Agent skill

Firecrawl Scraper

by ynulihao in ynulihao/AgentSkillOS

Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data.

MITAuto-check: notesData & Analytics

Install Firecrawl Scraper

skills CLI
$ npx skills add ynulihao/AgentSkillOS --skill firecrawl-scraper -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ynulihao/AgentSkillOS firecrawl-scraper --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ynulihao/AgentSkillOS.git skills-src && mkdir -p .claude/skills && cp -r skills-src/data/skill_seeds/firecrawl-scraper .claude/skills/firecrawl-scraper && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
firecrawl-scraper
GitHub stars
617
Used in
1 other repo
Token cost
~4.1k tokens
SKILL.md length
838 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data.

  • Works in 7 steps: /v2/scrape - Single Page Scraping → /v2/crawl - Full Site Crawling → /v2/map - URL Discovery → …
  • : scraping websites
  • SKILL.md covers What is Firecrawl?, API Endpoints, Authentication and Python SDK Usage, plus 4 more sections
  • Calls npm, pip and pnpm; reaches news.com and api.firecrawl.dev; needs FIRECRAWL_API_KEY

What it does

Firecrawl Scraper is an agent skill from ynulihao/AgentSkillOS. Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Use when: scraping websites, crawling entire sites, extracting web content, converting HTML to markdown, building web scrapers, handling dynamic JavaScript content, bypassing anti-bot protection, extracting structured data from web pages, or when encountering "content not loading", "JavaScript rendering issues", or "blocked by bot detection". Keywords: firecrawl, firecrawl…

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Web scraping. It works with Firecrawl and JavaScript. The repository describes itself as: Build your agent from 200,000+ skills via skill RETRIEVAL & ORCHESTRATION. The licence is MIT.

When your agent uses it

  • : scraping websites
  • Crawling entire sites
  • Extracting web content
  • Converting HTML to markdown

Example prompts

  • “content not loading”
  • “JavaScript rendering issues”
  • “blocked by bot detection”
  • “/firecrawl-scraper”

Requirements

  • Python 3
  • Node.js
  • A credential in FIRECRAWL_API_KEY

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. /v2/scrape - Single Page Scraping
  2. /v2/crawl - Full Site Crawling
  3. /v2/map - URL Discovery
  4. /v2/extract - Structured Data Extraction
  5. Documentation Scraping
  6. Product Data Extraction
  7. News Article Scraping

What it can do on your machine

Read from SKILL.md and the folder at commit c3cfae1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm
    • pip
    • pnpm
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • news.com
    • api.firecrawl.dev

    Also links to:

    • docs.firecrawl.dev
    • firecrawl.dev
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • FIRECRAWL_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Firecrawl Scraper loads about 4.1k tokens when it runs. Until then it costs about 211 tokens; SKILL.md has 838 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~211
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:102
    # .env file
  • NoteMentions a .env fileSKILL.md:107
    # .env.local (for local development)

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ynulihao/AgentSkillOS at commit c3cfae1, republished under its MIT licence (© ynulihao). 838 words, ~4,108 tokens.

Download SKILL.mdSave it as .claude/skills/firecrawl-scraper/SKILL.md (or your agent's skills folder).
name
firecrawl-scraper
description
Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Use when: scraping websites, crawling entire sites, extracting web content, converting HTML to markdown, building web scrapers, handling dynamic JavaScript content, bypassing anti-bot protection, extracting structured data from web pages, or when encountering "content not loading", "JavaScript rendering issues", or "blocked by bot detection". Keywords: firecrawl, firecrawl api, web scraping, web crawler, scrape website, crawl website, extract content, html to markdown, site crawler, content extraction, web automation, firecrawl-py, firecrawl-js, llm ready data, structured data extraction, bot bypass, javascript rendering, scraping api, crawling api, map urls, batch scraping
license
MIT

Firecrawl Web Scraper Skill

Status: Production Ready ✅ Last Updated: 2025-10-24 Official Docs: https://docs.firecrawl.dev API Version: v2


What is Firecrawl?

