Not in the top 1,000 by GitHub stars
kesslernity/awesome-copilot-cowork-bots
23 ready-to-upload bots for Microsoft 365 Copilot Cowork. Read-and-prepare first: sending, posting and deleting stay behind an approval you give each time. Finance, people, IT, projects, comms. MIT.
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/comms/brand-answer-monitor/skill/SKILL.md
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Heat
Insufficient historyNot enough history yet to measure heat. It appears after a few days of data.
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
- brand-answer-monitor
packs/comms/brand-answer-monitor/skill - competition-monitor
packs/comms/competition-monitor/skill - internal-newsletter-builder
packs/comms/internal-newsletter-builder/skill - leadership-update-drafter
packs/comms/leadership-update-drafter/skill - calendar-defender
packs/core-executive/calendar-defender/skill - budget-variance-explainer
packs/finance-finops/budget-variance-explainer/skill - cloud-cost-digest
packs/finance-finops/cloud-cost-digest/skill - expense-reconciliation
packs/finance-finops/expense-reconciliation/skill - invoice-vendor-followup
packs/finance-finops/invoice-vendor-followup/skill - subscription-hunter
packs/finance-finops/subscription-hunter/skill - change-advisory-prep
packs/it-ops/change-advisory-prep/skill - defect-intake-triage
packs/it-ops/defect-intake-triage/skill - incident-digest
packs/it-ops/incident-digest/skill - internal-expert-finder
packs/people-hr/internal-expert-finder/skill - interview-loop-coordinator
packs/people-hr/interview-loop-coordinator/skill - onboarding-buddy
packs/people-hr/onboarding-buddy/skill - document-transmittal-tracker
packs/projects/document-transmittal-tracker/skill - lessons-learned-harvester
packs/projects/lessons-learned-harvester/skill - rfi-query-tracker
packs/projects/rfi-query-tracker/skill - account-expert
packs/sales-bd/account-expert/skill - one-to-one-prep
packs/team-lead/one-to-one-prep/skill - project-decomposer
packs/team-lead/project-decomposer/skill - team-lead-mode
packs/team-lead/team-lead-mode/skill - bot-template
templates/bot-template/skill
How it works
brand-answer-monitor
When your agent uses it
Tracks how the open web describes the brand on the questions that matter, and builds a weekly trend sheet of what a research tool finds when it looks the brand up. Use when the user asks how the brand is being described, what sources say about the company, to track brand visibility, or to see whether published positioning is being picked up.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
802 tokensWhen the skill is activated
Reference documents
100 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,675 bytesreferences/config.mddoc396 bytes
Read SKILL.md
# Brand Answer Monitor
Tracks what a researcher finds when they look you up, week over week.
🔴 **Read this before using it.** The original idea was to track the brand's position inside
ChatGPT, Gemini and Perplexity answers. **This skill does not do that, and cannot.** Those are
competitor products behind their own interfaces, not open-web sources, and nothing in Cowork's
documentation establishes that Deep Research can query them. Shipping an "AEO tracker" on that
assumption would be inventing a capability.
What this does instead is honest and still useful: it records **what Deep Research surfaces about
the brand on a fixed set of questions**, week over week, so movement in sources and framing is
visible. Treat it as a proxy for what a research tool sees, not as a measurement of any specific
assistant's answer. If you later confirm a way to query those assistants, this skill's trend sheetView the complete source on GitHubcompetition-monitor
When your agent uses it
Watches a named list of competitors and reports only when something materially changed, staying silent when nothing did. Use when the user asks what competitors have changed, to monitor competitor pricing or positioning, or to set up a competitive watch.
What it loads into context
Frontmatter
52 tokensAlways available to the agent
SKILL.md
782 tokensWhen the skill is activated
Reference documents
123 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,541 bytesSKILL.mdcore3,541 bytesSKILL.mdcore3,541 bytesSKILL.mdcore3,541 bytesreferences/config.mddoc532 bytes
Read SKILL.md
# Competition Monitor
Reports a material change and nothing else. **The suppression is the product.**
**How this differs from a news digest.** A digest finds five to eight items because five to eight
is the target. This finds zero items most weeks, and that is the correct output. A monitor that
always reports something is a monitor its reader stops opening within a month.
