agent-governance
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems.
Skill by miyake-san
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: security, writing, agent-building
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What's inside
- Skill name
agent-governance- Description
- 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, AutoGen)
- License
- MIT
- Instructions
- 558 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- body: 558 lines (spec recommends under 500)
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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:
"""Declarative policy controlling agent behavior."""
name: str
allowed_tools: list[str] = field(default_factory=list) # allowlist
blocked_tools: list[str] = field(default_factory=list) # blocklist
blocked_patterns: list[str] = field(default_factory=list) # content filters
max_calls_per_request: int = 100 # rate limit
require_human_approval: list[str] = field(default_factory=list) # tools needing approval
def check_tool(self, tool_name: str) -> PolicyAction:
"""Check if a tool is allowed by this policy."""
if tool_name in self.blocked_tools:
return PolicyAction.DENY
if tool_name in self.require_human_approval:
return PolicyAction.REVIEW
if self.allowed_tools and tool_name not in self.allowed_tools:
return PolicyAction.DENY
return PolicyAction.ALLOW
def check_content(self, content: str) -> Optional[str]:
"""Check content against blocked patterns. Returns matched pattern or None."""
for pattern in self.blocked_patterns:
if re.search(pattern, content, re.IGNORECASE):
return pattern
return None
```
### Policy Composition
Combine multiple policies (e.g., org-wide + team + agent-specific):
```python
def compose_policies(*policies: GovernancePolicy) -> GovernancePolicy:
"""Merge policies with most-restrictive-wins semantics."""
combined = GovernancePolicy(name="composed")
for policy in policies:
combined.blocked_tools.extend(policy.blocked_tools)
combined.blocked_patterns.extend(policy.blocked_patterns)
combined.require_human_approval.extend(policy.require_human_approval)
combined.max_calls_per_request = min(
combined.max_calls_per_request,
policy.max_calls_per_request
)
if policy.allowed_tools:
if combined.allowed_tools:
combined.allowed_tools = [
t for t in combined.allowed_tools if t in policy.allowed_tools
]
else:
combined.allowed_tools = list(policy.allowed_tools)
return combined
# Usage: layer policies from broad to specific
org_policy = GovernancePolicy(
name="org-wide",
blocked_tools=["shell_exec", "delete_database"],
blocked_patterns=[r"(?i)(api[_-]?key|secret|password)\s*[:=]"],
max_calls_per_request=50
)
team_policy = GovernancePolicy(
name="data-team",
allowed_tools=["query_db", "read_file", "write_report"],
require_human_approval=["write_report"]
)
agent_policy = compose_policies(org_policy, team_policy)
```
### Policy as YAML
Store policies as configuration, not code:
```yaml
# governance-policy.yaml
name: production-agent
allowed_tools:
- search_documents
- query_databaseFrom miyake-san/sogo-agent-platform, MIT.
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Signals
- Stars
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- Forks
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- Open issues
- 0
- Last commit (this folder)
- Aug 28, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
agent-governance skill. Agent Mart. https://agentmart.dev/skills/miyake-san-agent-governance (last updated 2026-10-24)