Review Skill logo

Review Skill

Organization
existential-birds
review-skill

Reviews PRs that add or modify Agent Skills, checking structural validity, design quality, and marketplace consistency. Use when reviewing skill file changes, auditing SKILL.md quality, or running automated skill PR reviews.

Overview

Publisherexistential-birds
Repositorybeagle
Skill namereview-skill
Stars
82
Forks
8
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by existential-birds on GitHub. Read the source before you install it.

Installation

Install the Review Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/existential-birds/beagle.git /tmp/beagle
mkdir -p .claude/skills
cp -r /tmp/beagle/plugins/beagle-core/skills/review-skill .claude/skills/review-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Review Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Review Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Review Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Skill Review

Review Agent Skill PRs for structural validity, design quality, and marketplace consistency.

Arguments

  • $ARGUMENTS: Output file path for review results (required, passed by the calling harness or the user)
  • --base <branch>: Base branch for diff comparison (default: main)

Workflow

Step 1: Parse Arguments

Extract the output path from $ARGUMENTS. If no path is provided, default to .review-output.md. Extract --base if provided, otherwise default to main.

Step 2: Identify Changed Skills

bash
git diff --name-only $(git merge-base HEAD <base>)..<HEAD> | grep -E '(SKILL\.md|skills/[^/]+/)'

Group changed files by skill directory. Each unique skill directory is a review target. If no skill files changed, write "No skill files changed" to the output path and stop.

Step 3: Read Each Changed Skill End-to-End

For each changed skill:

  1. Read the full SKILL.md (not just diff lines)
  2. Read all files in the skill directory (references, scripts)
  3. Note the parent plugin directory and locate its plugin.json

Step 4: Run Structural Checks (HIGH Confidence)

Apply every check in references/structural-checks.md. These are binary pass/fail — violations are clear-cut.

Structural violations are HIGH confidence because they can be verified mechanically.

Step 5: Run Design Checks (MEDIUM Confidence)

Apply every check in references/design-checks.md. These require judgment — flag only when the issue is clear, not when the approach is merely different from what you'd choose.

Design issues are MEDIUM confidence because they involve subjective assessment.

Step 6: Run Marketplace Checks (HIGH Confidence)

Apply every check in references/marketplace-checks.md. These verify the skill integrates correctly with the marketplace it belongs to.

Marketplace violations are HIGH confidence because they can be verified by reading manifest files.

Step 7: Load and Apply Verification Protocol

Load the review-verification-protocol skill. Before reporting any finding, verify:

  1. You read the actual skill content, not just the diff context
  2. The issue is real, not a style preference
  3. The issue applies to skill files specifically (not general code review concerns)
  4. You can point to the specific line that proves the issue

Remove any finding you cannot verify.

Step 8: Write Output

Write all findings to the output path specified in Step 1, using the exact format below.

Output Format

markdown
## Review Summary

[1-2 sentence overview of findings across all reviewed skills]

## Issues

### Critical (Blocking)

1. [FILE:LINE] ISSUE_TITLE
   - Issue: Description of what's wrong
   - Why: Why this matters for skill quality or marketplace health
   - Fix: Specific recommended fix
   - Confidence: HIGH

### Major (Should Fix)

N. [FILE:LINE] ISSUE_TITLE
   - Issue: ...
   - Why: ...
   - Fix: ...
   - Confidence: HIGH|MEDIUM

### Minor (Nice to Have)

N. [FILE:LINE] ISSUE_TITLE
   - Issue: ...
   - Why: ...
   - Fix: ...
   - Confidence: HIGH|MEDIUM

### Informational (For Awareness)

N. [FILE:LINE] SUGGESTION_TITLE
   - Suggestion: ...
   - Rationale: ...
   - Confidence: MEDIUM

## Verdict

Ready: Yes | No | With fixes 1-N
Rationale: [1-2 sentences — only Critical and Major items block approval]

Every issue gets a sequential number. Every issue includes Confidence: HIGH|MEDIUM. The Verdict ignores Minor and Informational items.

Severity Calibration

Critical (Block Merge)

  • Invalid or missing YAML frontmatter (skill won't load)
  • Missing required name or description field
  • SKILL.md exceeds 500 lines (performance degradation)
  • Name collision with existing skill in the marketplace

Major (Should Fix)

  • name violates format rules (not kebab-case, too long, reserved word)
  • description missing "what" or "when" component, wrong person, or exceeds 1024 chars
  • Nested reference chains (references that reference other references)
  • Description too vague to trigger accurately
  • Structured output with no format template or example
  • Windows-style paths in file references

Minor (Nice to Have)

  • Time-sensitive content (hardcoded dates, "recently", "new")
  • Inconsistent terminology across skill files
  • Progressive disclosure not used when SKILL.md is dense
  • Workflows missing validation steps
  • Missing cross-reference (SKILL.md links to file that doesn't exist)

Informational (For Awareness)

  • Trigger keyword overlap with existing marketplace skills
  • Suggestions for additional reference files
  • Opportunities to improve description specificity
  • Script lacks --help or uses interactive prompts

Re-Review Rules

On subsequent review passes after fixes are applied:

  1. ONLY verify that previously flagged issues were addressed correctly
  2. Do NOT introduce new findings unrelated to previous issues
  3. Accept Minor items that weren't fixed — do not re-flag
  4. The goal of re-review is verification, not discovery

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Review Skill AI skill do?

Reviews PRs that add or modify Agent Skills, checking structural validity, design quality, and marketplace consistency. Use when reviewing skill file changes, auditing SKILL.md quality, or running automated skill PR reviews.

Why use Review Skill on TypingMind?

Because you install it once and use it with any model. Review Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Review Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/existential-birds/beagle/tree/main/plugins/beagle-core/skills/review-skill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Review Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Review Skill?

As many as you like. As long as a model supports skills, you can use Review Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Review Skill AI skill free?

Yes. It is published on GitHub by existential-birds under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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