Firecrawl is a Web Data API for AI that turns entire websites into LLM-ready markdown or structured data. It handles:

  • JavaScript rendering - Executes client-side JavaScript to capture dynamic content
  • Anti-bot bypass - Gets past CAPTCHA and bot detection systems
  • Format conversion - Outputs as markdown, JSON, or structured data
  • Screenshot capture - Saves visual representations of pages
  • Browser automation - Full headless browser capabilities

API Endpoints

1. /v2/scrape - Single Page Scraping

Scrapes a single webpage and returns clean, structured content.

Use Cases:

  • Extract article content
  • Get product details
  • Scrape specific pages
  • Convert HTML to markdown

Key Options:

  • formats: ["markdown", "html", "screenshot"]
  • onlyMainContent: true/false (removes nav, footer, ads)
  • waitFor: milliseconds to wait before scraping
  • actions: browser automation actions (click, scroll, etc.)
2. /v2/crawl - Full Site Crawling

Crawls all accessible pages from a starting URL.

Use Cases:

  • Index entire documentation sites
  • Archive website content
  • Build knowledge bases
  • Scrape multi-page content

Key Options:

  • limit: max pages to crawl
  • maxDepth: how many links deep to follow
  • allowedDomains: restrict to specific domains
  • excludePaths: skip certain URL patterns
3. /v2/map - URL Discovery

Maps all URLs on a website without scraping content.

Use Cases:

  • Find sitemap
  • Discover all pages
  • Plan crawling strategy
  • Audit website structure
4. /v2/extract - Structured Data Extraction

Uses AI to extract specific data fields from pages.

Use Cases:

  • Extract product prices and names
  • Parse contact information
  • Build structured datasets
  • Custom data schemas

Key Options:

  • schema: Zod or JSON schema defining desired structure
  • systemPrompt: guide AI extraction behavior

Authentication

Firecrawl requires an API key for all requests.

Get API Key
  1. Sign up at https://www.firecrawl.dev
  2. Go to dashboard → API Keys
  3. Copy your API key (starts with fc-)
Store Securely

NEVER hardcode API keys in code!

bash
# .env file
FIRECRAWL_API_KEY=fc-your-api-key-here
bash
# .env.local (for local development)
FIRECRAWL_API_KEY=fc-your-api-key-here

Python SDK Usage

Installation
bash
pip install firecrawl-py

Latest Version: firecrawl-py v4.5.0+

Basic Scrape
python
import os
from firecrawl import FirecrawlApp

# Initialize client
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))

# Scrape a single page
result = app.scrape_url(
    url="https://example.com/article",
    params={
        "formats": ["markdown", "html"],
        "onlyMainContent": True
    }
)

# Access markdown content
markdown = result.get("markdown")
print(markdown)
Crawl Multiple Pages
python
import os
from firecrawl import FirecrawlApp

app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))

# Start crawl
crawl_result = app.crawl_url(
    url="https://docs.example.com",
    params={
        "limit": 100,
        "scrapeOptions": {
            "formats": ["markdown"]
        }
    },
    poll_interval=5  # Check status every 5 seconds
)

# Process results
for page in crawl_result.get("data", []):
    url = page.get("url")
    markdown = page.get("markdown")
    print(f"Scraped: {url}")
Extract Structured Data
python
import os
from firecrawl import FirecrawlApp

app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))

# Define schema
schema = {
    "type": "object",
    "properties": {
        "company_name": {"type": "string"},
        "product_price": {"type": "number"},
        "availability": {"type": "string"}
    },
    "required": ["company_name", "product_price"]
}

# Extract data
result = app.extract(
    urls=["https://example.com/product"],
    params={
        "schema": schema,
        "systemPrompt": "Extract product information from the page"
    }
)

print(result)

TypeScript/Node.js SDK Usage

Installation
bash
npm install @mendable/firecrawl-js
# or
pnpm add @mendable/firecrawl-js
# or use the unscoped package:
npm install firecrawl

Latest Version: @mendable/firecrawl-js v4.4.1+ (or firecrawl v4.4.1+)

Basic Scrape
typescript
import FirecrawlApp from '@mendable/firecrawl-js';

// Initialize client
const app = new FirecrawlApp({
  apiKey: process.env.FIRECRAWL_API_KEY
});

// Scrape a single page
const result = await app.scrapeUrl('https://example.com/article', {
  formats: ['markdown', 'html'],
  onlyMainContent: true
});

// Access markdown content
const markdown = result.markdown;
console.log(markdown);
Crawl Multiple Pages
typescript
import FirecrawlApp from '@mendable/firecrawl-js';

const app = new FirecrawlApp({
  apiKey: process.env.FIRECRAWL_API_KEY
});

// Start crawl
const crawlResult = await app.crawlUrl('https://docs.example.com', {
  limit: 100,
  scrapeOptions: {
    formats: ['markdown']
  }
});

// Process results
for (const page of crawlResult.data) {
  console.log(`Scraped: ${page.url}`);
  console.log(page.markdown);
}
Extract Structured Data with Zod
typescript
import FirecrawlApp from '@mendable/firecrawl-js';
import { z } from 'zod';

const app = new FirecrawlApp({
  apiKey: process.env.FIRECRAWL_API_KEY
});

// Define schema with Zod
const schema = z.object({
  company_name: z.string(),
  product_price: z.number(),
  availability: z.string()
});

// Extract data
const result = await app.extract({
  urls: ['https://example.com/product'],
  schema: schema,
  systemPrompt: 'Extract product information from the page'
});

console.log(result);

Common Use Cases

1. Documentation Scraping

Scenario: Convert entire documentation site to markdown for RAG/chatbot

python
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))

docs = app.crawl_url(
    url="https://docs.myapi.com",
    params={
        "limit": 500,
        "scrapeOptions": {
            "formats": ["markdown"],
            "onlyMainContent": True
        },
        "allowedDomains": ["docs.myapi.com"]
    }
)

# Save to files
for page in docs.get("data", []):
    filename = page["url"].replace("https://", "").replace("/", "_") + ".md"
    with open(f"docs/{filename}", "w") as f:
        f.write(page["markdown"])
2. Product Data Extraction

Scenario: Extract structured product data for e-commerce

typescript
const schema = z.object({
  title: z.string(),
  price: z.number(),
  description: z.string(),
  images: z.array(z.string()),
  in_stock: z.boolean()
});

const products = await app.extract({
  urls: productUrls,
  schema: schema,
  systemPrompt: 'Extract all product details including price and availability'
});
3. News Article Scraping

Scenario: Extract clean article content without ads/navigation

python
article = app.scrape_url(
    url="https://news.com/article",
    params={
        "formats": ["markdown"],
        "onlyMainContent": True,
        "removeBase64Images": True
    }
)

# Get clean markdown
content = article.get("markdown")

Error Handling

Python
python
from firecrawl import FirecrawlApp
from firecrawl.exceptions import FirecrawlException

app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))

try:
    result = app.scrape_url("https://example.com")
except FirecrawlException as e:
    print(f"Firecrawl error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")
TypeScript
typescript
import FirecrawlApp from '@mendable/firecrawl-js';

const app = new FirecrawlApp({
  apiKey: process.env.FIRECRAWL_API_KEY
});

try {
  const result = await app.scrapeUrl('https://example.com');
} catch (error) {
  if (error.response) {
    // API error
    console.error('API Error:', error.response.data);
  } else {
    // Network or other error
    console.error('Error:', error.message);
  }
}

Rate Limits & Best Practices

Rate Limits
  • Free tier: 500 credits/month
  • Paid tiers: Higher limits based on plan
  • Credits consumed vary by endpoint and options
Best Practices
  1. Use onlyMainContent: true to reduce credits and get cleaner data
  2. Set reasonable limits on crawls to avoid excessive costs
  3. Handle retries with exponential backoff for transient errors
  4. Cache results locally to avoid re-scraping same content
  5. Use map endpoint first to plan crawling strategy
  6. Batch extract calls when processing multiple URLs
  7. Monitor credit usage in dashboard

Cloudflare Workers Integration

⚠️ Important: SDK Compatibility

The Firecrawl SDK cannot run in Cloudflare Workers due to Node.js dependencies (specifically axios which uses Node.js http module). Workers require Web Standard APIs.

✅ Use the direct REST API with fetch instead (see example below).

Alternative: Self-host with workers-firecrawl - a Workers-native implementation (requires Workers Paid Plan, only implements /search endpoint).


Show full SKILL.md (319 more words)Show less
Workers Example: Direct REST API

This example uses the fetch API to call Firecrawl directly - works perfectly in Cloudflare Workers:

typescript
interface Env {
  FIRECRAWL_API_KEY: string;
  SCRAPED_CACHE?: KVNamespace; // Optional: for caching results
}

interface FirecrawlScrapeResponse {
  success: boolean;
  data: {
    markdown?: string;
    html?: string;
    metadata: {
      title?: string;
      description?: string;
      language?: string;
      sourceURL: string;
    };
  };
}

export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    if (request.method !== 'POST') {
      return Response.json({ error: 'Method not allowed' }, { status: 405 });
    }

    try {
      const { url } = await request.json<{ url: string }>();

      if (!url) {
        return Response.json({ error: 'URL is required' }, { status: 400 });
      }

      // Check cache (optional)
      if (env.SCRAPED_CACHE) {
        const cached = await env.SCRAPED_CACHE.get(url, 'json');
        if (cached) {
          return Response.json({ cached: true, data: cached });
        }
      }

      // Call Firecrawl API directly using fetch
      const response = await fetch('https://api.firecrawl.dev/v2/scrape', {
        method: 'POST',
        headers: {
          'Authorization': `Bearer ${env.FIRECRAWL_API_KEY}`,
          'Content-Type': 'application/json',
        },
        body: JSON.stringify({
          url: url,
          formats: ['markdown'],
          onlyMainContent: true,
          removeBase64Images: true
        })
      });

      if (!response.ok) {
        const errorText = await response.text();
        throw new Error(`Firecrawl API error (${response.status}): ${errorText}`);
      }

      const result = await response.json<FirecrawlScrapeResponse>();

      // Cache for 1 hour (optional)
      if (env.SCRAPED_CACHE && result.success) {
        await env.SCRAPED_CACHE.put(
          url,
          JSON.stringify(result.data),
          { expirationTtl: 3600 }
        );
      }

      return Response.json({
        cached: false,
        data: result.data
      });

    } catch (error) {
      console.error('Scraping error:', error);
      return Response.json(
        { error: error instanceof Error ? error.message : 'Unknown error' },
        { status: 500 }
      );
    }
  }
};

Environment Setup: Add FIRECRAWL_API_KEY in Wrangler secrets:

bash
npx wrangler secret put FIRECRAWL_API_KEY

Optional KV Binding (for caching - add to wrangler.jsonc):

jsonc
{
  "kv_namespaces": [
    {
      "binding": "SCRAPED_CACHE",
      "id": "your-kv-namespace-id"
    }
  ]
}

See templates/firecrawl-worker-fetch.ts for a complete production-ready example.


When to Use This Skill

✅ Use Firecrawl when:

  • Scraping modern websites with JavaScript
  • Need clean markdown output for LLMs
  • Building RAG systems from web content
  • Extracting structured data at scale
  • Dealing with bot protection
  • Need reliable, production-ready scraping

❌ Don't use Firecrawl when:

  • Scraping simple static HTML (use cheerio/beautifulsoup)
  • Have existing Puppeteer/Playwright setup working well
  • Working with APIs (use direct API calls instead)
  • Budget constraints (free tier has limits)

Common Issues & Solutions

Issue: "Invalid API Key"

Cause: API key not set or incorrect Fix:

bash
# Check env variable is set
echo $FIRECRAWL_API_KEY

# Verify key format (should start with fc-)
Issue: "Rate limit exceeded"

Cause: Exceeded monthly credits Fix:

  • Check usage in dashboard
  • Upgrade plan or wait for reset
  • Use onlyMainContent: true to reduce credits
Issue: "Timeout error"

Cause: Page takes too long to load Fix:

python
result = app.scrape_url(url, params={"waitFor": 10000})  # Wait 10s
Issue: "Content is empty"

Cause: Content loaded via JavaScript after initial render Fix:

python
result = app.scrape_url(url, params={
    "waitFor": 5000,
    "actions": [{"type": "wait", "milliseconds": 3000}]
})

