unclecode/crawl4ai
GitHubOfficial Crawl4AI Cloud: a hosted web scraping, extraction, and search API for AI agents. Free API key, 1,000 credits a month, no card. Fully open source: this repo is the Apache-2.0 crawler that powers it, and you can self-host it.
- Stars:
- 86.9k
- Language:
- Python
- Default branch:
- main
- Last scored:
At a glance
- Rank
- #210 of 401
- #40 of 56 Python repos
- Checks passed
- 8 of 17
- Full list below
- Best set up for
- Claude Code
- Score 72.4
- Needs most work for
- Cursor
- Biggest fix: Cursor rules (.cursor/rules) (+11.5 pts)
What it has
What it's missing
What to fix first
Showing fixes for Claude Code
- 1AGENTS.md / CLAUDE.mdAdd an AGENTS.md covering project goals, layout, setup commands, and conventions. Aim for 800+ chars of real guidance (not boilerplate).+13.2 pts
- 2Type configurationAdd a type config (tsconfig.json for JS/TS, mypy.ini or pyrightconfig.json for Python). Rust/Go/JVM/Scala/Swift/C#/OCaml/Haskell/Zig are typed by default.+7.9 pts
- 3Pre-commit / git hooksSet up pre-commit (.pre-commit-config.yaml), husky, or lefthook to run format+lint on every commit.+5.3 pts
Score for each AI agent
Each agent weighs the checks by its own docs. Under each score are its top three. How each agent is scored →
Does unclecode/crawl4ai have agent instructions?
An AGENTS.md (or CLAUDE.md) at the root tells AI coding agents how to build, test and work in the repo. A few agents also read a file of their own.
- AGENTS.md / CLAUDE.md
- None at the root (no AGENTS.md, CLAUDE.md, AGENT.md, .claude/CLAUDE.md or .claude/AGENTS.md)
- Agent-specific files
- None: no GEMINI.md, .cursor/rules, .openhands/setup.sh, .aider.conf.yml or .agents/skills
- Repos that have one
- 29 of 56 Python repos · 221 of 401 repos on the leaderboard · See examples →
Get a starter AGENTS.md
From the files the checks found. Fill in the commands, then commit it at the root.
# AGENTS.md
Guidance for AI coding agents working in unclecode/crawl4ai. Official Crawl4AI Cloud: a hosted web scraping, extraction, and search API for AI agents. Written mainly in Python.
## Where things are
- Dependencies are declared in `pyproject.toml`.
- Tests live in `tests`.
- Lint and format rules are configured in `setup.cfg`.
- CI is defined in `.github/workflows`; read it for the exact install, lint and test steps.
- A reproducible environment is defined in `Dockerfile`.
- Follow the conventions in `CONTRIBUTING.md`.
## Commands
<!-- Fill in the exact commands CI runs. -->
- Install: TODO
- Test: TODO
- Lint: TODO
All 17 checks · 8 passed
How unclecode/crawl4ai compares
- vs leaderboard average
- 0.4 pts above
- Average 66.8
- vs Python average
- 3.8 pts below
- Average 71.0
- Stars among Python repos
- #13 of 56
Missing here, and how many repos have it
- Type configuration · passed by 68% of leaderboard repos, 57% of Python repos
- Pre-commit / git hooks · passed by 29% of leaderboard repos, 71% of Python repos
- Skills (.agents/skills) · passed by 17% of leaderboard repos, 20% of Python repos
Passes checks most repos miss
- Reproducible dev env · only 22% of repos pass it
One fix for the most agents: AGENTS.md / CLAUDE.md would raise the score for all 9 agents, by up to 13.3 points.
Similar repos
Same language and host as this repo, closest in overall score.
- Python · 145k ★
- encode/httpx67.4Python · 15.7k ★
- Kludex/uvicorn67.4Python · 11.1k ★
- tqdm/tqdm67.1Python · 31.4k ★
- explosion/spaCy66.2Python · 34k ★
- django/django65.8Python · 91.5k ★
Same topics, any language
Repos tagged with the same GitHub topics, most shared first.
- TypeScript · AI agents, crawler, data extraction, LLM, Markdown, scraper, web crawler, web scraping
- Svelte · LLM, mcp, rag
- Python · AI agents, LLM, rag
- Python · AI agents, LLM, rag
- mastra-ai/mastra84.4TypeScript · AI agents, LLM, mcp
- scrapy/scrapy86.8Python · crawler, web scraping
Add a badge to your README
Paste this at the top of the README. It shows the score, and links back to this page.
[](https://agentfriendlycode.com/repo/github/unclecode/crawl4ai)Check the score on every pull request
A GitHub Action posts one comment per pull request with how the score changed and why.