[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 ask user whether to skip.

Prerequisites: MUST READ .claude/skills/shared/understand-code-first-protocol.md AND .claude/skills/shared/evidence-based-reasoning-protocol.md before executing.

• docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models)

Skill Variant: Variant of /fix — debug and fix GitHub issues with systematic investigation.

Quick Summary

Goal: Investigate and fix bugs reported as GitHub issues with full traceability.

Workflow:

• Fetch — Read GitHub issue details (title, description, reproduction steps)

• Reproduce — Trace the reported behavior in code

• Fix — Apply fix with root cause evidence

Key Rules:

• Debug Mindset: every claim needs file:line evidence

• Link fix back to the GitHub issue for traceability

• Verify fix addresses the specific reproduction steps from the issue

$ARGUMENTS

Debug Mindset (NON-NEGOTIABLE)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

• Do NOT assume the first hypothesis is correct — verify with actual code traces

• Every root cause claim must include file:line evidence

• If you cannot prove a root cause with a code trace, state "hypothesis, not confirmed"

• Question assumptions: "Is this really the cause?" → trace the actual execution path

• Challenge completeness: "Are there other contributing factors?" → check related code paths

• No "should fix it" without proof — verify the fix addresses the traced root cause

⚠️ MANDATORY: Confidence & Evidence Gate

MANDATORY IMPORTANT MUST declare Confidence: X% with evidence list + file:line proof for EVERY claim. 95%+ recommend freely | 80-94% with caveats | 60-79% list unknowns | <60% STOP — gather more evidence.

Activate debug skill and follow its workflow.

IMPORTANT: Always use external memory at .ai/workspace/analysis/issue-[number].analysis.md for structured analysis. Re-read ENTIRE analysis file before proposing any fix — this prevents knowledge loss.

DO NOT make any code changes without explicit user approval. Present analysis and proposed fix, then wait for approval before implementing.

See .claude/docs/AI-DEBUGGING-PROTOCOL.md for comprehensive guidelines.

⚠️ MANDATORY: Post-Fix Verification

After applying the fix, MUST run /prove-fix — build code proof traces per change with confidence scores. Never skip.

IMPORTANT Task Planning Notes (MUST FOLLOW)

• Always plan and break work into many small todo tasks

• Always add a final review todo task to verify work quality and identify fixes/enhancements