No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by GPT-AGI · Codex Skill · ★ 651
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Clawd-Code safe to install? View the security audit →
English Português 🚀 Claude Code Python A Complete Python Reimplementation Based on Real Claude Code Source From TypeScript Source → Rebuilt in Python with ❤️ 🔥 Active Development • New Features Weekly 🔥 🎯 What is This? Clawd Code is a complete Python rewrite of Claude Code, based on the real TypeScript source code. ⚠️ Important: This is NOT Just Source Code Unlike the leaked TypeScript source, Clawd Codex is a fully functional, runnable CLI tool: |  server
Code search MCP for Claude Code. Make entire codebase the context for any coding agent. Embeddings are created
Your own Claude Code UI, sandbox, in-browser VS Code, terminal, multi-provider support (Anthropic, OpenAI, Git
📚 Your AI coding setup, everywhere. Manage skills, agents, rules, MCP connections and hooks in one place, wit
Explore other popular codex skill tools:
Clawd-Code is Claude-Code-Python: Reconstructing Claude Code in Python. It is categorized as a Codex Skill with 651 GitHub stars.
Clawd-Code is primarily written in Python. It covers topics such as claude, claude-code, openclaw.
You can find installation instructions and usage details in the Clawd-Code GitHub repository at github.com/GPT-AGI/Clawd-Code. The project has 651 stars and 313 forks, indicating an active community.
Clawd-Code is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Clawd-Code on Agent Skills Hub include MeiGen-AI-Design-MCP, arcade-mcp, Overture. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: