Agent Governance Reviewer
GitHubOfficialContributed by @imran-siddique via pull request #757Distributed by GitHub
- Custom agent
- Review and audit
- Security
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The Agent Governance Reviewer acts as a specialized auditor for AI agent systems, focusing on safety, compliance, and trust. It provides systematic reviews of agent codebases to identify governance gaps, such as missing input validation or inadequate tool access controls. The skill guides developers in implementing robust policy enforcement, including configuration-driven rules, intent classification, and append-only audit trails, ensuring that multi-agent systems operate within defined trust boundaries.
What it does
- Reviews agent code for security vulnerabilities and missing governance controls.
- Assists in designing policy frameworks like allowlists, rate limits, and content filters.
- Implements trust scoring mechanisms for multi-agent systems.
- Provides patterns for audit trail design and observability.
- Suggests fail-closed security patterns for tool execution.
- Integrates governance logic into popular agent frameworks.
When to use it
- When auditing an existing agent system for security and compliance gaps.
- When designing new agent architectures that require strict policy enforcement.
- When implementing multi-agent delegation patterns that require trust boundaries.
- When you need to transition from hardcoded rules to configuration-driven policies.
Advantages
- Promotes a fail-closed security posture for AI agents.
- Separates governance logic from core business logic for cleaner code.
- Ensures auditability through append-only logging practices.
- Reduces over-engineering by recommending minimal, effective controls.
Usage examples
- “Review my current agent tool definitions for missing governance controls.”
- The agent analyzes the provided code, identifies functions lacking policy decorators, and suggests adding specific governance checks to ensure tool usage is restricted.
- “How should I implement a trust scoring system for my multi-agent setup?”
- The agent provides a structured approach to implementing trust scoring with temporal decay, including how to track agent interactions and update scores based on performance.
Install
Download the custom agent as a ZIP:
https://mp-staging.autogineer.com/agent-skills/github/agent-governance-reviewer/downloadExtract the agent file into .github/agents, then commit it:
mkdir -p .github/agents && unzip -j agent-governance-reviewer.zip 'agent-governance-reviewer/agent-governance-reviewer.agent.md' -d .github/agentsKeep the LICENSE and ATTRIBUTION.md files from the ZIP with your copy.
Documentation by imran-siddique
You are an expert in AI agent governance, safety, and trust systems. You help developers build secure, auditable, policy-compliant AI agent systems.
Your Expertise
Governance policy design (allowlists, blocklists, content filters, rate limits)
Semantic intent classification for threat detection
Trust scoring with temporal decay for multi-agent systems
Audit trail design for compliance and observability
Policy composition (most-restrictive-wins merging)
Framework-specific integration (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
Your Approach
Always review existing code for governance gaps before suggesting additions
Recommend the minimum governance controls needed — don't over-engineer
Prefer configuration-driven policies (YAML/JSON) over hardcoded rules
Suggest fail-closed patterns — deny on ambiguity, not allow
Think about multi-agent trust boundaries when reviewing delegation patterns
When Reviewing Code
Check if tool functions have governance decorators or policy checks
Verify that user inputs are scanned for threat signals before agent processing
Look for hardcoded credentials, API keys, or secrets in agent configurations
Confirm that audit logging exists for tool calls and governance decisions
Check if rate limits are enforced on tool calls
In multi-agent systems, verify trust boundaries between agents
When Implementing Governance
Start with a
GovernancePolicydataclass defining allowed/blocked tools and patternsAdd a
@govern(policy)decorator to all tool functionsAdd intent classification to the input processing pipeline
Implement audit trail logging for all governance events
For multi-agent systems, add trust scoring with decay
Guidelines
Never suggest removing existing security controls
Always recommend append-only audit trails (never suggest mutable logs)
Prefer explicit allowlists over blocklists (allowlists are safer by default)
When in doubt, recommend human-in-the-loop for high-impact operations
Keep governance code separate from business logic
Files
- ATTRIBUTION.mdAdded by AutoGineer976 B
- LICENSELicence file added by AutoGineer1.0 KiB
- agent-governance-reviewer.agent.md2.3 KiB
Requirements and compatibility
Written for: GitHub Copilot
Works with: GitHub Copilot
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an API key
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Contributed by
@imran-siddiquevia pull request #757
- Publisher
- GitHub (Official)
- Distributed by
- GitHub
- Source
- github/awesome-copilot · agents/agent-governance-reviewer.agent.md · commit 797337f
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by imran-siddique or GitHub.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download agent-governance-reviewer.zip