[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 — quick fixes with minimal investigation.

Quick Summary

Goal: Rapidly fix small, well-understood issues with minimal investigation overhead.

Workflow:

• Identify — Quick root cause analysis from error message

• Fix — Apply targeted fix directly

• Verify — Run affected tests to confirm

Key Rules:

• Debug Mindset: every claim needs file:line evidence

• Use for simple, isolated bugs only — escalate to /fix-hard for complex issues

• Minimize investigation time; if root cause isn't clear within minutes, escalate

Analyze the skills catalog and activate the skills that are needed for the task during the process.

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.

Mission

Think hard to analyze and fix these issues: $ARGUMENTS

Workflow

• If the user provides a screenshots or videos, use ai-multimodal skill to describe as detailed as possible the issue, make sure developers can predict the root causes easily based on the description.

• Use debugger subagent to find the root cause of the issues and report back to main agent. 2.5. Write root cause analysis to .ai/workspace/analysis/{issue-name}.analysis.md . Re-read before implementing fix.

• Activate debug skills and problem-solving skills to tackle the issues.

• Start implementing the fix based the reports and solutions.

• Use tester agent to test the fix and make sure it works, then report back to main agent.

• If there are issues or failed tests, repeat from step 2.

• After finishing, respond back to user with a summary of the changes and explain everything briefly, guide user to get started and suggest the next steps.

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

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