agent-governance
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, Aut
Profile →npx skills add github/awesome-copilot --skill agent-governance --agent copilot
Same command for any agent — swap --agent for claude-code, codex, cursor.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Agent Governance Patterns Patterns for adding safety, trust, and policy enforcement to AI agent systems. ## Overview Governance patterns ensure AI agents operate within defined boundaries — controlling which tools they can call, what content they can process, how much they can do, and maintaining accountability through audit trails. ``` User Request → Intent Classification → Policy Check → Tool Execution → Audit Log ↓ ↓ ↓ Threat Detection Allow/Deny Trust Update ``` ## When to Use - **Agents with tool access**: Any agent that calls external tools (APIs, databases, shell commands) - **Multi-agent systems**: Agents delegating to other agents need trust boundaries - **Production deployments**: Compliance, audit, and safety requirements - **Sensitive operations**: Financial transactions, data access, infrastructure management --- ## Pattern 1: Governance Policy Define what an agent is allowed to do as a composable, serializable policy object. ```python from dataclasses import dataclass, field from enum import Enum from typing import Optional import re class PolicyAction(Enum): ALLOW = "allow" DENY = "deny" REVIEW = "review" # flag for human review @dataclass class GovernancePolicy: "
- Overview
- When to Use
- Pattern 1: Governance Policy
- Policy Composition
- Policy as YAML
- Pattern 2: Semantic Intent Classification
- Pattern 3: Tool-Level Governance Decorator
- Pattern 4: Trust Scoring
- Pattern 5: Audit Trail
- Pattern 6: Framework Integration
- PydanticAI
- CrewAI
- OpenAI Agents SDK
- Governance Levels
What does the agent-governance skill do?
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, Aut
How do I install it?
Run `npx skills add github/awesome-copilot --skill agent-governance --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.