EasyPlatform 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.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

AI Mistake Prevention — Failure modes to avoid on every task:

• Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.
• Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.
• Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.
• Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.
• When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.
• Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.
• Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.
• Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.
• Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.
• Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

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

.claude/hooks/**

.claude/docs/hooks/README.md

.claude/docs/hooks/*.md

.claude/skills/**

.claude/docs/skills/README.md

.claude/workflows/**

CLAUDE.md

.claude/docs/

src/{services-dir}/**

docs/business-features/

docs/project-config.json

src/{frontend-dir}/**

docs/project-reference/frontend-patterns-reference.md

CLAUDE.md

.claude/docs/README.md

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.

Step 1 — Surface all mistakes

List every error made during this session. For each, note:

• What happened (observable symptom — build fail, test fail, wrong output)
• Where it happened (file:line if applicable)

Common mistake categories:

• Assumed an API/type/enum value existed without reading the source
• Assumed infrastructure availability without checking requirements
• Conflated "code exists" with "code executes" — missed path tracing
• Used a pattern without verifying the new context has the same preconditions
• Reported "done" without verifying ALL affected outputs across all stacks
• Hallucinated method names, class names, or file paths

Step 2 — Extract root-cause lessons (NOT symptom fixes)

For each mistake, apply this 3-step extraction:

2a. Name the failure mode — NOT the symptom, the reasoning failure:

2b. Find the class — Where else could this SAME failure mode strike?

If the failure mode only applies in one specific file or case → go up one abstraction level until it generalizes. A good lesson applies to ≥3 different contexts.

2c. Write as a universal rule — Strip ALL project-specific names:

• No file paths, class names specific to this codebase, or tool names
• Must read as useful advice on a completely different codebase in a different language
• If multiple mistakes share the same failure mode → consolidate into ONE lesson
• Test: "Would this prevent the same class of mistake in a Java, Go, or Python project?" If yes → good. If no → rewrite.

Step 3 — Ask user to persist

"Found [N] root-cause lesson(s). Should I use

/learn

to save them for future sessions?"

Wait for user confirmation before invoking

/learn

Output one of:

• A numbered list: failure mode → universal lesson → proposed

  /learn

  text

• No AI mistakes identified in this session

  — if genuinely none found

Be honest and self-critical. Surface-level symptom fixes ("always check file X") that only apply to this codebase are NOT lessons — they are noise. The purpose is root-cause prevention that compounds across sessions.

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use

AskUserQuestion

• "/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

AskUserQuestion

• 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 <!-- SYNC:critical-thinking-mindset:reminder -->
• MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact. <!-- /SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->
• MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction. <!-- /SYNC:ai-mistake-prevention:reminder -->