1) a 100-day plan structured around the key post-close priorities; (2) an EBITDA bridge decomposition that maps value creation levers to EBITDA impact; (3) a value creation workstream design with owners, milestones, and KPIs; and (4) a KPI dashboard structure for quarterly portfolio monitoring.
## Method
### Step 1 -- 100-day plan
View the complete source on GitHubPricing Power Assessment
When your agent uses it
Produces a pricing power assessment -- price/volume/mix bridge, pocket-price waterfall, contract escalators and the last increase attempted -- when you need to know whether a price-led value creation plan is underwritable.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
1,074 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Pricing Power Assessment
## When to use
Use this skill whenever the value creation plan contains a pricing line, and always when the seller calls the business "underpriced". Commercial analysis establishes buyer power at the market level; this skill establishes what this company has actually realised, account by account. Price drops through at close to 100% margin -- one point of price on a 15%-margin business is a 6-7% lift in EBITDA -- so it is the highest-leverage and least-evidenced line in most models.
## What it does
Produces a pricing assessment: a price/volume/mix decomposition of growth, a pocket-price waterfall from list to cash received with discount dispersion, a contract review of escalators and caps, and the outcome of the last increase attempted.
## Method
### Step 1 -- Separate price from volume and mix
View the complete source on GitHubProprietary Angle Assessment
When your agent uses it
Tests a claimed proprietary angle against evidence, grades it real, partial or none and prices what it actually buys -- when you need to know whether there is a reason to win a deal outside a broad auction.
What it loads into context
Frontmatter
50 tokensAlways available to the agent
SKILL.md
1,018 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Proprietary Angle Assessment
## When to use
Use this skill the moment someone calls a deal proprietary, and always before a pre-emptive bid is underwritten -- the premium usually arrives attached to the claim. Start from the assumption that there is no angle; most do not survive step two.
## What it does
Produces a short assessment: the claim written plainly with its holder named, the result of each evidence test, a grade of real, partial or none, what the angle mechanically buys, and the premium it must justify against the expected clearing range.
## Method
### Step 1 -- Write the claim and name the person who holds it
View the complete source on GitHubRed Flag Register
When your agent uses it
Produces the single register in which every diligence finding is graded by severity and classified as priceable, fixable or walk-away, with a named owner and a resolution status, for when you need each flag to land in the price, the SPA or the value creation plan before IC.
What it loads into context
Frontmatter
65 tokensAlways available to the agent
SKILL.md
1,187 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Red Flag Register
## When to use
Use this skill from the first advisor read-out through to signing. The issues log tracks that a finding exists; the red flag register decides what is done about it. Every finding takes one of three routes -- it is paid for, it is fixed, or it ends the deal -- and forcing that choice early is what stops forty amber items reaching IC with no aggregate stated and no owner against any of them.
## What it does
Maintains one register in which each finding carries a quantified impact, a disposition of priceable, fixable or walk-away, the mechanism that carries it, a named owner, and a status that closes only when the finding has landed somewhere real.
## Method
### Step 1 -- Keep one register, not one per advisor
View the complete source on GitHubReturns Sensitivity
When your agent uses it
Isolates the two or three variables a return genuinely depends on, presents the return surface across them, and states the entry price at which the base case stops clearing the hurdle -- when you need a walk-away price rather than a range of hopes.
What it loads into context
Frontmatter
58 tokensAlways available to the agent
SKILL.md
1,343 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Returns Sensitivity
## When to use
Use this skill once a base case exists and the question turns to how much of the return is assumption. It is the discipline that runs before a final bid, and again whenever someone proposes stretching for the asset. Its output is a single number the deal team commits to in advance: the price above which the base case no longer clears the fund's own hurdle.
## What it does
Produces a sensitivity note: a one-at-a-time elasticity test that separates the variables that move the return from the ones that decorate it, a return surface across the two that survive, a note of which of them the sponsor actually controls, and a stated walk-away price in both multiple and enterprise value.
## Method
### Step 1 -- Strip the collinear variables before flexing anything
View the complete source on GitHubRisk and Mitigant Register
When your agent uses it
Builds a live risk register pairing every material risk with a named mitigant, an owner and a residual assessment, when you need to show which risks are priced into the bid and which are simply accepted.
