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commercial-policy

Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under. Covers discount matrix design (ARR band x term length x payment terms x strategic value), commercial policy design, exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces). For Head of Commercial, Head of Deal Desk, VP Sales, or RevOps at the policy-design moment — NOT per-deal application (that is deal-desk) and NOT pricing model selection (that is pricing-strategist).

71

Quality

89%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable and well-structured: concrete commands, a gated 5-step workflow, real one-level-deep bundle files, and sharp boundary sections against sibling skills. Its main costs are redundancy — the forcing-question library and anti-patterns recap content that belongs in or already exists in reference files — and an implicit rather than explicit re-lint feedback loop.

Suggestions

Move the 8-question forcing-question library into a reference file (e.g., references/forcing_questions.md) and keep a one-line pointer with the walk order ('lock 1-4 before 5-8'), cutting ~40 lines from SKILL.md.

De-duplicate the Anti-patterns section against references/policy_anti_patterns.md — keep only names plus lint-rule mapping inline and let the reference carry the rationale and sources.

Make the lint feedback loop explicit in workflow step 4: 'fix BLOCKER findings, re-run policy_linter.py, and only publish when it reports zero BLOCKERs'.

DimensionReasoningScore

Conciseness

The body is dense and assumes competence (no padding explaining known concepts), but the ~40-line forcing-question library and the 8-item anti-patterns section overlap material already carried in references/policy_anti_patterns.md and could be trimmed or pointered. This is 'efficient; minor instances of over-explanation that could be trimmed' (4), not the fully lean top anchor.

4 / 5

Actionability

Fully executable guidance: copy-paste commands with real flags ('python3 scripts/discount_matrix_builder.py --input policy_intake.json --profile saas --output json > matrix.json'), a named intake template with the exact CRM fields to capture, and stated expected outputs ('The sample matrix lints to FAIL with 4 BLOCKERs + 6 MAJORs + 2 MINORs — by design'). Matches the copy-paste-ready top anchor.

5 / 5

Workflow Clarity

Clear 5-step sequence (audit → build matrix → design exception flow → lint → publish/quarterly review) with an explicit gate ('Resolve every BLOCKER before publishing the matrix to AEs') and a quarterly re-run cadence. Falls just short of the top anchor because the fix-and-re-lint retry loop is implied ('lint is the gate') rather than spelled out as a validate → fix → re-validate iteration.

4 / 5

Progressive Disclosure

Good structure verified against the actual bundle: three references with one-line descriptions, a scripts table, and an assets template — all cited paths exist and are one level deep and clearly signaled. Minor gap: the in-body anti-patterns section duplicates content that already has a dedicated reference file (references/policy_anti_patterns.md), so some content that belongs in references is inline.

4 / 5

Total

17

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it states a clear niche, enumerates concrete capabilities, gives explicit 'use when' triggers including role names, and actively disambiguates against sibling skills. The only weakness is trigger-term coverage that stops just short of full synonym variation.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — 'discount matrix design (ARR band x term length x payment terms x strategic value)', 'exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces)' — with comprehensive coverage and no gaps, matching the top anchor rather than the 'minor gaps' anchor at 4.

5 / 5

Completeness

Explicitly answers both what ('the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under') and when ('Use when designing or revising a company's commercial policy', 'at the policy-design moment') with concrete trigger phrases, matching the top anchor exactly.

5 / 5

Trigger Term Quality

Good natural keyword coverage ('commercial policy', 'discount matrix', 'approval thresholds', 'exception flows', 'discount governance') plus role-based triggers ('Head of Commercial, Head of Deal Desk, VP Sales, or RevOps'), but misses common variations a user might say such as 'discount approval policy' or 'deal desk policy', so it falls between the 'good coverage' (4) and 'comprehensive synonyms' (5) anchors.

4 / 5

Distinctiveness Conflict Risk

Clear niche with explicit boundary negation — 'NOT per-deal application (that is deal-desk) and NOT pricing model selection (that is pricing-strategist)' — making wrong-skill triggering minimal, which matches the top anchor.

5 / 5

Total

19

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

alirezarezvani/claude-skills

Path

commercial/skills/commercial-policy/SKILL.md

Reviewed

Table of Contents

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