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 shinpr/claude-code-workflows --skill recipe-quality-profilegit clone --depth 1 https://github.com/shinpr/claude-code-workflowsWrote 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/shinpr/claude-code-workflows/recipe-quality-profile)<a href="https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-quality-profile"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-quality-profile.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00800 |
| Opus 5 | $0.00020 | $0.00400 |
| Sonnet 5 | $0.00008 | $0.00160 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
recipe-quality-profile 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Execute Skill: llm-friendly-context before proposing profile conditions or writing the profile. Execute Skill: coding-principles to distinguish repository-owned policy from general code-quality knowledge.
Purpose
Establish repository-specific implementation and code-review acceptance conditions with the user, then create or update docs/project-context/quality.yaml.
Requested policy change: $ARGUMENTS
Profile Contract
version: 1
review_dimensions:
- id: stable-kebab-case-id
applies_when: Observable condition that makes this repository rule relevant to a change.
pass: Observable accepted state to verify.
evidence:
- "repository/path: section, identifier, or contract"
Each dimension owns one repository-specific quality decision. applies_when limits its implementation and review surface, pass defines the accepted state, and evidence identifies why the repository owns the rule.
Authoring Flow
- Use the current working repository as the target and read its
docs/project-context/quality.yamlwhen present. For an existing profile, use the requested policy change as the update boundary; when none is supplied, ask for it and keep the profile unchanged. - Build candidates from acceptance conditions expressed or enforced by repository instructions, contributor documentation, CI, manifests and scripts, schemas and public contracts, tests, or representative implementation patterns. For an update, derive candidates only from the requested policy change and preserve unrelated dimensions.
- For each candidate, inspect supporting and contradicting evidence wherever it can change the candidate's applicability, accepted state, or repository ownership. Separate observed repository facts from policy choices that require user confirmation.
- Retain a candidate only when failing its
passcondition would change implementation acceptance and every repository fact it depends on has cited evidence. Give it the narrowest usefulapplies_when, one positive observablepasscondition, and consolidate candidates that would produce the same finding and correction. Omit a candidate when required repository evidence is unavailable and report the exact evidence needed. - Present proposed additions, changes, and removals, confirm that other dimensions remain unchanged, show the supporting and contradicting evidence, and state unresolved policy choices with their effect on implementation and review acceptance. Obtain explicit user confirmation of a proposal with no unresolved choices before writing.
- Write only the confirmed profile content. Read the result and verify version
1, unique IDs, all required fields, observable conditions, readable evidence references, and consistency with the confirmed proposal.
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.
- 7d ago First seen · 66 lines · 41 tokens per session scan A 3b19da99c9d7
recipe-quality-profile is a skill published in the GitHub repository shinpr/claude-code-workflows (679 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 800 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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