[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof. 1. Citefile:line, grep results, or framework docs for EVERY claim 2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend 3. Cross-service validation required for architectural changes 4. "I don't have enough evidence" is valid and expected output BLOCKED until:- []Evidence file path (file:line)- []Grep search performed- []3+ similar patterns found- []Confidence level stated Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output:"Insufficient evidence. Verified: [...]. Not verified: [...]."
External Memory: For complex or lengthy work (research, analysis, scan, review), write intermediate findings and final results to a report file in plans/reports/ — prevents context loss and serves as deliverable.Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, and recommendation requires file:line proof or traced evidence with confidence percentage (>80% to act, <80% must verify first).Quick Summary
Goal: Review current branch changes, summarize impact/quality, and check for documentation staleness.
Workflow:
- Review — Analyze recent commits: what was modified, added, removed
- Summarize — Provide detailed change summary with quality assessment
- Doc Check — Cross-reference changed files against docs/ for staleness
- Lesson Learned — Analyze AI mistakes/issues during the task and capture lessons
Key Rules:
- READ-ONLY: do not implement or fix anything, only flag
- Doc staleness check is REQUIRED (see mapping table below)
- Lesson-learned analysis is REQUIRED (see section below)
- Final review task MUST ATTENTION include doc-staleness check AND lesson-learned analysis
Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).
Review my current branch and the most recent commits. Provide a detailed summary of all changes, including what was modified, added, or removed. Analyze the overall impact and quality of the changes.
IMPORTANT: Do not start implementing.
Doc Staleness Check (REQUIRED)
After the change summary, run git diff --name-only (against base branch or recent commits) and cross-reference changed files against relevant documentation:
| Changed file pattern | Docs to check for staleness |
|---|---|
.claude/hooks/** | .claude/docs/hooks/README.md, hook count tables in .claude/docs/hooks/*.md |
.claude/skills/** | .claude/docs/skills/README.md, skill count/catalog tables |
.claude/workflows/** | CLAUDE.md workflow catalog table, .claude/docs/ workflow references |
src/Services/** | docs/business-features/ doc for the affected service |
src/{frontend-dir}/** | docs/project-reference/frontend-patterns-reference.md, relevant business-feature docs |
CLAUDE.md | .claude/docs/README.md (navigation hub must stay in sync) |
Output one of:
- A bulleted list of docs that may need updating, with a brief note on what is likely stale (e.g., "hook count changed from 31 to 32").
No doc updates needed— if no changed file pattern maps to a doc.
Do not edit docs during watzup. Only flag. The user decides whether to fix.
AI Mistake & Lesson Learned Analysis (REQUIRED)
After the doc staleness check, review the entire session for AI mistakes and lessons learned:
- Analyze mistakes — Did AI make any errors during this task? Examples:
- Wrong assumptions about code behavior - Incorrect pattern usage (violated project conventions) - Missing edge cases or validation - Hallucinated APIs, methods, or file paths - Over-engineering or unnecessary complexity - Missed existing code that should have been reused - Wrong architectural layer placement
- Identify lessons — For each mistake found, formulate a concise lesson:
- What went wrong (specific, with file:line if applicable) - Why it happened (root cause) - How to prevent it next time (actionable rule)
- Ask user to persist — If any lesson exists, ask the user: "Found [N] lesson(s) learned during this task. Should I use
/learnto remember them for future sessions?" Wait for user confirmation before invoking/learn.
Output one of:
- A numbered list of lessons with the
/learnprompt above No AI mistakes identified in this session— if genuinely none found
Be honest and self-critical. The purpose is continuous improvement, not self-congratulation.
Next Steps
MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use AskUserQuestion to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:
- "/workflow-end (Recommended)" — Complete and close the active workflow
- "/commit" — Commit changes if not using workflow
- "Skip, continue manually" — user decides
Closing Reminders
MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality. MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:
- IMPORTANT MUST ATTENTION cite
file:lineevidence for every claim (confidence >80% to act). NEVER speculate without proof. - IMPORTANT MUST ATTENTION READ
CLAUDE.mdbefore starting