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analyze-performance-traces

tutti-os · Разработка

Analyze Chrome, Chromium, Electron, React DevTools, or Perfetto-compatible JSON traces and audit user-reported profiling findings without loading large artifacts into context; prove trigger-to-render/layout chains, separate measured facts from source inference, find exact code choke points, classify forced layout and render fanout, implement semantically safe fixes, and verify behavior plus repository budgets. Use for trace files, reported profiling durations or call chains, dropped frames, long

Оригинален текст · няма потвърден превод на български
Платформи: Не са посочениНиво: Не е посоченоВ индекса: 21.09.2026 г.Обновен в GitHub: 05.09.2026 г.

Теми: agent-collaboration · agent-orchestration · agent-workspace · agentic-ai · agentic-workflow · ai-agents · ai-tools · ai-workspace · claude-code · codex · coding-agent · desktop-app · developer-tools · hermes-agent · local-first

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22.09.2026 г.

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Analyze Performance Traces

End with an evidence chain from trigger to exact source. Fix the earliest proven cause. Never turn an API name or an inclusive duration into a causal claim without checking execution context.

Choose the evidence mode

State which mode applies before making findings:

  1. Trace-backed: a trace is supplied or discoverable. Durations, processes, threads, and event ordering may be reported from it.
  2. Reported-finding audit: the user supplies durations or a chain but not the artifact. Treat those details as leads. Confirm current source paths and trigger conditions; label the durations, thread, and invalidation scope unverified.
  3. Source-only: no trace-derived lead exists. Report hypotheses, not measured bottlenecks.

Do not block a reported-finding audit merely because the original trace file is absent. If the user asks for safe implementation after the source chain is proven, proceed within authorization; require a comparable post-change trace before claiming millisecond or frame-rate improvement.

If neither a trace nor a concrete lead exists, ask for the smallest reproducible capture unless the user explicitly wants source-only analysis.

Start safely

  1. Read repository instructions, nearest area instructions, relevant architecture docs, current diff, and validation policy. Record Git baseline before editing.

  2. Discover trace artifacts without printing them wholesale. For each candidate:

    ls -lh TRACE.json
head -c 512 TRACE.json
tail -c 512 TRACE.json

  3. Run the bundled bounded-memory summarizer:

    node <skill-dir>/scripts/summarize-trace TRACE.json --top 40 --min-ms 16

  4. Record trace revision/build, production versus development mode, profiling hooks, source maps, screenshots, React tracks, renderer count, and capture window. Separate profiler startup and instrumentation overhead from product work.

  5. Prefer a repository-owned performance runner when it reproduces the same interaction. List scenarios first; a convenient but different scenario is not proof. In this repository, inspect docs/conventions/testing.md and use pnpm perf:agent-gui -- --list-scenarios when relevant.

Tutti manual capture

When a new Desktop trace is required:

TUTTI_ELECTRON_REMOTE_DEBUGGING_PORT=9223 \
TUTTI_ELECTRON_JS_FLAGS=--max-old-space-size=8192 \
VITE_TUTTI_WHY_DID_YOU_RENDER=0 \
make dev-gui

Then capture from another terminal:

Целият SKILL.md в GitHub