Skill: Octane performance audit
SkillMediaLets your agent audit or defend Octane app performance across rendering, SSR, hydration, and bundle size.
Use Skill: Octane performance audit in Claude, ChatGPT or Ahel Desktop
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Details
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About this skill
Audit or defend Octane performance. Use when a change can affect per-render, per-node, compiler-output, SSR, hydration, or bundle cost, or when asked whether something is fast enough.
What this skill tells your AI
The instructions your AI receives, as published by octanejs/octane in .agents/skills/performance-audit/SKILL.md and read by ahel’s review.
Use this to investigate performance regressions, benchmark results, scheduler/reconciler overhead, compiler output quality, or ecosystem binding perf.
Read first
- Benchmark README in the affected
benchmarks/*directory packages/octane/src/runtime.tscomments for runtime-level changes- Existing benchmark scripts in
benchmarks/*/package.jsonandrun.mjs
Workflow
-
Define target
- Scenario: mount, update, keyed reorder, context, effects, Suspense, hydration, SSR, binding package.
- Metric: runtime duration, allocations, DOM operations, bundle size, compiler output size, benchmark score.
- Baseline: current
main, previous commit, React, Solid/Ripple comparison, or documented expectation. - Semantic control: the output, identity, ordering, or lifecycle result that proves both candidates perform the same work.
-
Choose harness
- Existing benchmarks:
benchmarks/news,js-framework,recursive-context,signal-favoring,dbmon. - Micro regression: focused Vitest with counters/logging.
- Compiler output: inspect emitted JS from
compile.js/Vite transform. - Browser-only perf: use Playwright or benchmark harness if available.
- Existing benchmarks:
-
Run baseline and candidate
- Warm up.
- Run multiple iterations.
- Record environment and command.
- Avoid mixing dependency install/build changes with code changes.
- Use the same commit inputs, runner options, and machine state. Do not compare a quick smoke result with a full result.
- Treat a delta inside observed variance as inconclusive. Prefer ratio guards and deterministic counters when wall-clock noise is larger than the claim.
-
Diagnose
- Runtime hot paths: scheduler queues, effect flushing, keyed reconciliation, event delegation, context propagation, refs.
- Compiler hot paths: unnecessary deopts, over-broad dynamic regions, missed folding, slot churn, repeated closures.
- Binding hot paths: excessive subscriptions, selector equality failures, layout-effect loops.
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Patch or report
- Prefer measurable changes with a regression test/benchmark note.
- Preserve correctness over micro-optimizations.
- Document tradeoffs and residual risk.
-
Challenge the conclusion
- Inspect whether work was shifted to startup, compilation, hydration, garbage collection, or a less visible branch rather than removed.
- Check allocation lifetime and invalidation for new caches or memoization.
- Attempt a workload that should make the proposed improvement disappear; if it does not, look for a harness or measurement error.
- Re-run the final candidate after self-review changes. Never report a stale intermediate measurement as the final result.
Report template
## Performance audit
- Target: ...
- Baseline command/result: ...
- Candidate command/result: ...
- Delta: ...
## Findings
- ...
## Recommendation
- ...
## Validation
- ...
## Confidence and residual risk
- Noise/variance: ...
- Modes not measured: ...
- Alternative explanation considered: ...
Common pitfalls
- jsdom is poor for layout/paint measurements.
- Differential
innerHTMLtests prove correctness, not performance. - React and Octane may perform different physical DOM move sets while producing identical final DOM.
- Compiler output changes can shift runtime cost; inspect both layers.
Signals
- GitHub stars
- 1k
- Forks
- 61
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
performance-audit-octanejs- Source
- github.com/octanejs/octane