## Inputs
- **Deep Research** over the competitor list
- `references/config.md` for competitors, the watch list and what counts as material
- The prior run's output, read from the output folder, which is how "changed" is possible at all
## ProcedureView the complete source on GitHubinternal-newsletter-builder
When your agent uses it
Builds a dated internal newsletter draft from the period's real material, every item sourced to the thing it describes, with nothing invented to fill a section. Use when the user asks to draft the internal newsletter, build the team update, prepare the monthly round-up, or says the newsletter is due.
What it loads into context
Frontmatter
68 tokensAlways available to the agent
SKILL.md
628 tokensWhen the skill is activated
Reference documents
79 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,939 bytesSKILL.mdcore2,939 bytesreferences/config.mddoc377 bytes
Read SKILL.md
# Internal Newsletter Builder
Builds the round-up from what actually happened, and leaves a section out rather than filling it.
## Inputs
- **Enterprise Search**, **Email** and **Meetings** over the period
- `references/config.md` for the sections, the audience and what is never included
## Procedure
1. **Gather** the period's material: shipped work, decisions taken, documents published, meetings
that produced an outcome, new joiners if config allows it.
2. **Place each item in exactly one section** from config. An item that fits none is dropped, not
relocated into the nearest.
3. **For each item, write**: one sentence on what happened, one on why it matters to thisView the complete source on GitHubleadership-update-drafter
When your agent uses it
Drafts a leadership update in a fixed structure from the period's evidence, keeping facts and inferences visibly separate and stating what is not known. Use when the user asks to draft a leadership update, prepare a status note for the executive, write the weekly update to the sponsor, or says an update is due upward.
What it loads into context
Frontmatter
74 tokensAlways available to the agent
SKILL.md
674 tokensWhen the skill is activated
Reference documents
108 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,050 bytesreferences/config.mddoc412 bytes
Read SKILL.md
# Leadership Update Drafter
Writes the upward update in a fixed shape, with the uncomfortable parts kept in.
**How this differs from `write-like-me`.** That skill learns a voice and writes in it. This one
imposes a structure and protects the honesty of the content. If both are installed, this provides
the skeleton and that provides the register.
## Inputs
- **Email**, **Meetings** and **Enterprise Search** over the period
- `references/config.md` for the structure, the audience and the escalation bar
## Procedure
1. **Gather** the period's evidence for each section of the configured structure.View the complete source on GitHubcalendar-defender
When your agent uses it
Reviews the week ahead for double-bookings, meetings with no agenda or no decision to make, and lost focus time, then proposes specific changes without making any of them. Use when the user asks to review their calendar, find conflicts, protect focus time, says their week is overbooked, or wants to clean up next week.
What it loads into context
Frontmatter
75 tokensAlways available to the agent
SKILL.md
743 tokensWhen the skill is activated
Reference documents
93 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,415 bytesreferences/config.mddoc312 bytes
Read SKILL.md
# Calendar Defender
Finds the week's conflicts and the meetings that should not exist, and proposes, never acts.
## Inputs
- **Calendar Management** for the week ahead
- **Email** and **Meetings** for whether an agenda exists and what each meeting is for
- `references/config.md` for focus-time targets, working hours and meetings never touched
## Procedure
1. **Load the window** from config, normally the next seven days.
2. **Find hard conflicts**: overlapping accepted meetings. For each, say which has more attendees,
which is recurring, and which has an agenda, so the user can choose.