What it loads into context
Frontmatter
51 tokensAlways available to the agent
SKILL.md
1,009 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Risk and Mitigant Register
## When to use
Use this skill from the point diligence findings start landing through to the first board meeting after close. The IC memo carries a risk matrix; this is the instrument behind it, kept live and handed over at completion. Reach for it when the risk section reads as a list of things that might go wrong rather than decisions taken.
## What it does
Produces a register in which each risk is sized in the currency of the deal, matched to one mitigant with one named owner and a date, assessed for what remains after it, and classified as priced, transferred, mitigated or accepted -- ending with the accepted risks on one page.
## Method
1. **Harvest, never invent.** Every entry traces to a finding in a workstream, cited by source. Generic risks -- competition, cyclicality, key person -- are cut unless a finding gives them a number.
2. **Size before you rank.** Express each risk as EBITDA at risk, enterprise value at risk, or months of delay. "Customer concentration" is not a risk; "the top customer, 18% of revenue, renews eleven months after close" is.View the complete source on GitHubThesis Development
When your agent uses it
Turns a vague sector interest into a written investment thesis with a falsifiable core claim, must-be-true conditions and kill criteria set in advance -- when you need a thesis diligence can disprove.
What it loads into context
Frontmatter
46 tokensAlways available to the agent
SKILL.md
1,005 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Thesis Development
## When to use
Use this skill before a market map exists and long before a target is named, when the partnership has an interest ("we like industrial services") but no written claim anyone can argue with. Use it also when a thesis has drifted into defending consecutive passes.
## What it does
Produces a short thesis document: sub-sector boundary, the core claim in falsifiable form, where in the EBITDA bridge the return is created, the why-now catalyst, must-be-true conditions with owners, kill criteria agreed in advance, and the entry multiple range supported. It is written to be attacked, not to survey a sector.
## Method
### Step 1 -- Draw the boundary before writing anything
View the complete source on GitHubThird-Party Advisor Brief
When your agent uses it
Produces the scope document for an external diligence provider -- the questions to answer, the deliverable format, the materiality threshold and the explicit exclusions -- for when you need the output to change a decision rather than describe a market.
What it loads into context
Frontmatter
56 tokensAlways available to the agent
SKILL.md
1,146 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Third Party Advisor Brief
## When to use
Use this skill before engaging any external provider on a live deal: commercial diligence, QoE, technology, insurance, ESG, or an operational specialist. Providers write to the scope they are given. A scope framed as topics -- "assess the competitive landscape" -- produces a competent report that changes nothing, billed in full. A scope framed as questions with decisions attached produces findings you can price.
## What it does
Produces an engagement brief covering the decision the work informs, the numbered questions to answer, the materiality and de-minimis thresholds, the deliverable format and interim read-out dates, the explicit exclusions, the fee structure with phasing and change control, and the reliance position.
## Method
### Step 1 -- State the decision and its date
View the complete source on GitHubVendor Due Diligence
When your agent uses it
Commissions and controls sell-side due diligence -- scope, provider selection, reliance architecture, and the handling of adverse findings -- when you need a VDD pack that survives a buyer's confirmatory diligence rather than one that collapses in exclusivity.
What it loads into context
Frontmatter
59 tokensAlways available to the agent
SKILL.md
1,326 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
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# Vendor Due Diligence
## When to use
Use this skill once the exit route is chosen and before the advisor drafts the CIM, because the VDD databook is what the CIM's financials must reconcile to. It is also the right skill when a known issue exists and the team is deciding whether to disclose it, fix it first, or leave it for the buyer to find. It is worth commissioning where the buyer set is broad or where lenders need a report they can rely on; on a bilateral sale to one known buyer it often is not.
## What it does
Produces: a VDD scope specification by workstream; a provider and reliance plan; a working protocol that keeps the sponsor in control of scope without touching conclusions; a decision framework for adverse findings; and the reconciliation rules that keep the VDD, the databook, the CIM and the model telling one story.
## Method
### Step 1 -- Decide what the VDD is buying
View the complete source on GitHubaccretion-dilution-tester
When your agent uses it
Run a defensible accretion/dilution analysis with the financing, synergy, and tax mechanics that actually move EPS. Use when pricing an M&A transaction with a public-company acquirer, framing a stock-vs-cash consideration mix, or stress-testing IC and board materials. Built around purchase-price mechanics, financing mix, synergy timing, tax shield, intangible amortization, and disciplined sensitivity.
What it loads into context
Frontmatter
93 tokensAlways available to the agent
SKILL.md
3,360 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Governing Principle
- The Five Mechanics That Move Accretion
- Workflow
- Hypotheses to Pressure-Test
- Quality Checks Before Sharing
- Common Failure Modes
- Deliverable
Files
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# Accretion / Dilution Tester
## Purpose
Produce an accretion/dilution analysis that holds up under board, sell-side analyst, and rating-agency scrutiny — built from a defensible sources-and-uses, the right financing mix at market rates, realistic synergy timing, and a tax model that reflects actual deal mechanics.
The output is not a single accretion number. It is a sensitivity table that shows the path from "what we believe" to "what would have to be true" — and a written paragraph on where the deal lives within that sensitivity.
## Governing Principle
**Synergies decide the deal. Financing decides the day-one math. Neither is what's in the IC deck — the IC deck shows the punchline.**
A weak accretion analysis lets the headline accretion number do the work and hides the synergies, the financing assumptions, and the share count mechanics that produced it. A strong analysis shows all three transparently and lets the reader see what the deal really requires.
View the complete source on GitHubcapital-allocation-advisor
When your agent uses it
Ranks competing uses of capital (reinvest in the core, M&A, debt paydown, buyback, dividend, cash buffer) by value creation, scoring each on its return spread over cost of capital subject to leverage, liquidity, and covenant constraints. Triggers on "capital allocation", "use of cash", "deploy capital", "buyback vs debt", "where to invest excess cash", "reinvest or return", "allocation framework", "capital plan".
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
1,715 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it produces
- Method
- Inputs
- Output format
- Quality bar
- Example
Files
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# Capital Allocation Advisor
## When to use
Use when the CFO must decide how to deploy available capital across competing uses and wants the choices ranked by value creation with the logic exposed. Typical triggers:
- An annual capital plan or capital-return policy review.
- A windfall, refinancing, or asset-sale event that frees up cash.
- A board discussion on buyback versus dividend versus debt paydown.
- A "what should we do with the cash" or "reinvest or return" question.
This is portfolio-of-uses allocation across the whole capital base. It is not the standalone valuation of one acquisition target.
## What it produces
A ranked capital-allocation table that lists each use of capital, its estimated marginal return, the cost-of-capital hurdle it clears or fails, the spread between the two, the constraints it touches, and a strategic-fit note. It ends with a recommended allocation of the available pool and the conditions that would change the ranking.
## Method
1. Size the allocable pool. Only surplus capital is allocable.View the complete source on GitHubcim-red-flag-reviewer
When your agent uses it
Read a sell-side CIM the way a sharp buyer's MD reads it — surfacing quality-of-earnings risks, narrative gaps, and unsupported claims. Use on the buy-side when evaluating a teaser or CIM, on the sell-side as a pre-launch stress test, or when preparing IOI / LOI logic. Built around quality-of-earnings, concentration, sustainability, working capital and capex realism, and narrative pressure-testing.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
3,144 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Governing Principle
- The Seven Risk Areas Every CIM Review Must Cover
- Workflow
- Hypotheses to Pressure-Test
- Quality Checks Before Sharing
- Common Failure Modes
- Deliverable
Files
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# CIM Red-Flag Reviewer
## Purpose
Surface the issues a CIM is designed to softly de-emphasize — quality-of-earnings risks, customer concentration realities, margin sustainability questions, working capital and capex realism, narrative-vs-evidence gaps — before they show up in management diligence, QofE, or worst, post-close.
The output is not a critique of the CIM. It is a working risk register that informs an IOI / LOI structure on the buy-side or a pre-launch CIM tightening on the sell-side.
## Governing Principle
**Every CIM is a sales document. Read it as a sales document, not as a description.**
Sell-side advisors are paid to present the business at its best. A buyer who reads the CIM at face value is reading the answer; a sharp buyer reads the CIM looking for what the answer is leaving out.
