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 endorphin-ai/claude-code-teams --skill reactgit clone --depth 1 https://github.com/endorphin-ai/claude-code-teamsWrote 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/endorphin-ai/claude-code-teams/react)<a href="https://agentmods.dev/skills/endorphin-ai/claude-code-teams/react"><img src="https://agentmods.dev/badge/skills/endorphin-ai/claude-code-teams/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/endorphin-ai/claude-code-teams/react"><img src="https://agentmods.dev/badge/skills/endorphin-ai/claude-code-teams/react.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 | $0.00031 | $0.04419 |
| Opus 5.5 | $0.00012 | $0.01768 |
| Sonnet 5.5 | $0.00006 | $0.00884 |
| Haiku 4.5 | $0.00003 | $0.00442 |
Grade A, and why
react scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
export const apiClient = axios.create({ The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
6 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.
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.
- 1mo ago First seen · 531 lines · 31 tokens per session scan A bb04aaa7c3d3
react is a skill published in the GitHub repository endorphin-ai/claude-code-teams (3 stars, last pushed 7mo ago), with no licence file. It adds 31 tokens to every session and 4,419 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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dev-react-perf
React/Next.js performance optimization. Points to Vercel's react-best-practices (70 rules by impact - waterfalls, bundle, re-renders) and adds what it leaves out - list virtualization, state colocation, profiling tools, Core Web Vitals targets. Trigger when the user wants to optimize rendering, reduce re-renders, or…
dev-shadcn
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state-management
State management patterns and implementation. Trigger when the user wants to manage global state, use Redux, Zustand, or other solutions.
React 最佳实践
A set of React guidance covering component design patterns, Hooks, and performance optimisation. React is a JavaScript library for building user interfaces, and Hooks are functions used in React components.
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AI-powered multi-agent code review. Simulates a team of Principal Engineers reviewing code from different perspectives. Use when asked to review code, check a PR, analyze changes, or perform code review.