3. **Find meetings with no stated purpose**: no agenda in the invitation, no linked document, noView the complete source on GitHubbudget-variance-explainer
When your agent uses it
Drafts the narrative behind a budget variance from the context the user supplies and the discussion in mail and meetings, never producing or changing the figure itself. Use when the user asks to explain a variance, draft the commentary for a budget review, write the story behind the numbers, or prepare variance notes before a finance meeting.
What it loads into context
Frontmatter
75 tokensAlways available to the agent
SKILL.md
658 tokensWhen the skill is activated
Reference documents
74 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,048 bytesSKILL.mdcore3,048 bytesreferences/config.mddoc320 bytes
Read SKILL.md
# Budget Variance Explainer
Writes the story behind a number somebody else owns.
🔴 **This skill never produces a figure.** The user supplies the variance. The skill explains it.
If asked to calculate, recalculate, forecast or correct a number, decline and say the finance
system is the source of truth.
## Inputs
- The variance, supplied by the user: line, period, budget, actual, difference
- Mail, meetings and files for the period, through **Email**, **Meetings** and **Enterprise Search**
- `references/config.md` for the cost-centre vocabulary and the house commentary structure
## ProcedureView the complete source on GitHubcloud-cost-digest
When your agent uses it
Turns cloud billing exports and provider alert emails into a short digest of what moved, what is anomalous and what to ask an owner about. Use when the user asks about cloud spend, what changed on the bill, why costs went up, to prepare a FinOps review, or to explain a cost spike.
What it loads into context
Frontmatter
71 tokensAlways available to the agent
SKILL.md
705 tokensWhen the skill is activated
Reference documents
78 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,232 bytesSKILL.mdcore3,232 bytesreferences/config.mddoc339 bytes
Read SKILL.md
# Cloud Cost Digest
Explains what moved on the bill, with the question to ask each owner.
## Inputs
- A billing export the user supplies, through **Excel**
- Provider alert and budget emails, through **Email**
- `references/config.md` for the materiality floor, owner mapping and the comparison period
## Procedure
1. **Load the export.** Without it, say so and stop. Alert emails alone cannot produce a digest;
they can produce an alert summary, which is a different and lesser thing.
2. **Compare** the current period against the comparison period in config, by service and by the
tag or account that config names as the ownership dimension.View the complete source on GitHubexpense-reconciliation
When your agent uses it
Reconciles submitted expense claims against the receipts and statements sitting in the mailbox, lists what is missing or unmatched, and drafts the chaser to each claimant. Use when the user asks to reconcile expenses, check expense claims, find missing receipts, chase expense documentation, or prepare the expense pack before a close.
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
639 tokensWhen the skill is activated
Reference documents
111 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,893 bytesSKILL.mdcore2,893 bytesreferences/config.mddoc461 bytes
Read SKILL.md
# Expense Reconciliation
Finds the gap between what was claimed and what was evidenced, before someone else does.
## Inputs
- Mailbox, through **Email**, for receipts, card statements and claim confirmations
- A claims export the user supplies, through **Excel**
- `references/config.md` for the period, the materiality threshold and the policy rules to check
## Procedure
1. **Load the claims export.** If none is supplied, say so and stop: reconciliation without the
claim side is not reconciliation, it is a receipt hunt. Offer that instead.
2. **Gather evidence** from the mailbox over the period: receipts, invoices, card statements.
3. **Match** each claim to evidence on amount, date within the config tolerance, and merchant.View the complete source on GitHubinvoice-vendor-followup
When your agent uses it
Finds invoice and payment threads in the mailbox that have gone unanswered, ages them, and drafts the follow-up to each counterparty. Use when the user asks what invoices are outstanding, which vendors have not replied, to chase payment or payment queries, or to prepare the aged follow-up list before a finance review.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
601 tokensWhen the skill is activated
Reference documents
122 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,772 bytesSKILL.mdcore2,772 bytesSKILL.mdcore2,772 bytesreferences/config.mddoc398 bytes
Read SKILL.md
# Invoice & Vendor Follow-up
Finds the invoice threads that stopped, with age and amount, and drafts the nudge.
