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 skills add cmaranho/rn-agent-skills --skill rn-performancegit clone --depth 1 https://github.com/cmaranho/rn-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cmaranho/rn-agent-skills/rn-performance)<a href="https://agentmods.dev/skills/cmaranho/rn-agent-skills/rn-performance"><img src="https://agentmods.dev/badge/skills/cmaranho/rn-agent-skills/rn-performance/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cmaranho/rn-agent-skills/rn-performance"><img src="https://agentmods.dev/badge/skills/cmaranho/rn-agent-skills/rn-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00461 |
| Opus 5 | $0.00024 | $0.00230 |
| Sonnet 5 | $0.00010 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
rn-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 9d 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 Native — Performance
Objetivo
Entregar UI fluida e inicialização rápida, otimizando com base em medição, não em suposição.
Quando utilizar
- Jank em scroll/animação, renders excessivos ou telas lentas.
- Alto uso de memória ou tempo de inicialização elevado.
- Revisão de performance de listas e componentes pesados.
Conhecimentos necessários
- Modelo de threads do RN (JS thread vs UI/main thread).
- Profiling (ex.: Flipper, React DevTools Profiler, Perf Monitor, Hermes).
- Memoização (
memo,useMemo,useCallback) e integridade referencial. - Virtualização de listas e otimização de imagens.
Fluxo de execução
- Meça primeiro: reproduza e faça profiling; identifique o gargalo real.
- Isole a causa (re-render, trabalho na main thread, lista não virtualizada, imagem grande).
- Aplique a correção mínima (memoização, selector granular, virtualização, mover trabalho para a UI thread).
- Meça de novo e compare; evite otimização especulativa.
- Adicione uma guarda contra regressão quando possível.
Boas práticas
- Componentes/hooks puros; props referencialmente estáveis.
- Listas virtualizadas com
keyExtractorestável e item memoizado. - Anime na UI thread; evite bloquear a JS thread.
- Lazy load de telas/recursos; imagens dimensionadas e cacheadas.
Armadilhas comuns
- Otimizar sem medir.
- Literais inline de objeto/função quebrando
memo. indexcomo key em listas.- Trabalho síncrono pesado no render ou na main thread.
Critérios de sucesso
- Gargalo medido antes e depois, com ganho comprovado.
- Sem jank perceptível no fluxo alvo.
- Sem re-renders desnecessários no caminho crítico.
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.
- 9d ago First seen · 52 lines · 48 tokens per session scan A a15604f0e8b2
rn-performance is a skill published in the GitHub repository cmaranho/rn-agent-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 48 tokens to every session and 461 once invoked, about $0.0002 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 2026-08-31.
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