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 nimadorostkar/Claude-Skills-collection --skill reactgit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/react)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/react"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/react/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/nimadorostkar/claude-skills-collection/react"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/react.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.01113 |
| Opus 5 | $0.00019 | $0.00557 |
| Sonnet 5 | $0.00008 | $0.00223 |
| Haiku 4.5 | $0.00004 | $0.00111 |
Grade A, and why
react 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
React
Purpose
Write React where state lives in one place, effects are rare, and re-renders are understood rather than suppressed with memoization applied at random.
When to Use
- Building or reviewing React components.
- Diagnosing unnecessary re-renders or stale state.
- Deciding where state belongs: local, lifted, context, or server.
- Removing
useEffectcalls that should not exist.
Capabilities
- Component decomposition and state colocation.
- Hook correctness: dependencies, cleanup, and the rules that are not optional.
- State management selection:
useState,useReducer, context, external store, server state. - Data fetching with TanStack Query or the framework's own loader.
- Render profiling and targeted memoization.
Inputs
- The component tree and where data enters it.
- The interaction and its performance characteristics, if performance is the concern.
- React version — the correct answer changed with 18 and again with 19.
Outputs
- Components with a single source of truth for each piece of state.
- Effects only where genuinely synchronizing with an external system.
- Memoization applied where a profile shows it is needed.
Workflow
- Locate the state — Put it as close to where it is used as possible. Lift only when two siblings need it. Reach for context only when prop drilling exceeds about three levels.
- Separate server state from client state — Data from an API is cache, not state. It has staleness, refetching, and error semantics that
useStatedoes not model. Use a query library. - Delete unnecessary effects — An effect that computes a value from props belongs in render. An effect that resets state on a prop change belongs in a
key. MostuseEffectcalls in a typical codebase should not exist. - Profile before memoizing — React DevTools Profiler shows what actually re-renders and why.
useMemoon a cheap computation costs more than it saves. - Make the dependencies honest — Never silence the exhaustive-deps lint rule. If the array is wrong, the bug is a stale closure, and it will be intermittent.
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.
- 6d ago First seen · 104 lines · 38 tokens per session scan A 9284de75f44d
react is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 22d ago), licensed MIT. It adds 38 tokens to every session and 1,113 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 2026-09-03.
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