OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skillsnpx agentmods add skills/leoyeai/openclaw-master-skills/afrexai-react-productionWrote 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/leoyeai/openclaw-master-skills/afrexai-react-production)<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/afrexai-react-production"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/afrexai-react-production/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/leoyeai/openclaw-master-skills/afrexai-react-production"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/afrexai-react-production.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 | $0.00032 | $0.06962 |
| Opus 5.5 | $0.00013 | $0.02785 |
| Sonnet 5.5 | $0.00006 | $0.01392 |
| Haiku 4.5 | $0.00003 | $0.00696 |
Grade A, and why
afrexai-react-production 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 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.
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 — 759 lines — stays where its author put it; the contents beside it link to each section on GitHub.
React Production Engineering
Complete methodology for building production-grade React applications. Covers architecture decisions, component design, state management, performance optimization, testing, and deployment — not just API reference, but engineering methodology with decision frameworks, templates, and scoring systems.
Phase 1: Architecture Assessment
Quick Health Check (score /16)
- Component tree depth < 6 levels (+2)
- No prop drilling past 2 levels (+2)
- Bundle size < 200KB gzipped (+2)
- LCP < 2.5s on 4G (+2)
- Test coverage > 70% on business logic (+2)
- Zero
anytypes in production code (+2) - No direct DOM manipulation (+2)
- Consistent error boundaries (+2)
Architecture Brief
project:
name: ""
type: "" # spa | ssr | hybrid | static
framework: "" # next | remix | vite-spa | astro
scale: "" # small (<20 routes) | medium (20-100) | large (100+)
team_size: "" # solo | small (2-5) | medium (6-15) | large (15+)
current_state:
react_version: "" # 18 | 19
typescript: true
router: "" # react-router | next-app | tanstack-router
state_management: "" # useState | zustand | jotai | redux | tanstack-query
styling: "" # tailwind | css-modules | styled-components | vanilla-extract
testing: "" # vitest | jest | playwright | cypress
ci_cd: "" # github-actions | gitlab-ci | vercel
pain_points: []
goals: []
Framework Selection Decision Matrix
| Factor | Vite SPA | Next.js | Remix | Astro |
|---|---|---|---|---|
| SEO needed | ❌ | ✅ Best | ✅ Good | ✅ Best |
| Dashboard/app | ✅ Best | ✅ Good | ✅ Good | ❌ |
| Content-heavy | ❌ | ✅ Good | ✅ Good | ✅ Best |
| Team familiarity | ✅ Simple | ⚠️ Learning curve | ⚠️ Web standards | ⚠️ Islands |
| Deployment | Anywhere | Vercel optimal | Anywhere | Anywhere |
| Bundle size | You control | Framework overhead | Smaller | Minimal JS |
Decision rules:
- Dashboard/internal tool with no SEO → Vite SPA
- Marketing + app hybrid → Next.js
- Content-first with some interactivity → Astro
- Web-standards-first, nested layouts → Remix
- Default for most SaaS products → Next.js
What ships with it
2 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 · 759 lines · 32 tokens per session scan A 394c02456b7c
afrexai-react-production is a skill published in the GitHub repository LeoYeAI/openclaw-master-skills (2,166 stars, last pushed 3mo ago), licensed MIT. It adds 32 tokens to every session and 6,962 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
next-cache-components-optimizer
Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…
server-side-calls
Call tRPC procedures directly from server code using t.createCallerFactory() and router.createCaller(context) for integration testing, internal server logic, and custom API endpoints. Catch TRPCError and extract HTTP status with getHTTPStatusCodeFromError(). Error handling via onError option.
verify
Build/launch/drive recipe for verifying apps/docs changes at runtime (demos, docs pages, llms.txt).
implement-feature
Implement an approved feature plan with benefit-based placement, TDD, revision-bound evidence, and PR-ready output.
walkeros-testing-strategy
Use when writing tests, reviewing test code, or discussing testing approach for walkerOS packages. Covers env pattern, dev examples, and package-specific strategies.
writing-tests
Gates whether a new test should exist and forces it to be efficient, protecting CI from low-value test bloat. Use before any change to what a pytest, Jest, or Playwright test asserts or sets up, down to one fixture or one assertion added to an existing block. Front-loads the value bar (every test must catch a…