View the complete source on GitHubcompany-teardown
When your agent uses it
Reverse-engineer a target's business model, unit economics, growth drivers, and risk profile from disclosed and inferred data. Use at the start of any sell-side or buy-side mandate, before drafting a CIM section, pitching coverage, or building a financial model. Built around revenue decomposition, cost-structure analysis, capital intensity, and concentration risk.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
2,705 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Governing Principle
- The Six Lenses Every Teardown Must Cover
- Workflow
- Hypotheses to Pressure-Test
- Quality Checks Before Sharing
- Common Failure Modes
- Deliverable
Files
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# Company Teardown
## Purpose
Build a fact-based working view of a company — how it makes money, what it actually costs to run, what its capital intensity looks like, who its customers and suppliers are, and where its risks concentrate — before any valuation or model is built.
The teardown is the foundation. A model built on a misread of the business will be precise and wrong.
## Governing Principle
**Read the business before you read the multiple.**
The model is downstream of the teardown. The valuation is downstream of the model. The recommendation is downstream of the valuation. Skip the teardown and every downstream layer is contaminated.
View the complete source on GitHubearnings-and-filings-teardown
When your agent uses it
Extracts the financially material content from 10-K, 10-Q, and 8-K filings and earnings call transcripts into a structured one page brief with a source location on every number. Triggers when someone asks to tear down a filing or earnings release, summarize a 10-K or 10-Q, pull KPIs guidance and risks from a transcript, or brief the CFO on what a company reported.
What it loads into context
Frontmatter
93 tokensAlways available to the agent
SKILL.md
1,392 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it produces
- Method
- Inputs
- Output format
- Quality bar
- Example
Files
SKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytesSKILL.mdcore6,224 bytes
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# Earnings and Filings Teardown
## When to use
Use when the office of the CFO needs the financially material substance of a public disclosure distilled fast and traceably.
- A competitor's or the company's own 10-K, 10-Q, or 8-K landed and needs a read.
- An earnings call transcript needs to be reduced to KPIs, guidance, and risks.
- Pre or post earnings prep, or an audit committee read ahead.
- A benchmarking or planning workstream needs clean, sourced inputs from a filing.
The signal is a filing or transcript in hand and a need for reported KPIs, segment detail, guidance, risks, capital actions, and one time items, each tied to where it was found.
## What it producesView the complete source on GitHubic-memo-drafting
When your agent uses it
Draft an investment committee memo covering deal thesis, business quality summary, diligence findings, risk matrix, returns analysis, and recommendation -- in the format senior investment professionals expect.
What it loads into context
Frontmatter
43 tokensAlways available to the agent
SKILL.md
1,920 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore9,346 bytes
Read SKILL.md
# IC Memo Drafting
## When to use
Use this skill after diligence is substantially complete and the deal team has formed a clear view on the opportunity. The IC memo is the written argument for (or against) the investment decision -- it must be complete, balanced, and defensible under cross-examination from senior investment professionals, LPs, and in some cases, internal risk committees. Use it to draft the memo, stress-test the argument, and ensure no material finding from diligence is omitted.
## What it does
Produces a structured IC memo draft covering all standard sections: executive summary, business description, deal overview, market and competitive position, management assessment, diligence findings, financial analysis, returns, risk matrix, and recommendation. The draft is written in institutional investment prose -- direct, evidence-based, no marketing language.
## Method
### Step 1 -- Executive summary (write last, present first)
View the complete source on GitHublbo-returns-analysis
When your agent uses it
Build a structured LBO returns analysis with bear/base/bull scenarios, MOIC and IRR sensitivity to entry multiple and leverage, and covenant headroom assessment.
What it loads into context
Frontmatter
42 tokensAlways available to the agent
SKILL.md
2,037 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- What it does
- Method
- Inputs
- Output format
- Example
Files
SKILL.mdcore9,537 bytes
Read SKILL.md
# Financial Scenario Modelling
## When to use
Use this skill when you need to build or stress-test the returns analysis for an LBO acquisition. It is most useful in three situations: (1) ahead of an indicative bid, when you need to establish the range of supportable entry prices; (2) ahead of a final bid, when you need to refine the model with updated diligence data; or (3) ahead of the IC memo, when you need to present returns under clearly defined scenarios with transparent assumptions. This skill structures the logic and the sensitivity analysis -- it does not replace a live Excel model, but it defines what that model must contain and what assumptions to test.
