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recipe-quality-profile

Proposes repository-specific quality policy for implementation and review and, after confirmation, creates or updates docs/project-context/quality.yaml

Install / Use

npx skills add shinpr/claude-code-workflows --skill recipe-quality-profile

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

82/100

Supported Platforms

Universal

Our assessment of recipe-quality-profile

recipe-quality-profile scores 82/100 on our quality scale, 662nd of 943 AI & Machine Learning skills we index.

Its SKILL.md is 4.3 KB long, split into 5 sections with 1 code example: a solid amount of guidance for an agent.

It has 687 GitHub stars, a meaningful sign that others use it.

Substance
26/30
Structure
15/20
Description
15/15
Adoption
12/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 2 days ago, so recipe-quality-profile is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-04. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

recipe-quality-profile compared with similar skills

All 4 of these similar skills score higher than recipe-quality-profile; compare them before choosing.

SkillScoreStarsUpdatedFormat
recipe-quality-profile (this skill)by shinpr826872d agoSKILL.md
claude-memby thedotmack10095.5ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10085.2k2d agoCLAUDE.md
headroomby headroomlabs-ai10074.4ktodayCLAUDE.md
CowAgentby zhayujie10047.2ktodayCLAUDE.md

Frequently asked questions

How do I install recipe-quality-profile?
Run npx skills add shinpr/claude-code-workflows --skill recipe-quality-profile. The install tabs above show the steps for each supported agent.
Which AI agents does recipe-quality-profile work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is recipe-quality-profile safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is recipe-quality-profile still maintained?
The repository was last updated 2 days ago, so recipe-quality-profile is actively maintained.

name: recipe-quality-profile description: Proposes repository-specific quality policy for implementation and review and, after confirmation, creates or updates docs/project-context/quality.yaml. Use when asked to create or update a repository quality profile. disable-model-invocation: true

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

  1. Use the current working repository as the target and read its docs/project-context/quality.yaml when 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.
  2. 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.
  3. 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.
  4. Retain a candidate only when failing its pass condition would change implementation acceptance and every repository fact it depends on has cited evidence. Give it the narrowest useful applies_when, one positive observable pass condition, 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.
  5. 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.
  6. 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.

When no repository-specific dimension remains and no profile exists, report that repository evidence supports no profile content and leave the repository unchanged.

Result

Before confirmation, report:

  • proposed additions, changes, and removals, plus the unchanged remainder;
  • supporting and contradicting evidence for each modification;
  • omitted candidates and the exact missing evidence;
  • policy choices requiring the user's decision and their effect on implementation and review acceptance.

After confirmation, report:

  • the profile path and whether it was created, updated, or left unchanged;
  • dimensions added, changed, or removed;
  • evidence used for each changed dimension;
  • an exact validation limitation when the result could not be verified.

Completion Check

  • [ ] Every retained dimension changes an implementation or review decision and cites repository or user-confirmed policy evidence
  • [ ] Conditions are positive, observable, and limited by applies_when
  • [ ] The profile contains repository-specific acceptance conditions only
  • [ ] Supporting and contradicting evidence were compared where they could change the proposal
  • [ ] The user confirmed the complete proposal before the repository write
  • [ ] Dimensions outside the update boundary remain unchanged
  • [ ] The written profile satisfies the Profile Contract

Related Skills

View on GitHub
GitHub Stars687
CategoryAI
Updated2d ago
Forks104

Languages

JavaScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions