fix-fast

[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.

Understand Code First — Search codebase for 3+ similar implementations BEFORE writing any code. Read existing files, validate assumptions with grep evidence, map dependencies via graph trace. Never invent new patterns when existing ones work. MUST READ .claude/skills/shared/understand-code-first-protocol.md for full protocol and checklists.

Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs file:line proof. Confidence: >95% recommend freely, 80-94% with caveats, <80% DO NOT recommend — gather more evidence. Cross-service validation required for architectural changes. MUST READ .claude/skills/shared/evidence-based-reasoning-protocol.md for full protocol and checklists.

• docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected: ...] header before reading)

Estimation Framework — SP scale: 1(trivial) → 2(small) → 3(medium) → 5(large) → 8(very large, high risk) → 13(epic, SHOULD split) → 21(MUST split). MUST provide story_points and complexity estimate after investigation. MUST READ .claude/skills/shared/estimation-framework.md for full protocol and checklists.

Skill Variant: Variant of /fix — quick fixes with minimal investigation.

Quick Summary

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

Workflow:

1. Identify — Quick root cause analysis from error message
2. Fix — Apply targeted fix directly
3. 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

[MANDATORY] Read .claude/skills/shared/root-cause-debugging-protocol.md BEFORE proposing any fix. Responsibility attribution and data lifecycle tracing are required.

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

⚠️ Validate Before Fix (NON-NEGOTIABLE): After root cause analysis, MUST present findings + proposed fix to user via AskUserQuestion and get explicit approval BEFORE any code changes. No silent fixes.

Workflow

1. 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.
2. 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.
3. Activate debug-investigate skills and problem-solving skills to tackle the issues.
4. 🛑 Present root cause + proposed fix → AskUserQuestion → wait for user approval.
5. Start implementing the fix based the reports and solutions.
6. Use tester agent to test the fix and make sure it works, then report back to main agent.
7. If there are issues or failed tests, repeat from step 2.
8. 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.

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

Closing Reminders

• MUST break work into small todo tasks using TaskCreate BEFORE starting
• MUST search codebase for 3+ similar patterns before creating new code
• MUST cite file:line evidence for every claim (confidence >80% to act)
• MUST add a final review todo task to verify work quality
• MUST STOP after 3 failed fix attempts — report outcomes, ask user before #4 MANDATORY IMPORTANT MUST READ the following files before starting:
• MUST READ .claude/skills/shared/understand-code-first-protocol.md before starting
• MUST READ .claude/skills/shared/evidence-based-reasoning-protocol.md before starting
• MUST READ .claude/skills/shared/estimation-framework.md before starting