Agent Skills: watzup

[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. Cite file: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:

1. Review — Analyze recent commits: what was modified, added, removed
2. Summarize — Provide detailed change summary with quality assessment
3. Doc Check — Cross-reference changed files against docs/ for staleness
4. 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:

1. 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

2. 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)

3. Ask user to persist — If any lesson exists, ask the user:

   "Found [N] lesson(s) learned during this task. Should I use /learn to remember them for future sessions?"

   Wait for user confirmation before invoking /learn.

Output one of:

• A numbered list of lessons with the /learn prompt 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:line evidence for every claim (confidence >80% to act). NEVER speculate without proof. <!-- /SYNC:evidence-based-reasoning:reminder -->
• IMPORTANT MUST ATTENTION READ CLAUDE.md before starting