## Inputs
- Mailbox, through **Email**
- `references/config.md` for the ageing buckets, the chase ladder and who is never chased
## Procedure
1. **Find invoice threads** over the window: invoices sent or received, payment queries, disputes,
remittance advice.
2. **Determine the state of each thread** from the last message only: awaiting their reply,
awaiting ours, resolved, or ambiguous. Ambiguous is a valid answer and must not be guessed.
3. **Age** from the last message in the thread, not from the invoice date, and bucket by config.View the complete source on GitHubsubscription-hunter
When your agent uses it
Finds every recurring subscription, license and service renewal hiding in the user's mailbox and files, and builds a dated renewal calendar with a drafted cancellation or renegotiation reply for each one. Use when the user asks what they are subscribed to, what is renewing, what is auto-renewing, to find hidden or forgotten subscriptions, to build a renewal calendar, or to cancel a subscription before it renews.
What it loads into context
Frontmatter
89 tokensAlways available to the agent
SKILL.md
1,167 tokensWhen the skill is activated
Reference documents
187 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Config
- Procedure
- Output
- Definition of done
- When there is no data, or the data is stale
- Boundaries
- Self-check before returning
Files
SKILL.mdcore5,239 bytesSKILL.mdcore5,239 bytesSKILL.mdcore5,239 bytesSKILL.mdcore5,239 bytesSKILL.mdcore5,239 bytesreferences/config.mddoc773 bytes
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# Subscription Hunter
Surfaces every recurring charge in the mailbox before it renews itself, with a drafted reply ready
for the ones that should stop.
## Inputs
- The user's mailbox, through the **Email** built-in skill
- Organization files and contracts, through **Enterprise Search**
- `references/config.md` for the lookback window, the value threshold and the ignore list
## Config
Read `references/config.md` first. If it is missing, use: 24-month lookback, report everythingView the complete source on GitHubchange-advisory-prep
When your agent uses it
Assembles the pack for the next change advisory board from the change requests, threads and documents already circulating, with the risk and rollback position for each change stated or marked missing. Use when the user asks to prepare for CAB, build the change board pack, review upcoming changes, or says a change board is coming up.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
599 tokensWhen the skill is activated
Reference documents
47 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,742 bytesreferences/config.mddoc171 bytes
Read SKILL.md
# Change Advisory Board Prep
Builds the pack from what people actually wrote, and names every change that arrived without a
rollback plan.
## Inputs
- **Email** and Teams traffic about upcoming changes
- **Enterprise Search** for change records, runbooks and prior post-incident notes
- `references/config.md` for the board date, the required fields and the risk vocabulary
## Procedure
1. **Find the changes** proposed for the board window.
2. **For each change, extract the required fields** from config. The usual set: what changes, who
owns it, the window, affected systems, risk rating as stated by the proposer, rollback plan,View the complete source on GitHubdefect-intake-triage
When your agent uses it
Turns a reported problem in mail or Teams into a structured, ticket-ready intake with the evidence attached and the gaps named, then an Adaptive Card for approval before anything is filed. Use when the user asks to triage a bug report, turn a complaint into a ticket, prepare a defect for filing, or says a user reported a problem.
What it loads into context
Frontmatter
79 tokensAlways available to the agent
SKILL.md
730 tokensWhen the skill is activated
Reference documents
94 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,368 bytesreferences/config.mddoc392 bytes
Read SKILL.md
# Defect Intake and Triage
Turns "it's broken" into something an engineer can act on, or says exactly what is still missing.
🔴 **This does not reproduce anything.** Reproduction needs a terminal, a staging environment and
arbitrary browser control, none of which Cowork has. The portable half of a bug-reproduction
pattern is the **intake and handoff**, and that is all this does. The card says so to the reader.
