Learn-skills.dev ralph-skill-review-loop
Self-improving review loop for Ralph Wiggum skills. Reviews skills against best practices, implements improvements, and continues until two consecutive clean reviews. Use when validating or improving the ralph-prompt-* skill suite.
git clone https://github.com/NeverSight/learn-skills.dev
T=$(mktemp -d) && git clone --depth=1 https://github.com/NeverSight/learn-skills.dev "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/skills-md/adaptationio/skrillz/ralph-skill-review-loop" ~/.claude/skills/neversight-learn-skills-dev-ralph-skill-review-loop && rm -rf "$T"
data/skills-md/adaptationio/skrillz/ralph-skill-review-loop/SKILL.mdRalph Skill Review Loop
Overview
A meta-skill that uses the Ralph Wiggum technique to review and improve the Ralph Wiggum prompt generator skills themselves. Runs a continuous improvement loop until skills pass review twice consecutively with no recommendations.
Quick Start
Copy and run this prompt in a Ralph loop:
/ralph-wiggum:ralph-loop "[paste prompt below]" --completion-promise "RALPH_SKILLS_PERFECTED" --max-iterations 100
THE SELF-IMPROVING REVIEW LOOP PROMPT
# Task: Self-Improving Review of Ralph Wiggum Skills ## Objective Review and improve the Ralph Wiggum prompt generator skills until they pass two consecutive reviews with zero improvement recommendations. ## Target Skills 1. ralph-prompt-builder (Master orchestrator) 2. ralph-prompt-single-task (Single task generator) 3. ralph-prompt-multi-task (Multi-task generator) 4. ralph-prompt-project (Project generator) 5. ralph-prompt-research (Research generator) Location: .claude/skills/ralph-prompt-*/SKILL.md ## Reference Materials - RALPH-WIGGUM-TECHNIQUE-COMPREHENSIVE-RESEARCH.md (12,000+ words of best practices) - skill-builder-package/research/ (skill building best practices) - skill-builder-package/examples/ (production skill patterns) --- ## STATE MANAGEMENT ### Required State Files Create these files to track progress: **RALPH_REVIEW_STATE.json**: ```json { "current_iteration": 1, "consecutive_clean_reviews": 0, "skills_reviewed": [], "improvements_made": [], "last_review_timestamp": "", "status": "IN_PROGRESS" }
RALPH_REVIEW_LOG.md:
# Ralph Skills Review Log ## Iteration History [Append each iteration's findings here]
STEP 1: ORIENTATION (Every Iteration)
Read current state:
cat RALPH_REVIEW_STATE.json cat RALPH_REVIEW_LOG.md | tail -50 git log --oneline -5 ls -la .claude/skills/ralph-prompt-*/
Check: How many consecutive clean reviews do we have?
- If 2 or more: Output <promise>RALPH_SKILLS_PERFECTED</promise>
- If less than 2: Continue to Step 2
STEP 2: COMPREHENSIVE SKILL REVIEW
Review Framework
For EACH skill in ralph-prompt-*, evaluate against:
2.1 Ralph Technique Alignment (from research)
- Clear completion criteria defined
- Includes self-verification commands
- Has TDD/iteration approach
- Includes "If Stuck" guidance
- Uses <promise> completion tags correctly
- Recommends appropriate max-iterations
- Follows "deterministically bad" philosophy (failures are fixable)
2.2 Skill Structure Quality
- YAML frontmatter complete (name, description with triggers)
- Progressive disclosure (overview → details → examples)
- Quick Start section exists and is actionable
- Examples are realistic and complete
- Best practices section included
- Integration with Ralph loop documented
2.3 Content Completeness
- All sections properly filled (no placeholders)
- Examples match the skill type
- Verification commands are real and runnable
- Edge cases addressed
- Cross-references to related skills
2.4 Prompt Template Quality
- Templates follow research best practices
- Success criteria are measurable
- Phase structure is clear (for multi-phase)
- State tracking included
- Progress tracking pattern included
Review Process
For each skill:
- Read the SKILL.md file completely
- Compare against RALPH-WIGGUM-TECHNIQUE-COMPREHENSIVE-RESEARCH.md
- Check against all 16 criteria above
- Document findings in REVIEW_FINDINGS.md
Review Output Format
Create/update REVIEW_FINDINGS.md:
# Review Findings - Iteration [N] ## Summary - Skills reviewed: [count] - Total issues found: [count] - Critical issues: [count] - Improvements needed: [count] ## ralph-prompt-builder ### Passing - [x] Criterion that passes ### Issues Found - [ ] [CRITICAL/HIGH/MEDIUM/LOW] Issue description - Location: [section/line] - Current: [what exists] - Should be: [what it should be] - Fix: [specific fix] ## ralph-prompt-single-task [... same format] ## ralph-prompt-multi-task [... same format] ## ralph-prompt-project [... same format] ## ralph-prompt-research [... same format] ## Recommendations Summary ### Must Fix (Critical/High) 1. [Recommendation 1] 2. [Recommendation 2] ### Should Fix (Medium) 1. [Recommendation 3] ### Nice to Have (Low) 1. [Recommendation 4] ## Review Result - [ ] CLEAN (zero recommendations) - [ ] NEEDS_WORK (has recommendations)
STEP 3: IMPLEMENT IMPROVEMENTS
If REVIEW_FINDINGS.md shows NEEDS_WORK:
3.1 Prioritize Fixes
Work in this order:
- Critical issues (breaks functionality)
- High issues (significantly impacts quality)
- Medium issues (improves quality)
- Low issues (polish)
3.2 Implement Each Fix
For each recommendation:
- Read the target skill file
- Implement the specific fix
- Verify the fix addresses the issue
- Commit the change:
git add .claude/skills/ralph-prompt-[name]/SKILL.md git commit -m "Improve ralph-prompt-[name]: [brief description] - [Change 1] - [Change 2] Part of Ralph skills self-improvement loop iteration [N]"
3.3 Track Improvements
Update RALPH_REVIEW_STATE.json:
{ "improvements_made": [ { "iteration": N, "skill": "ralph-prompt-X", "issue": "description", "fix": "what was done" } ] }
STEP 4: POST-IMPROVEMENT VERIFICATION
After implementing fixes:
4.1 Verify Each Skill Still Works
For each modified skill:
- YAML frontmatter is valid
- All sections render correctly
- Examples are syntactically correct
- No broken references
4.2 Check for Regressions
- No content accidentally deleted
- Cross-references still valid
- Templates still complete
4.3 Run Syntax Check
# Verify YAML frontmatter for f in .claude/skills/ralph-prompt-*/SKILL.md; do head -20 "$f" | grep -E "^(name:|description:)" done
STEP 5: UPDATE STATE
Update RALPH_REVIEW_STATE.json:
If review was CLEAN (zero recommendations):
{ "consecutive_clean_reviews": [previous + 1], "last_review_result": "CLEAN", "last_review_timestamp": "[timestamp]" }
If review was NEEDS_WORK:
{ "consecutive_clean_reviews": 0, "last_review_result": "NEEDS_WORK", "improvements_this_iteration": [count], "last_review_timestamp": "[timestamp]" }
Update RALPH_REVIEW_LOG.md:
## Iteration [N] - [timestamp] ### Review Result [CLEAN/NEEDS_WORK] ### Issues Found - [Issue 1] - [Issue 2] ### Fixes Applied - [Fix 1] - [Fix 2] ### State After - Consecutive clean reviews: [N] - Total improvements to date: [N]
STEP 6: LOOP DECISION
Check Termination Condition
Read RALPH_REVIEW_STATE.json:
cat RALPH_REVIEW_STATE.json | jq '.consecutive_clean_reviews'
If consecutive_clean_reviews >= 2:
Skills have passed two consecutive reviews with zero recommendations.
Create RALPH_SKILLS_VALIDATION_COMPLETE.md:
# Ralph Skills Validation Complete ## Summary - Total iterations: [N] - Total improvements made: [count] - Final state: All skills validated ## Skills Validated 1. ralph-prompt-builder - PASSED 2. ralph-prompt-single-task - PASSED 3. ralph-prompt-multi-task - PASSED 4. ralph-prompt-project - PASSED 5. ralph-prompt-research - PASSED ## Validation Criteria Met All 16 review criteria passing for all 5 skills. ## Timestamp [ISO timestamp]
Output: <promise>RALPH_SKILLS_PERFECTED</promise>
If consecutive_clean_reviews < 2:
Continue to next iteration (loop back to STEP 1)
REVIEW CRITERIA REFERENCE (Quick Check)
Ralph Technique Alignment
- Clear completion criteria
- Self-verification commands
- TDD/iteration approach
- "If Stuck" guidance
- <promise> tags used correctly
- Appropriate max-iterations recommendations
- Deterministically bad philosophy
Skill Structure Quality
- Complete YAML frontmatter
- Progressive disclosure
- Actionable Quick Start
- Realistic examples
- Best practices section
- Ralph loop integration docs
Content Completeness
- No placeholders
- Matching examples
- Real verification commands
ESCAPE HATCH
If stuck after 50 iterations without reaching 2 consecutive clean reviews:
- Document the recurring issues in RALPH_REVIEW_BLOCKERS.md
- List which criteria keep failing
- Identify if criteria are too strict
- Output: <promise>RALPH_REVIEW_BLOCKED</promise>
PROGRESS TRACKING
Every 5 iterations, summarize:
PROGRESS SUMMARY - Iteration [N] ================================ Started: [timestamp] Current: [timestamp] Consecutive clean reviews: [N]/2 Skills Status: - ralph-prompt-builder: [X/16 criteria passing] - ralph-prompt-single-task: [X/16 criteria passing] - ralph-prompt-multi-task: [X/16 criteria passing] - ralph-prompt-project: [X/16 criteria passing] - ralph-prompt-research: [X/16 criteria passing] Improvements made: [total count] Remaining issues: [count]
COMPLETION CONDITIONS
Output <promise>RALPH_SKILLS_PERFECTED</promise> ONLY when:
- All 5 skills reviewed
- All 16 criteria checked per skill
- Zero recommendations in current review
- Zero recommendations in previous review
- consecutive_clean_reviews >= 2 in state file
- RALPH_SKILLS_VALIDATION_COMPLETE.md created
- All changes committed
SAFETY LIMITS
- Maximum iterations: 100
- Expected completion: 20-40 iterations
- Budget alert: If > 50 iterations, evaluate if criteria are too strict
--- ## Usage Instructions ### 1. Initialize State Files Before running, create the initial state: ```bash # Create state file cat > RALPH_REVIEW_STATE.json << 'EOF' { "current_iteration": 0, "consecutive_clean_reviews": 0, "skills_reviewed": [], "improvements_made": [], "last_review_timestamp": "", "status": "NOT_STARTED" } EOF # Create log file cat > RALPH_REVIEW_LOG.md << 'EOF' # Ralph Skills Review Log ## Overview Self-improving review loop for Ralph Wiggum prompt generator skills. ## Target: Two consecutive clean reviews --- ## Iteration History EOF
2. Run the Loop
/ralph-wiggum:ralph-loop "[THE PROMPT ABOVE]" \ --completion-promise "RALPH_SKILLS_PERFECTED" \ --max-iterations 100
3. Monitor Progress
# Check current state cat RALPH_REVIEW_STATE.json | jq '.' # See recent activity tail -30 RALPH_REVIEW_LOG.md # Check how many clean reviews cat RALPH_REVIEW_STATE.json | jq '.consecutive_clean_reviews'
4. After Completion
Review the outputs:
- Final stateRALPH_REVIEW_STATE.json
- Complete historyRALPH_REVIEW_LOG.md
- Last review detailsREVIEW_FINDINGS.md
- Success certificateRALPH_SKILLS_VALIDATION_COMPLETE.md- Git log - All improvements committed
Why This Works
- State Tracking: JSON state file persists across iterations
- Clear Criteria: 16 specific, measurable review criteria
- Self-Correction: Each iteration reads previous results and fixes issues
- Termination Condition: Two consecutive clean reviews ensures stability
- Evidence-Based: All findings documented, all fixes tracked
- Git Integration: Every improvement committed for auditability
Expected Behavior
Iteration 1-5: Discovery phase
- Identify initial issues across all skills
- Begin fixing critical issues
Iteration 6-15: Improvement phase
- Systematic fixes
- Quality improvements
- Cross-consistency
Iteration 16-25: Stabilization phase
- Fewer issues found
- Polish and edge cases
- Approaching clean reviews
Iteration 26-40: Validation phase
- First clean review achieved
- Verify no regressions
- Second clean review achieved
- Completion
Customization
Stricter Review
Add more criteria to the review framework.
Faster Completion
Reduce to "one clean review" by changing:
consecutive_clean_reviews >= 1
Focus on Specific Skills
Modify the target skills list in the prompt.