agent-governance-toolkit: AI Agent Governance Toolkit — Policy enforcement, zero-trust identity, execution sandboxing, and reliability

Last updated: 2026-10-23 · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install agent-governance-toolkit

pip install agent-governance-toolkit[full]
pip install agent-governance-toolkit    # Compliance & attestation

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 67/100

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. Full audit →

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.

agent-frameworkai-agentsai-safetycompliancegovernancemicrosoftowasppolicy-enginepythonsecurity

Quick Facts

Stars	6,459
Forks	1,106
Language	Python
Category	Agent Tool
License	MIT
Quality Score	67/100
Open Issues	109
Last Updated	2026-10-23
Created	2026-03-02
Platforms	python
Est. Tokens	~17k

About agent-governance-toolkit

Welcome to Agent Governance Toolkit! [!IMPORTANT] Community Preview — Not Official Microsoft-Signed Releases All packages currently published from this repository (PyPI, npm, NuGet) are community preview releases for testing and evaluation purposes only. They are not official Micro

Compatible Skills

These tools work well together with agent-governance-toolkit for enhanced workflows:

agent-audit — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
superagentx — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
asqav-sdk — semantic(0.30)+complementary+rare_topics+same_lang+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:

View on GitHub → Browse Agent Tool tools