## Inputs
- The report itself, from **Email** or Teams
- **Enterprise Search** for prior reports of the same thing, and for the owning team
- `references/config.md` for the required intake fields and the severity vocabulary
## ProcedureView the complete source on GitHubincident-digest
When your agent uses it
Turns the mail and Teams traffic around an incident into a dated timeline with the open questions and who owns each. Use when the user asks for an incident timeline, what happened during an outage, to prepare a post-incident review, or to catch up on an incident in progress.
What it loads into context
Frontmatter
64 tokensAlways available to the agent
SKILL.md
666 tokensWhen the skill is activated
Reference documents
60 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,033 bytesSKILL.mdcore3,033 bytesreferences/config.mddoc252 bytes
Read SKILL.md
# Incident Digest
Rebuilds what happened and when, from the traffic, so the review starts from a timeline instead of
from memory.
## Inputs
- **Email** and Teams traffic for the incident window
- **Enterprise Search** for any status page, runbook or change record referenced in the traffic
- `references/config.md` for the severity vocabulary and the channels that matter
## Procedure
1. **Establish the window.** First signal to last all-clear, from the traffic itself. If the
incident is open, say so and mark the timeline as in progress.
2. **Build the timeline** in UTC and in the user's local time, one row per event that changed whatView the complete source on GitHubinternal-expert-finder
When your agent uses it
Finds who inside the organization has already done a given kind of work, with the evidence for each name, and drafts the introduction. Strictly internal, never external sourcing. Use when the user asks who has done this before, who knows about a topic, who to ask internally, or who worked on a similar project.
What it loads into context
Frontmatter
74 tokensAlways available to the agent
SKILL.md
723 tokensWhen the skill is activated
Reference documents
96 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,309 bytesreferences/config.mddoc403 bytes
Read SKILL.md
# Internal Expert Finder
Answers "who here has already solved this", with the evidence, before anyone reinvents it.
🔴 **Internal only.** This skill never sources candidates externally, never reads professional
networks, and never touches recruitment. That boundary is the whole design: it is the portable
half of an external-sourcing pattern that does not belong inside a tenant.
## Inputs
- **Enterprise Search** across documents, sites and shared files
- **Meetings** for who presented or led on a topic
- `references/config.md` for the evidence bar and groups to exclude
## ProcedureView the complete source on GitHubinterview-loop-coordinator
When your agent uses it
Prepares an interview loop: who covers which competency, what each interviewer needs beforehand, and a consolidated feedback pack afterwards scored against a written bar. Use when the user asks to plan an interview loop, prepare a panel, build a debrief pack, or says they are interviewing for a role.
What it loads into context
Frontmatter
68 tokensAlways available to the agent
SKILL.md
636 tokensWhen the skill is activated
Reference documents
63 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,079 bytesreferences/config.mddoc249 bytes
Read SKILL.md
# Interview Loop Coordinator
Makes a panel cover the whole bar once, instead of four people asking the same question.
## Inputs
- The role's written bar, supplied by the user or found via **Enterprise Search**
- Panel availability, through **Calendar Management**
- `references/config.md` for the competency list and the scoring scale
## Procedure
1. **Load the bar.** Without a written bar, stop and say so. A loop scored against an unwritten
bar is not a loop, it is a series of opinions, and the pack would launder that into a decision.
2. **Map competencies to interviewers**, so every competency is covered at least once and no
interviewer carries more than the config maximum. State any competency with no coverage.View the complete source on GitHubonboarding-buddy
When your agent uses it
Builds a dated first-fortnight plan for a new joiner from the team's own documents, meetings and systems, naming who they meet and what they read on which day. Use when the user asks to plan an onboarding, prepare for a new starter, build a first-week plan, or says someone is joining the team.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
611 tokensWhen the skill is activated
Reference documents
90 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,709 bytesreferences/config.mddoc344 bytes
Read SKILL.md
# Onboarding Buddy
Turns "they start Monday" into a dated plan built from what the team actually has.
