Individual skill

commercial-policy

Use when writing or revising discount rules: discount matrix, approver thresholds, exception flows and the deal framework sales works under. Builds the matrix with discount_matrix_builder.py, routes exceptions with exception_router.py and checks the policy with policy_linter.py.

commercial/skills/commercial-policy/SKILL.md

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Repository stars (not skill ratings): 29,481
Repository last updated: Nov 5, 2026
License: MIT

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agentic-ai Repository topic
anthropic-claude Repository topic
claude-ai Repository topic
claude-code Repository topic
claude-skills Repository topic
claude-code-skills Repository topic
ai-coding-agent Repository topic
claude-code-plugins Repository topic
developer-tools Repository topic
openai-codex Repository topic
commercial Declared skill tag
discount-policy Declared skill tag
discount-matrix Declared skill tag
exception-flow Declared skill tag
governance Declared skill tag
deal-framework Declared skill tag
commercial-discipline Declared skill tag
sales Derived category
writing Derived category

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SKILL.mdcore · 13,921 bytes
SKILL.mdcore · 13,921 bytes
assets/policy_design_template.mddoc · 6,751 bytes
references/discount_governance_canon.mddoc · 8,246 bytes
references/policy_anti_patterns.mddoc · 10,766 bytes
references/policy_design_canon.mddoc · 7,607 bytes
scripts/discount_matrix_builder.pyruns · 14,176 bytes
scripts/exception_router.pyruns · 10,400 bytes
scripts/policy_linter.pyruns · 17,478 bytes

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# commercial-policy

## Purpose

Design the **rules of engagement** that govern discounting off list price — the artifact that Deal Desk and AEs operate under. Three deterministic tools:

1. `discount_matrix_builder.py` — builds a 4-dimensional matrix (ARR band × term length × payment terms × strategic value tier), each cell carrying an approved discount band backed by current win-rate + NRR data, plus an approver tier (AE / Manager / Director / VP / CFO).
2. `exception_router.py` — when an asks-for-discount lands outside the matrix, routes it through the named approver chain, attaches required compensating commitments (multi-year prepay + named expansion path + reference commitment + MSA tightening), produces machine-readable audit-trail metadata, and flags precedent risk if 3+ similar exceptions have landed in the trailing quarter.
3. `policy_linter.py` — lints the matrix for governance defects: approver inversion, band inversion, margin-floor violation, coverage gaps, cliff edges, undefined strategic tiers, inconsistent margin floors, thin data backing.

The output is the **policy itself** (matrix + exception flow + lint report), not a per-deal application of it.

## When to use