Advanced Features

Browser Actions

Perform interactions before scraping:

python
result = app.scrape_url(
    url="https://example.com",
    params={
        "actions": [
            {"type": "click", "selector": "button.load-more"},
            {"type": "wait", "milliseconds": 2000},
            {"type": "scroll", "direction": "down"}
        ]
    }
)
Custom Headers
python
result = app.scrape_url(
    url="https://example.com",
    params={
        "headers": {
            "User-Agent": "Custom Bot 1.0",
            "Accept-Language": "en-US"
        }
    }
)
Webhooks for Long Crawls

Instead of polling, receive results via webhook:

python
crawl = app.crawl_url(
    url="https://docs.example.com",
    params={
        "limit": 1000,
        "webhook": "https://your-domain.com/webhook"
    }
)

Package Versions

PackageVersionLast Checked
firecrawl-py4.5.0+2025-10-20
@mendable/firecrawl-js (or firecrawl)4.4.1+2025-10-24
API Versionv2Current

Note: The Node.js SDK requires Node.js >=22.0.0 and cannot run in Cloudflare Workers. Use direct REST API calls in Workers (see Cloudflare Workers Integration section).


Official Documentation


Next Steps After Using This Skill

  1. Store scraped data: Use Cloudflare D1, R2, or KV to persist results
  2. Build RAG system: Combine with Vectorize for semantic search
  3. Add scheduling: Use Cloudflare Queues for recurring scrapes
  4. Process content: Use Workers AI to analyze scraped data

Token Savings: ~60% vs manual integration Error Prevention: API authentication, rate limiting, format handling Production Ready: ✅

© ynulihao, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in data/skill_seeds/firecrawl-scraper of ynulihao/AgentSkillOS.

Open the folder on GitHubat commit c3cfae1

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in ynulihao/AgentSkillOS, which our catalogue first saw on October 7, 2026.

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Questions about Firecrawl Scraper

What does Firecrawl Scraper do?

Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Firecrawl Scraper is an agent skill from ynulihao/AgentSkillOS. Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data.

When should I use Firecrawl Scraper?

Firecrawl Scraper fits situations like: : scraping websites; crawling entire sites; extracting web content; converting HTML to markdown.

How do I install Firecrawl Scraper in Claude Code?

Run `npx skills add ynulihao/AgentSkillOS --skill firecrawl-scraper -a claude-code`. Or copy the skill folder (data/skill_seeds/firecrawl-scraper in ynulihao/AgentSkillOS) into .claude/skills/firecrawl-scraper in your project. Claude Code loads it when a task matches its description.

How do I install Firecrawl Scraper in Codex?

Run `npx skills add ynulihao/AgentSkillOS --skill firecrawl-scraper -a codex`. Or copy the skill folder (data/skill_seeds/firecrawl-scraper in ynulihao/AgentSkillOS) into .agents/skills/firecrawl-scraper in your project. Codex loads it when a task matches its description.

Can I use Firecrawl Scraper in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ynulihao/AgentSkillOS --skill firecrawl-scraper -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/firecrawl-scraper, .gemini/skills/firecrawl-scraper, .github/skills/firecrawl-scraper and .opencode/skills/firecrawl-scraper in your project.

What does Firecrawl Scraper need to run?

Going by SKILL.md and its folder, Firecrawl Scraper needs the command-line tools its instructions call (npm, pip, pnpm and npx) and credentials named FIRECRAWL_API_KEY. Our summary lists: Python 3; Node.js; A credential in FIRECRAWL_API_KEY.

Does Firecrawl Scraper access the network?

SKILL.md names 5 domains. In commands or code: news.com and api.firecrawl.dev; the agent is likely to contact these when it follows the instructions. As links in the text: docs.firecrawl.dev, firecrawl.dev and github.com. This is read from the text; nothing was executed.

Is Firecrawl Scraper safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Firecrawl Scraper use?

Firecrawl Scraper is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Firecrawl Scraper use?

About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Firecrawl Scraper?

Skills that share tags, products or a category with Firecrawl Scraper: Firecrawl Scraper (secondsky/claude-skills, 227 stars), Firecrawl (aiskillstore/marketplace, 430 stars), Firecrawl Scraper (lamm-mit/scienceclaw, 244 stars) and Web Scraping (platonai/Browser4, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Firecrawl Scraper?

ynulihao (a GitHub user) maintains it in ynulihao/AgentSkillOS, which has 617 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on March 7, 2026.

Source: ynulihao/AgentSkillOS on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.