## Inputs
- **Enterprise Search** for the team's existing material: handbooks, architecture notes, runbooks
- **Calendar Management** for who is available in the first fortnight
- `references/config.md` for the role templates and the standing first-week items
## Procedure
1. **Establish** the start date, the role and the team. Missing any of these, ask once and stop.
2. **Find the real material.** Search for what this team has written: onboarding notes, decision
records, runbooks, recent all-hands. Record what exists and, importantly, what does not.
3. **Find the people** the role should meet, evidenced by who owns the systems and documents theView the complete source on GitHubdocument-transmittal-tracker
When your agent uses it
Tracks documents issued to clients, contractors and authorities: what was sent, to whom, on what date, what response was due and what is now overdue for return. Use when the user asks what has been transmitted, what is outstanding for comment or approval, to build a transmittal register, or which documents are overdue for return.
What it loads into context
Frontmatter
78 tokensAlways available to the agent
SKILL.md
672 tokensWhen the skill is activated
Reference documents
82 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,925 bytesSKILL.mdcore2,925 bytesreferences/config.mddoc280 bytes
Read SKILL.md
# Document Transmittal Tracker
Answers "what did we send, and who still owes us a response", from the mail itself.
## Inputs
- **Email** for transmittal messages and their responses
- **Enterprise Search** for the transmittal register, if one exists as a file
- `references/config.md` for document-number patterns, response windows and the party list
## Procedure
1. **Find transmittals** by the document-number pattern in config, plus the usual vocabulary:
"for approval", "for comment", "for construction", "IFC", "IFR", "transmittal".
2. **One row per document revision**, not per message. Revision B of a drawing is a different row
from revision A, and conflating them hides the resubmission.View the complete source on GitHublessons-learned-harvester
When your agent uses it
Pulls recurring problems out of close-out reports, retrospectives and project correspondence into a themed register showing which lesson keeps repeating across projects. Use when the user asks for lessons learned, what keeps going wrong, to prepare a close-out, or whether a problem has happened before.
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
667 tokensWhen the skill is activated
Reference documents
96 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,271 bytesSKILL.mdcore3,271 bytesSKILL.mdcore3,271 bytesSKILL.mdcore3,271 bytesreferences/config.mddoc437 bytes
Read SKILL.md
# Lessons Learned Harvester
Finds the lesson that has now been learned four times, which is the only kind worth acting on.
## Inputs
- **Enterprise Search** across close-out reports, retrospectives and project folders
- **Email** for the correspondence where problems were actually discussed
- `references/config.md` for the project list, the theme taxonomy and the lookback
## Procedure
1. **Gather** close-out and retrospective material across the configured projects and lookback.
2. **Extract individual lessons**, one per row, each with: the project, the date, what happened,
what was recommended, and the source link.
3. **Theme them** against the config taxonomy. A lesson that fits no theme goes in `Unthemed`View the complete source on GitHubrfi-query-tracker
When your agent uses it
Tracks open requests for information and technical queries: who asked, who owes the answer, how long it has been open and what it is holding up. Use when the user asks what RFIs are open, which queries are unanswered, what is blocked waiting on an answer, or to prepare the RFI log before a progress meeting.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
651 tokensWhen the skill is activated
Reference documents
61 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,812 bytesSKILL.mdcore2,812 bytesreferences/config.mddoc164 bytes
Read SKILL.md
# RFI and Query Tracker
Shows which open questions are actually blocking work, rather than which are merely old.
## Inputs
- **Email** and Teams traffic for queries and their answers
- **Enterprise Search** for the RFI log, if one exists
- `references/config.md` for the RFI numbering pattern and response windows by discipline
## Procedure
1. **Find queries** by the numbering pattern and the vocabulary: "RFI", "query", "clarification
required", "please confirm", "awaiting your response".
2. **For each, extract**: reference, raised by, raised on, directed to, the question in one line,
the response window from config, whether answered, and the source link.View the complete source on GitHubaccount-expert
When your agent uses it
Owns the context for one named customer, rebuilding what is happening with them from mail, meetings and files, and producing a pre-meeting brief or a state-of-the-account summary on request. Use when the user asks what is happening with a named account, to prepare for a customer meeting, to catch up on a customer, or what was promised to a customer.
