performance

[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)

Evidence Gate: MANDATORY IMPORTANT MUST — every claim, finding, and recommendation requires file:line proof or traced evidence with confidence percentage (>80% to act, <80% must verify first).

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.

Quick Summary

Goal: Analyze and optimize performance bottlenecks in database queries, API endpoints, or frontend rendering.

Workflow:

1. Profile — Identify bottlenecks using profiling data or metrics
2. Analyze — Trace hot paths and measure impact
3. Optimize — Apply targeted optimizations with before/after measurements

Key Rules:

• Analysis Mindset: measure before and after, never optimize blindly
• Evidence-based: every claim needs profiling data or benchmarks
• Focus on highest-impact bottlenecks first

$ARGUMENTS

Analysis 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 a bottleneck location — verify with actual code traces and profiling evidence
• Every performance claim must include file:line evidence
• If you cannot prove a bottleneck with a code trace, state "suspected, not confirmed"
• Question assumptions: "Is this really slow?" → trace the actual execution path and query plan
• Challenge completeness: "Are there other bottlenecks?" → check the full request pipeline
• No "should improve performance" without proof — measure before and after

[IMPORTANT] Database Performance Protocol (MANDATORY):

1. Paging Required — ALL list/collection queries MUST use pagination. NEVER load all records into memory. Verify: no unbounded GetAll(), ToList(), or Find() without Skip/Take or cursor-based paging.
2. Index Required — ALL query filter fields, foreign keys, and sort columns MUST have database indexes configured. Verify: entity expressions match index field order, database collections have index management methods, migrations include indexes for WHERE/JOIN/ORDER BY columns.

⚠️ MANDATORY: Confidence & Evidence Gate

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

Activate arch-performance-optimization skill and follow its workflow.

CRITICAL: Present findings and optimization plan. Wait for explicit user approval before making changes.

Graph-Assisted Investigation — When .code-graph/graph.db exists, MUST run at least ONE graph command on key files before concluding. Pattern: Grep finds files → trace --direction both reveals full system flow → Grep verifies details. Use connections for 1-hop, callers_of/tests_for for specific queries, batch-query for multiple files. MUST READ .claude/skills/shared/graph-assisted-investigation-protocol.md for full protocol and checklists. Run python .claude/scripts/code_graph query callers_of <function> --json on hot functions to understand call frequency.

Graph Intelligence (RECOMMENDED if graph.db exists)

If .code-graph/graph.db exists, enhance analysis with structural queries:

• Identify hot paths calling bottleneck: python .claude/scripts/code_graph query callers_of <function> --json
• Batch analysis: python .claude/scripts/code_graph batch-query file1 file2 --json

See .claude/skills/shared/graph-intelligence-queries.md for full query reference.

Graph-Trace for Hot Path Analysis

When graph DB is available, use trace to map execution paths for performance analysis:

• python .claude/scripts/code_graph trace <bottleneck-file> --direction both --json — full call chain: what triggers this code + what it triggers downstream
• python .claude/scripts/code_graph trace <bottleneck-file> --direction downstream --json — downstream cascade (N+1 queries, excessive event handlers)
• Cross-service MESSAGE_BUS edges reveal distributed performance bottlenecks

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Workflow Recommendation

IMPORTANT MUST: If you are NOT already in a workflow, use AskUserQuestion to ask the user:

1. Activate quality-audit workflow (Recommended) — performance → sre-review → test
2. Execute /performance directly — run this skill standalone

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Next Steps

MANDATORY IMPORTANT MUST after completing this skill, use AskUserQuestion to recommend:

• "/sre-review (Recommended)" — Production readiness review after optimization
• "/changelog" — Document performance changes
• "Skip, continue manually" — user decides

Closing Reminders

MANDATORY IMPORTANT MUST break work into small todo tasks using TaskCreate BEFORE starting. MANDATORY IMPORTANT MUST validate decisions with user via AskUserQuestion — never auto-decide. MANDATORY IMPORTANT MUST add a final review todo task to verify work quality. 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/graph-assisted-investigation-protocol.md before starting