Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bestagentkits/agency-skills --skill commercial-policygit clone --depth 1 https://github.com/bestagentkits/agency-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bestagentkits/agency-skills/commercial-policy)<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/commercial-policy"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/commercial-policy/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bestagentkits/agency-skills/commercial-policy"><img src="https://agentmods.dev/badge/skills/bestagentkits/agency-skills/commercial-policy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00142 | $0.03313 |
| Opus 5 | $0.00071 | $0.01656 |
| Sonnet 5 | $0.00028 | $0.00663 |
| Haiku 4.5 | $0.00014 | $0.00331 |
Grade A, and why
commercial-policy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to commercial-policy — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
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).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.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
- A new Head of Commercial or Head of Deal Desk is writing the company's first formal commercial policy
- The existing matrix is older than 6 months and discount drift is showing in margin reviews
- Reps are citing "Maria approved 28% on Acme last quarter" as precedent and you need to break the precedent loop
- Q-over-Q exception count is rising and you suspect the matrix bands are mispriced
- CFO has tightened the margin floor and the matrix needs to be rebuilt against the new constraint
- A board / exec is asking "why do we discount this much?" and you need a data-backed defensible policy
Do NOT use this skill to:
- Approve a specific deal — that's
commercial/skills/deal-desk - Set the pricing model + list price — that's
commercial/skills/pricing-strategist - Author a proposal / SOW / MSA prose — that's
business-growth/contract-and-proposal-writer - Make the strategic "when do we hire a VP Sales" call — that's
c-level-advisor/cro-advisor
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 214 B
- assets/policy_design_template.md 6.6 KB
- references/discount_governance_canon.md 8.1 KB
- references/policy_anti_patterns.md 11 KB
- references/policy_design_canon.md 7.4 KB
- scripts/discount_matrix_builder.py 14 KB runs code
- scripts/exception_router.py 10 KB runs code
- scripts/policy_linter.py 17 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 151 lines · 142 tokens per session scan A 6e812240f2b9
commercial-policy is a skill published in the GitHub repository bestagentkits/agency-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 142 tokens to every session and 3,313 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to commercial-policy, differing in 7 lines, and is treated as a copy.
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