analyze-performance-traces

A skill for examining performance recordings from Chrome, Chromium, Electron, React DevTools, or Perfetto. These recordings show what the browser or application did over time during a slow interaction.

In plain words
What is it for?
Use it to investigate reported performance problems, locate source-code choke points, assess forced layout, and decide where a safe fix should start.
Why use it?
It separates measured evidence from guesses and traces a slowdown from the user action to the exact code causing extra rendering, layout work, or other delays.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/tutti-os/tutti/analyze-performance-traces
Any agent
npx skills add tutti-os/tutti --skill analyze-performance-traces
Clone the repo
git clone --depth 1 https://github.com/tutti-os/tutti

Made for: Claude Code, Codex.

Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,562 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00127 $0.02562
Opus 5 $0.00063 $0.01281
Sonnet 5 $0.00025 $0.00512
Haiku 4.5 $0.00013 $0.00256

Measured yesterday against content hash 103f509f4e92, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyze-performance-traces scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.codex/skills/analyze-performance-traces/SKILL.md · 193 lines

How it starts

The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 193 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 193 lines · 127 tokens per session scan A 103f509f4e92

Subscribe to this mod's changes

analyze-performance-traces is a skill published in the GitHub repository tutti-os/tutti (3,632 stars, last pushed 2d ago), licensed Apache-2.0. It adds 127 tokens to every session and 2,562 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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