## What it does
Produces: (1) a structured LBO model logic description (sources and uses, capital structure, operating assumptions, exit assumptions); (2) bear/base/bull scenario assumptions clearly differentiated; (3) a returns sensitivity table described in prose (MOIC and IRR vs entry multiple and exit multiple, and vs leverage and interest rate); and (4) a covenant headroom analysis and downside protection assessment.
## Method
### Step 1 -- Sources and uses of funds
View the complete source on GitHubprecedent-transaction-screener
When your agent uses it
Build a screened, cycle-adjusted set of M&A precedents that actually inform pricing. Use when building the precedent page of a valuation deck, pressure-testing a control-premium thesis, or framing a buy-side bid against historical comparables. Built around screening discipline, cycle and structure adjustments, and synergy calibration.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
2,542 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Governing Principle
- The Five Filters Every Precedent Set Must Pass
- Workflow
- Hypotheses to Pressure-Test
- Quality Checks Before Sharing
- Common Failure Modes
- Deliverable
Files
SKILL.mdcore12,027 bytes
Read SKILL.md
# Precedent Transaction Screener
## Purpose
Identify the M&A transactions that genuinely inform what a control buyer would pay for this target — and discard the ones that look comparable but were priced under conditions that no longer apply.
The output is not a long list of "transactions in the sector." It is a tight set of true comparables, calibrated for cycle, deal structure, and buyer type, with the multiples that should actually anchor the valuation conversation.
## Governing Principle
**A precedent is only useful if you would re-do the deal at the same multiple today. If not, adjust or discard.**
Bad precedent work pads the page with deal count. Good precedent work cuts the list down to the five to fifteen transactions that an experienced buyer or seller would actually negotiate against.
View the complete source on GitHubpriced-round-dilution
When your agent uses it
A founder wants to compare simple priced-equity financing scenarios. Produces A pre/post-money and ownership bridge with explicit instrument exclusions.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
209 tokensWhen the skill is activated
Reference documents
348 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
Scripts executed separately
scripts/dilution.py
Files
SKILL.mdcore1,038 bytesreferences/working-templates.mddoc1,774 bytesscripts/dilution.pyruns1,020 bytesscripts/illustrative-inputs.jsonasset151 bytes
Read SKILL.md
# Priced-round dilution
Read references/working-templates.md. Collect pre-money equity value, new cash, fully diluted pre-round shares and any existing holder’s shares. In a simple round with no other changes, post-money equals pre-money plus new cash, price per share equals pre-money divided by pre-round shares, and new investor ownership equals new cash divided by post-money. Reconcile new and existing shares and ensure ownership sums to 100 percent. Use scripts/dilution.py for this exact simple case. If SAFEs, notes, option-pool top-ups, warrants, secondary shares or fees are present, stop using the simple calculator and build a term-specific model from the actual documents. Distinguish cash going to the company from secondary proceeds. Present raw terms and questions for counsel; do not choose a deal for the user.View the complete source on GitHubstartup-valuation-brief
When your agent uses it
An early-stage company needs a supportable valuation discussion. Produces A method-selection memo, assumptions ledger and defensible scenario range.
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
195 tokensWhen the skill is activated
Reference documents
348 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
Files
SKILL.mdcore1,088 bytesreferences/working-templates.mddoc1,774 bytes
Read SKILL.md
# Startup valuation brief
Read references/working-templates.md. Establish purpose, date, currency, stage, capital structure and information availability. Distinguish enterprise value and equity value, pre-money and post-money, and a convertible valuation cap from a priced valuation. Select methods that data supports and explain rejected alternatives. For DCF, disclose revenue, margin, reinvestment, discount rate, terminal growth and survival assumptions; do not present a mechanically precise result as certainty. For comparable methods, require sourced dated metrics and disclose selection limitations. Bridge enterprise to equity value with cash, debt and other claims when relevant. Produce a range with sensitivity and an evidence ledger. If material data is absent, return a preparation plan or illustrative scenarios explicitly labelled as such, not a fabricated valuation.View the complete source on GitHubtrading-comps-builder
When your agent uses it
Construct a clean trading comps universe with disciplined peer selection, calendarization, EBITDA adjustments, and outlier treatment. Use when building the comps page of a valuation deck, framing a minority valuation reference, or pressure-testing a public-market reference range. Built around peer comparability, metric normalization, and the difference between a peer and a peer-shaped distractor.
