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.
npx agentmods add skills/afk-surf/openbridge/react-component-performancenpx skills add AFK-surf/OpenBridge --skill react-component-performancegit clone --depth 1 https://github.com/AFK-surf/OpenBridgeWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00052 | $0.00467 |
| Opus 5 | $0.00026 | $0.00234 |
| Sonnet 5 | $0.00010 | $0.00093 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
react-component-performance 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 2d ago.
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.
What it actually says
React Component Performance
Overview
Identify render hotspots, isolate expensive updates, and apply targeted optimizations without changing UI behavior.
Workflow
- Reproduce or describe the slowdown.
- Identify what triggers re-renders (state updates, props churn, effects).
- Isolate fast-changing state from heavy subtrees.
- Stabilize props and handlers; memoize where it pays off.
- Reduce expensive work (computation, DOM size, list length).
- Validate with profiling; avoid speculative changes.
Checklist
- Measure: use React DevTools Profiler or log renders; capture baseline.
- Find churn: identify state updated on a timer, scroll, input, or animation.
- Split: move ticking state into a child; keep heavy lists static.
- Memoize: wrap leaf rows with
memoonly when props are stable. - Stabilize props: use
useCallback/useMemofor handlers and derived values. - Avoid derived work in render: precompute, or compute inside memoized helpers.
- Control list size: window/virtualize long lists; avoid rendering hidden items.
- Keys: ensure stable keys; avoid index when order can change.
- Effects: verify dependency arrays; avoid effects that re-run on every render.
- Style/layout: watch for expensive layout thrash or large Markdown/diff renders.
Optimization Patterns
- Isolate ticking state: move a timer/animation into a child component so the parent list does not re-render every tick.
- Stabilize callbacks: prefer
useCallbackfor handlers passed to memoized rows. - Split rows: extract list rows into memoized components with narrow props.
- Defer heavy rendering: lazy-render or collapse expensive content until expanded.
- Prefer derived data outside render: compute summaries with
useMemoor helper functions when inputs are stable.
Example Reference
Load references/examples.md when the user wants a concrete refactor example.
What ships with it
1 file 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.
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.
- 2d ago First seen · 45 lines · 52 tokens per session scan A b3ffe6f6767c
react-component-performance is a skill published in the GitHub repository AFK-surf/OpenBridge (424 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 467 once invoked, about $0.0003 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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