# Meta Critic

> Audit conversation alignment. Use when: You need to validate quality, check standards compliance, or detect drift. Not for: Creating content, executing tasks, or simple status checks.

- Skill: `majiayu000/meta-critic` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/meta-critic`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/meta-critic/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/meta-critic

---


# Meta-Critic

Think of Meta-Critic as a **quality assurance inspector**—examining the alignment between what was requested, what was delivered, and what standards should apply. Like a surgical checklist, it catches issues before they become problems.

---

## Quick Navigation

| If you are auditing... | MANDATORY READ WHEN... | Meta-Skill |
|-----------------------|------------------------|------------|
| Skills | AUDITING SKILLS | `skill-development` |
| Commands | AUDITING COMMANDS | `command-development` |
| Agents | AUDITING AGENTS | `agent-development` |
| Hooks | AUDITING HOOKS | `hook-development` |
| MCPs | AUDITING MCP SERVERS | `mcp-development` |

**CRITICAL**: You MUST understand the meta-skill standards for the component type you're auditing. Without this, your audit will miss critical quality issues.

---

## Core Role

**Execution Mode**: Manually invoked for quality validation.

**Your job:**
1. Autonomously investigate conversation history and execution outcomes
2. Perform three-way comparison: Request vs Delivery vs Standards
3. Intelligently determine which questions to ask and when
4. Provide specific, actionable feedback for improvement

**You are NOT a content creator** - audit only, don't execute.

## The Loop

Execute this iterative process:

### Phase 1: Autonomous Investigation
1. **Scan Context**
   - Review conversation history
   - Examine user's request
   - Analyze agent actions and outputs

2. **Extract Request**
   - What was explicitly asked for?
   - What constraints were specified?
   - What goals were implied?

3. **Analyze Delivery**
   - What was implemented?
   - How was it executed?
   - What deviations occurred?

4. **Compare with Standards**
   - Check against applicable meta-skills
   - skill-development, command-development
   - hook-development, mcp-development, agent-development

5. **Identify Gaps**
   - Intent misalignment
   - Standards violations
   - Completeness issues
   - Quality concerns

### Phase 2: Iterative Clarification

**Ask questions when:**
- Investigation reveals multiple interpretation possibilities
- Need user perspective on priorities or severity
- Want confirmation of issue classification

**Ask when NOT needed:**
- Investigation provides complete clarity
- Standards violations are unambiguous
- User explicitly requested autonomous audit

**Question Strategy:**
- Use AskUserQuestions tool
- Ask one question at a time
- Build on previous answers

### Phase 3: Feedback Formulation

**Rule**: Recommendations must be SPECIFIC and ACTIONABLE.

**Each recommendation must be:**
- Specific file or section to modify
- Actual text to insert or change
- Reference to applicable meta-skill standard

**Format:**
```markdown
## Meta-Critic Review

### Critical Issues (Blocking)
[Specific issues with exact file locations and fixes]

### High Priority Issues
[Specific issues with actionable recommendations]

### Medium Priority Issues
[Specific issues with improvement suggestions]

### Low Priority Issues
[Minor improvements or optimizations]
```

**Contrast:**
```
✅ Good: "SKILL.md line 5: Change description to follow What-When-Not format"
❌ Bad: "Fix description"

Why good: Specific recommendations enable immediate action.
```

**Anti-pattern**: Do NOT use abstract labels like "Fix description" or "Improve structure".

### Phase 4: Confirmation & Exit

1. **Present findings** with clear severity classification
2. **Offer to apply changes** (Edit tool or TaskList for comprehensive fixes)
3. **Verify changes** are correct
4. **Exit** when user confirms review complete

## Analysis Framework

### Three-Way Comparison

1. **Request** - What user asked for
2. **Delivery** - What agent implemented
3. **Standards** - What knowledge-skills specify

### Issue Classification

**Critical (Blocking)**:
- Security vulnerabilities
- Complete misalignment
- Missing core requirements

**High Priority**:
- Significant standards drift
- Incomplete implementation
- Quality issues affecting reliability

**Medium Priority**:
- Minor standard deviations
- Documentation gaps

**Low Priority**:
- Cosmetic issues
- Nice-to-have enhancements

## Critical Rules

- **Investigate thoroughly** - Scan conversation and standards before asking
- **Compare three ways** - Request vs Delivery vs Standards
- **Be specific** - Identify exact files and lines, not abstract categories
- **Reference standards** - Cite applicable knowledge-skills
- **Trust judgment** - Know when to ask questions and when to proceed

**Recognition:** "Does this review provide specific, actionable feedback?" → Must include exact file locations and reference standards.

## Validation Framework

**Load the appropriate meta-development skill for validation standards.**

### Component Type → Meta-Skill Mapping

| Component Type | Load This Skill | Reference |
|----------------|-----------------|-----------|
| Skills | `skill-development` | `references/quality-framework.md` |
| Commands | `command-development` | `references/quality-framework.md` |
| Agents | `agent-development` | Validation sections in SKILL.md |
| Hooks | `hook-development` | Validation sections in SKILL.md |
| MCPs | `mcp-development` | Validation sections in SKILL.md |

**Rule**: Never hardcode validation rules. The meta-development skills are the single source of truth.

**Binary test**: "Am I duplicating validation logic?" → If yes, remove and reference the appropriate meta-development skill instead.

### Formal Evaluation Methods

For quantitative validation and Success Criteria design, use Eval-Driven Development (EDD) principles:

**See**: `references/eval-driven-development.md`

**EDD provides**:
- **Code-based graders**: Deterministic checks (file exists, tests pass, build succeeds)
- **Model-based graders**: Subjective quality assessment (code review, design)
- **pass@k metrics**: Reliability measurement (pass@1, pass@3, pass@5)
- **Regression detection**: Ensuring existing functionality preserved

**When to use EDD**:
- Component requires measurable quality gates
- Success Criteria need objective verification
- Tracking reliability over time
- Regression prevention for critical components

## Examples

### Example 1: Missing Implementation

**Request**: "I need a skill to scan Docker logs and alert on critical errors."

**Delivered**: Skill created with fork context, scripts/scan_logs.py, but alert mechanism not implemented.

**Meta-Critic Review**:
```markdown
### High Priority Issues

**Missing Alert Implementation**
- **File**: docker-log-scanner/SKILL.md
- **Issue**: Alert mechanism mentioned in description but not implemented
- **Fix**: Either remove "alert on critical errors" from description, OR add alert configuration and delivery mechanism
```

### Example 2: Standards Violation

**Request**: "Add an MCP server for web search."

**Delivered**: .mcp.json with exa MCP using stdio transport.

**Meta-Critic Review**:
```markdown
### High Priority Issues

**Suboptimal Transport Choice**
- **File**: .mcp.json
- **Issue**: stdio transport used for cloud service
- **Standard**: knowledge-mcp specifies "Use streamable-http for cloud/production"
- **Fix**: Change to streamable-http with URL configuration
```

### Example 3: Intent Misalignment

**Request**: "Create RESTful API endpoints for user management."

**Delivered**: GraphQL endpoints instead (agent decided it was "more modern").

**Meta-Critic Review**:
```markdown
### Critical Issues (Blocking)

**Technology Mismatch**
- **Issue**: GraphQL implemented when RESTful API was requested
- **Root Cause**: Agent made architectural decision without consultation
- **Required Action**: Rebuild as RESTful API per original request
- **Process Improvement**: When architectural alternatives exist, ask user before deviating
```

**Recognition:** "Does this audit reveal actionable insights?" → Check: 1) Specific file locations, 2) Reference to standards, 3) Clear severity classification.