Skill Review

Language

Match user's language: Respond in the same language the user uses.

Overview

Review an agent skill through three layers: automated linting (hard rules), contextual finding evaluation (agent judges with context), and structured semantic review (deep analysis against best practices). Optionally fix issues and verify fixes through independent subagent validation.

Workflow

Progress:

• Step 1: Identify the skill
• Step 2: Review (linting + profile + findings + semantic)
• Step 3: Present findings
• Step 4: Fix gate
• Step 5: Verify & iterate

Step 1: Identify the Skill

Accept the skill location as a directory path containing SKILL.md. Auto-detect if the current working directory contains one.

Step 2: Review

Run both tools, then evaluate.

2a. Automated linting:

python3 {SKILL_DIR}/scripts/validate.py run --path <skill-path>

Output: checks (hard-rule verdicts → linter grade) + findings (soft detections needing judgment).

2b. Profile extraction:

bash {SKILL_DIR}/scripts/analyze.sh analyze <skill-path>

Note skill level (l0/l0plus/l1) and feature flags.

2c. Contextual findings review:

Judge each finding using its contexthint. See references/semanticdimensions.md § Finding Judgment Table for decision criteria. Promote real issues to warnings; dismiss the rest with a brief note.

2d. Semantic review:

Read the skill's SKILL.md fully, then score each dimension (0-3). Read references/semantic_dimensions.md for the full checklist per dimension:

Step 3: Present Findings

Format the report:

[Skill Review] <skill-name>

═══ Linter ═══
Grade: <letter> (<pass>/<total> passed, <warn> warnings, <fail> failures)

Failures:
  ✗ <check_id>: <message> → Fix: <fix>

Warnings:
  ⚠ <check_id>: <message>

Findings (agent-reviewed):
  ✓ <finding_id>: dismissed — <reason>
  ⚠ <finding_id>: promoted to warning — <reason>

═══ Semantic Review ═══
5.1 Description Quality:   <score>/3  <one-line assessment>
5.2 Workflow Design:        <score>/3  <one-line assessment>
5.3 Runtime Robustness:     <score>/3  <one-line assessment>
5.4 Script Quality:         <score>/3  <one-line assessment>
5.5 UX Practices:           <score>/3  <one-line assessment>
5.6 Setup Flow Integrity:   <score>/3  <one-line assessment>
                            ─────────
Semantic Score:             <total>/18

═══ Improvement Suggestions ═══
For each dimension scoring < 3, provide:
  1. What to change and why
  2. Which file to edit
  3. A concrete before/after example or specific instruction
  4. Priority: High (functionality/UX) / Medium (convention) / Low (polish)

If linter grade is A and semantic score ≥ 15: congratulate and suggest publishing with better-skill-publish.

Step 4: Fix Gate

Ask the user:

• Fix all — Apply all suggested changes, then auto-verify (Step 5)
• Pick and choose — Select specific items, then auto-verify (Step 5)
• None — End here, use the report as reference

After fixing, do NOT self-evaluate. Proceed directly to Step 5.

Step 5: Verify & Iterate

CRITICAL: Verification must be independent. The agent that fixed cannot judge its own work.

5a. Dispatch verification subagent:

Agent(subagent_type: "general-purpose", description: "Verify skill review", prompt: <template>)

Use the prompt template from references/semantic_dimensions.md § Verification Subagent Prompt Template. The verification subagent must:

1. Run validate.py and analyze.sh fresh (never trust cached results)
2. Read references/semantic_dimensions.md for scoring criteria
3. Score all 6 dimensions independently, citing file:line evidence
4. Return linter grade + per-dimension scores + specific FAIL items

5b. Process verification result:

• All pass → Report success, done
• Has failures → Fix ONLY the specific FAIL items from the verification report, then dispatch a NEW subagent to verify again
• Max 3 rounds — if issues persist after 3 fix-verify cycles, report remaining issues and let the user decide

Anti-patterns (never do these):

Linter Reference

Grading (hard-rule checks only):

• A — All pass, zero warnings
• B — All pass, some warnings
• C — 1–2 failures
• D — 3+ failures
• F — SKILL.md missing or no valid frontmatter

Check categories:

References

• references/semantic_dimensions.md — Full checklist for each review dimension + finding judgment table + verification prompt template
• references/validation_rules.md — Rationale for each linter check
• references/improvement_patterns.md — Knowledge base of improvement patterns with examples
• references/best_practices.md — Skill design conventions and quick reference