AI-Governor-Framework: The Keystone Framework for AI-Driven Code

by Fr-e-d · Agent Tool · ★ 77

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

How to install AI-Governor-Framework

git clone https://github.com/Fr-e-d/AI-Governor-Framework.git .ai-governor

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 62/100

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.

aiai-agentai-agents-frameworkai-frameworkai-governanceclaude-aiclaude-codecontext-engineeringcursor-aideveloper-tools

Quick Facts

Stars77
Forks9
CategoryAgent Tool
LicenseApache-2.0
Quality Score62/100
Last Updated2026-03-11
Created2025-07-25
Platformsclaude-code, gemini
Est. Tokens~31k

About AI-Governor-Framework

AI Governor Framework The Keystone for AI-Driven Code Stop fighting your AI assistant. Start governing it. Tired of AI-generated code that's buggy, inconsistent, and ignores your architecture? The AI Governor Framework is a safe, plug-and-play system designed to teach your AI your project's unique DNA.

Compatible Skills

These tools work well together with AI-Governor-Framework for enhanced workflows:

  • awesome-vibe-coding-guide — semantic(0.30)+complementary+rare_topics+similar_pop+shared_platform (59%)
  • MCAF — semantic(0.30)+complementary+rare_topics+similar_pop+shared_platform (50%)

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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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