What it loads into context
Frontmatter
79 tokensAlways available to the agent
SKILL.md
2,557 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Governing Principle
- The Three Tests of a True Peer
- Workflow
- Hypotheses to Pressure-Test
- Quality Checks Before Sharing
- Common Failure Modes
- Deliverable
Files
SKILL.mdcore12,049 bytesSKILL.mdcore12,049 bytesSKILL.mdcore12,049 bytes
Read SKILL.md
# Trading Comps Builder
## Purpose
Build a defensible public trading comparables set that supports a minority-stake valuation reference, frames the public-market view of the target, and survives a sharp counterparty's review.
The output is a small set of true peers — typically 6 to 12 — with clean, calendarized metrics, consistent EBITDA adjustments, and a documented rationale for inclusion or exclusion of every name considered.
## Governing Principle
**A peer is a company whose multiple a sophisticated investor would actually use to price the target. Everything else is a distractor.**
The discipline is in what gets cut, not in what gets added. A comps page with 25 names is usually a comps page with 6 peers and 19 things hiding the analysis.
View the complete source on GitHubvaluation-triangulator
When your agent uses it
Build a defensible valuation range across DCF, trading comps, precedent transactions, LBO, and premiums paid. Use when pricing a sell-side mandate, framing a buy-side bid, preparing a fairness-style readout, or pressure-testing an IC valuation page. Built around methodology triangulation, the football field, and the bridge from enterprise value to equity value per share.
What it loads into context
Frontmatter
83 tokensAlways available to the agent
SKILL.md
2,858 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- Governing Principle
- The Five Lenses Every Valuation Must Triangulate
- Workflow
- Hypotheses to Pressure-Test
- Quality Checks Before Sharing
- Common Failure Modes
- Deliverable
Files
SKILL.mdcore13,430 bytesSKILL.mdcore13,430 bytes
Read SKILL.md
# Valuation Triangulator
## Purpose
Produce a valuation range that survives a senior banker's review and a sophisticated counterparty's diligence — anchored in multiple methodologies, reconciled where they disagree, and translated cleanly from enterprise value down to equity value per share.
The output is not a number. It is a defended range, a football field, and a written view on which methodology should carry the most weight in this specific situation.
## Governing Principle
**Every valuation methodology is wrong on its own. The triangulation is the answer.**
A single methodology produces a number. Triangulation produces a thesis. Senior bankers do not pick a method; they reconcile across methods and explain the gaps.
View the complete source on GitHubSkills included
- bridge-and-acquisition-financing
- buyer-targeting
- capital-structure
- carve-out-analysis
- cim-pitchbook
- company-research
- comparable-analysis
- compliance
- covenant-package-analysis
- cross-border-deal-considerations
- data-room
- dcf-modeling
- deal-pipeline-tracker
- deal-structuring
- debt-sourcing
- due-diligence
- earnout-structuring
- equity-sourcing
- equity-story-development
- escrow-and-indemnity
- fairness-opinion
- financial-modeling
- financing-strategy
- industry-analysis
- investor-targeting
- ipo-readiness-assessment
- knowledge-base
- lbo-modeling
- management-deck
- management-incentive-plan
- market-intelligence
- merger-analysis
- nda-tracking
- negotiation-support
- objection-handling
- offer-evaluation
- outreach-email
- post-deal-monitoring
- precedent-transactions
- purchase-price-allocation
- qa-preparation
- quality-control
- rating-agency-presentation
- regulatory-and-antitrust-review
- reporting
- risk-assessment
- roadshow
- scenario-analysis
- sell-side-process-letter
- sensitivity-analysis
- sum-of-the-parts-valuation
- syndication
- synergy-quantification
- task-management
- teaser-one-pager
- term-sheet
- timeline-milestones
- valuation-analysis
- working-capital-adjustment
- workstream-coordinator
- Add-On Acquisition Pipeline
- Buyer Narrative and Positioning
- CIM Teardown
- Commercial Analysis
- Competitive Moat Review
- Customer Cohort Analysis
- Deal Screening
- Debt Package Sizing
- Diligence Architecture
- Diligence Workstream Plan
- Exit Options Review
- Exit Preparation
- Financial Scenario Modelling
- Hundred-Day Plan
- IC Memo Drafting
- Information Gap Log
- Investment Committee Q&A
- LBO Structuring
- Management Presentation Review
- Market Map and Sourcing
- Operating KPI Cadence
- Portfolio Value Creation
- Pricing Power Assessment
- Proprietary Angle Assessment
- Red Flag Register
- Returns Sensitivity
- Risk and Mitigant Register
- Thesis Development
- Third-Party Advisor Brief
- Vendor Due Diligence
- accretion-dilution-tester
- capital-allocation-advisor
- cim-red-flag-reviewer
- company-teardown
- earnings-and-filings-teardown
- ic-memo-drafting
- lbo-returns-analysis
- precedent-transaction-screener
- priced-round-dilution
- startup-valuation-brief
- trading-comps-builder
- valuation-triangulator
Repository facts
- License
- MIT
- Created
- Sep 8, 2026
- Last pushed
- Sep 10, 2026
- Forks
- 6
- Open issues
- 0
- Project activity
- Active
Before you install
Local scriptsAutomated signals, not a guarantee
Checked Nov 7, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 27 notes
packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/investment-banking/skills/nda-tracking/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/investment-banking/skills/quality-control/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/investment-banking/skills/quality-control/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/investment-banking/skills/rating-agency-presentation/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/investment-banking/skills/regulatory-and-antitrust-review/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/add-on-acquisition-pipeline/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/commercial-analysis/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/deal-screening/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/diligence-architecture/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/diligence-workstream-plan/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/operating-kpi-cadence/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/operating-kpi-cadence/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/private-equity/skills/third-party-advisor-brief/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/cim-red-flag-reviewer/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/cim-red-flag-reviewer/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/company-teardown/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/earnings-and-filings-teardown/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/earnings-and-filings-teardown/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/earnings-and-filings-teardown/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- 6 network referencesin 2 files: priced-round-dilution/references/working-templates.md:42 startup-valuation-brief/references/working-templates.md:42
- No hidden or obfuscated text
- No instruction overrides
- 1 executable scriptin 1 file: priced-round-dilution/scripts/dilution.py:1
- No access to secrets
- No requests to vote in Hot
Show all 7 signals by file
skills/priced-round-dilution/references/working-templates.md
- Network accessline 42
- Claude skill upload guide: https://support.claude.com/en/articles/12512180-use-skills-in-claude - Network accessline 43
- NYU Stern valuation resources: https://pages.stern.nyu.edu/~adamodar/ - Network accessline 44
- YC financing documents and SAFE resources: https://www.ycombinator.com/documents
skills/priced-round-dilution/scripts/dilution.py
- Executable scriptline 1
Executable file
skills/startup-valuation-brief/references/working-templates.md
- Network accessline 42
- Claude skill upload guide: https://support.claude.com/en/articles/12512180-use-skills-in-claude - Network accessline 43
- NYU Stern valuation resources: https://pages.stern.nyu.edu/~adamodar/ - Network accessline 44
- YC financing documents and SAFE resources: https://www.ycombinator.com/documents
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Signal confidence: 7 facts
- Network access in prose of documentationpriced-round-dilution/references/working-templates.md:42Low confidence
- Network access in prose of documentationpriced-round-dilution/references/working-templates.md:43Low confidence
- Network access in prose of documentationpriced-round-dilution/references/working-templates.md:44Low confidence
- Executable script in prose of a file that runspriced-round-dilution/scripts/dilution.py:1Low confidence
- Network access in prose of documentationstartup-valuation-brief/references/working-templates.md:42Low confidence
- Network access in prose of documentationstartup-valuation-brief/references/working-templates.md:43Low confidence
- Network access in prose of documentationstartup-valuation-brief/references/working-templates.md:44Low confidence
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md packs/investment-banking/skills/bridge-and-acquisition-financing/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.