awesome-ai-anatomy: Source code teardowns of 14 AI coding agents

by NeuZhou · MCP Server · ★ 237

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 54/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentai-coding-assistantai-securityawesomeawesome-listclaude-codeclinecode-reviewcoding-agentdesign-patterns

Quick Facts

Stars237
Forks19
LanguageD2
CategoryMCP Server
LicenseMIT
Quality Score54/100
Open Issues13
Last Updated2026-04-13
Created2026-04-04
Platformsclaude-code, cli, codex, mcp
Est. Tokens~1546k

About awesome-ai-anatomy

NEW: AgentSentinel -- We went from studying agent anatomy to protecting it. A zero-trust local proxy that monitors, secures, and records every decision your AI agent makes. Built from the security findings of our 16+ agent teardowns. English | 简体中文 <h

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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