What it loads into context
Frontmatter
82 tokensAlways available to the agent
SKILL.md
764 tokensWhen the skill is activated
Reference documents
138 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,508 bytesSKILL.mdcore3,508 bytesreferences/config.mddoc549 bytes
Read SKILL.md
# Account Expert
One skill, one customer, context rebuilt from the tenant rather than from a CRM.
**Why this exists next to the first-party Sales plugin.** Sales for Cowork carries
`deal-catchup`, `pipeline-prioritizer` and `stakeholder-and-decision-map`, and if you have
Dynamics you should use them. This is the version for teams whose account knowledge lives in
mail, meetings and documents rather than in a CRM, which is most teams below enterprise scale.
## Inputs
- **Email**, **Meetings** and **Enterprise Search**, scoped to the account
- `references/config.md` for the account name, its domains, the people on both sides, and
what the user counts as a commitment
View the complete source on GitHubone-to-one-prep
When your agent uses it
Prepares a brief for a one-to-one with a named person: their open items, what they raised recently, what you owe them, and what has gone unanswered between you. Use when the user asks to prepare for a 1:1, what to discuss with someone, what they owe a colleague, or says they have a one-to-one coming up.
What it loads into context
Frontmatter
83 tokensAlways available to the agent
SKILL.md
668 tokensWhen the skill is activated
Reference documents
73 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore2,838 bytesreferences/config.mddoc238 bytes
Read SKILL.md
# One-to-One Prep
Walks into the 1:1 knowing what you owe them, which is the half most prep skips.
## Inputs
- **Email**, **Meetings** and Teams traffic between the user and that person
- `references/config.md` for the window and what counts as a commitment
- The prior brief, if one exists, so items do not reappear as new
## Procedure
1. **Scope to the two people.** Threads where both are present. A group thread counts only if the
person contributed to it.
2. **Build four lists, in this order:**
- **What you owe them.** Commitments the user made, quoted and linked. **This section isView the complete source on GitHubproject-decomposer
When your agent uses it
Breaks a project, initiative or goal into owned tasks, each carrying its own verification criteria and a named owner, and returns one Adaptive Card per task. It plans and does not execute. Use when the user asks to break down a project, decompose an initiative, turn a goal into tasks, work out who does what, or says a project is too big to start.
What it loads into context
Frontmatter
84 tokensAlways available to the agent
SKILL.md
970 tokensWhen the skill is activated
Reference documents
123 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Inputs
- Procedure
- The verification bar
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check before returning
Files
SKILL.mdcore4,287 bytesreferences/config.mddoc528 bytes
Read SKILL.md
# Project Decomposer
Turns a project into tasks somebody can actually finish, each with a stated way to tell it is done.
**This skill does no work.** It decomposes and stops. If a task it produces looks like something
Cowork could do, that is a separate request the user makes deliberately.
## Inputs
- A project description from the user, or a named document found through **Enterprise Search**
- Existing context: prior decisions, related threads, the people already involved
- `references/config.md` for team names, the default task size and the house verification bar
## ProcedureView the complete source on GitHubteam-lead-mode
When your agent uses it
The orchestrator for a team lead's week. Runs the other team-lead skills in a stated order inside one task and assembles their outputs into a single review, degrading gracefully when a skill is not installed. Use when the user asks for their weekly team review, to run the team lead routine, says it is Monday planning, or wants everything in one place.
What it loads into context
Frontmatter
83 tokensAlways available to the agent
SKILL.md
882 tokensWhen the skill is activated
Reference documents
82 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- The skills it invokes, in order
- Procedure
- Output
- Definition of done
- When there is no data
- Boundaries
- Self-check
Files
SKILL.mdcore3,851 bytesreferences/config.mddoc318 bytes
Read SKILL.md
# Team Lead Mode
Runs the pack in order and assembles one review, rather than making you run four things.
🔴 **This is not multi-agent, and the distinction matters.** Grok Bot has a roster of Bots that
message each other and pass ownership. Cowork runs **one task that loads several skills**. This
skill calls others in sequence inside that single task. If you came here expecting agents
negotiating, that is the capability Cowork does not have, and pretending otherwise would waste
your afternoon.
## The skills it invokes, in order
1. `workstream-health` if installed, else read `project.md` files directly and say you did
2. `one-to-one-prep` for each direct report named in configView the complete source on GitHubbot-template
When your agent uses it
One sentence on what this produces, then the triggering phrases. Use when the user asks to <phrase>, says <phrase>, or wants <outcome>. This text is the routing logic Cowork matches a request against, so write it for the matcher and not for a reader.
What it loads into context
Frontmatter
63 tokensAlways available to the agent
SKILL.md
601 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
- Inputs
- Config the user edits
- Procedure
- Output
- Definition of done
- When there is no data, or stale data
- Boundaries
- Self-check before returning
Files
SKILL.mdcore2,627 bytesSKILL.mdcore2,627 bytesSKILL.mdcore2,627 bytesSKILL.mdcore2,627 bytesSKILL.mdcore2,627 bytesSKILL.mdcore2,627 bytes
Read SKILL.md
# <Bot name>
<One line: the repeatable outcome this owns. Not a category.>
## Inputs
- What the user supplies, if anything
- Which built-in skills this reads through: Email, Enterprise Search, Meetings, Deep Research,
Calendar Management, Excel, Word
- Which config file it reads, if any
## Config the user edits
Read `references/config.md` at the start of every run. If it is missing, say so once and continueView the complete source on GitHubSkills included
- brand-answer-monitor
- competition-monitor
- internal-newsletter-builder
- leadership-update-drafter
- calendar-defender
- budget-variance-explainer
- cloud-cost-digest
- expense-reconciliation
- invoice-vendor-followup
- subscription-hunter
- change-advisory-prep
- defect-intake-triage
- incident-digest
- internal-expert-finder
- interview-loop-coordinator
- onboarding-buddy
- document-transmittal-tracker
- lessons-learned-harvester
- rfi-query-tracker
- account-expert
- one-to-one-prep
- project-decomposer
- team-lead-mode
- bot-template
Repository facts
- License
- MIT
- Created
- Nov 4, 2026
- Last pushed
- Nov 5, 2026
- Forks
- 0
- Open issues
- 0
- Project activity
- Active
Before you install
Instructions onlyAutomated signals, not a guarantee
Checked Nov 6, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 25 notes
packs/comms/competition-monitor/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/comms/competition-monitor/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/comms/competition-monitor/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/comms/internal-newsletter-builder/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/budget-variance-explainer/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/cloud-cost-digest/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/expense-reconciliation/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/invoice-vendor-followup/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/invoice-vendor-followup/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/subscription-hunter/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/subscription-hunter/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/subscription-hunter/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/finance-finops/subscription-hunter/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/it-ops/incident-digest/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/projects/document-transmittal-tracker/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/projects/lessons-learned-harvester/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/projects/lessons-learned-harvester/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/projects/lessons-learned-harvester/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/projects/rfi-query-tracker/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedpacks/sales-bd/account-expert/skill/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- No dangerous shell commands
- No network access
- No hidden or obfuscated text
- No instruction overrides
- No executable scripts
- No access to secrets
- No requests to vote in Hot
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.
No combined signals at this commit.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md packs/comms/brand-answer-monitor/skill/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md packs/comms/brand-answer-monitor/skill/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md packs/comms/brand-answer-monitor/skill/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md packs/comms/brand-answer-monitor/skill/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md packs/comms/brand-answer-monitor/skill/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md packs/comms/brand-answer-monitor/skill/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.