Your AI agent has access to send_email, query_database, and delete_file. Once deployed, it makes decisions autonomously — and autonomously means without you in the loop. When something goes wrong, “an agent did it” is not an incident response.

Microsoft’s open-source Agent Governance Toolkit (AGT) addresses this problem directly. Released in April 2026 under an MIT license (1,500+ GitHub stars), it provides deterministic policy enforcement, approval gates, tamper-evident audit logging, and risk controls for any Python-based agent framework — LangChain, CrewAI, AutoGen, and others.

This guide walks you through getting started with AGT, from installation through writing your first policy.

⚠️ Accuracy note: All commands and code examples in this guide are sourced directly from the official AGT GitHub README. AGT is in Public Preview as of May 2026 — production-quality with Microsoft-signed releases, but may have breaking API changes before GA. Always refer to the official documentation for the most current syntax.

Why Prompt-Level Safety Isn’t Enough

Before diving in, it’s worth understanding the problem AGT solves that prompt instructions cannot.

Telling an agent “don’t drop tables” is a polite request to a stochastic system. Research published at ICLR 2025 found 100% attack success rates on GPT-4o, GPT-3.5, Claude 3, and Llama-3 under adaptive adversarial input. Prompt-level defenses are probabilistic by construction.

AGT’s approach is different: every tool call is intercepted in deterministic application code before the model’s intent reaches the wire. Actions the governance kernel denies aren’t “unlikely” — they’re structurally impossible.

Prerequisites

  • Python 3.10 or higher
  • pip
  • An existing agent codebase (LangChain, CrewAI, AutoGen, or a custom implementation)

Installation

Install the full AGT package:

pip install agent-governance-toolkit[full]

This installs all optional dependencies including the CLI tools, TypeScript SDK bridge, and OWASP compliance checking modules.

Verify your installation:

agt doctor

This checks that all core components are correctly installed and configured.

Your First Governed Tool — Two Lines of Code

AGT’s quickest entry point wraps any existing tool function with the govern() decorator:

from agentmesh.governance import govern

safe_tool = govern(my_tool, policy="policy.yaml")

That’s it. safe_tool evaluates your YAML policy on every call, logs the decision to an audit trail, and raises GovernanceDenied if the action is blocked.

Writing Your First Policy

Create a policy.yaml file in your project root:

# policy.yaml
apiVersion: governance.toolkit/v1
name: production-policy
default_action: allow
rules:
  - name: block-destructive
    condition: "action.type in ['drop', 'delete', 'truncate']"
    action: deny
    description: "Destructive operations require human approval"

  - name: require-approval-for-send
    condition: "action.type == 'send_email'"
    action: require_approval
    approvers: ["security-team"]

With this policy in place:

>>> safe_tool(action="read", table="users")
{'table': 'users', 'rows': 42}

>>> safe_tool(action="drop", table="users")
GovernanceDenied: Action denied by policy rule 'block-destructive':
  Destructive operations require human approval

The policy file supports YAML and OPA Rego formats. YAML is the recommended starting point for most teams.

The PolicyEvaluator API (Programmatic Control)

For more complex scenarios, use the PolicyEvaluator API directly:

from agent_os.policies import (
    PolicyEvaluator, PolicyDocument, PolicyRule,
    PolicyCondition, PolicyAction, PolicyOperator, PolicyDefaults
)

evaluator = PolicyEvaluator(policies=[PolicyDocument(
    name="my-policy", version="1.0",
    defaults=PolicyDefaults(action=PolicyAction.ALLOW),
    rules=[PolicyRule(
        name="block-dangerous-tools",
        condition=PolicyCondition(
            field="tool_name",
            operator=PolicyOperator.IN,
            value=["execute_code", "delete_file"]
        ),
        action=PolicyAction.DENY, priority=100,
    )],
)])

result = evaluator.evaluate({"tool_name": "web_search"})    # Allowed
result = evaluator.evaluate({"tool_name": "delete_file"})   # Blocked

CLI Tools for Validation and Compliance

AGT ships a command-line tool (agt) for validation, auditing, and compliance checking:

# Check installation health
agt doctor

# Run OWASP Agentic Top 10 compliance check
agt verify

# Strict compliance check — fail CI on weak evidence
agt verify --evidence ./agt-evidence.json --strict

# Scan prompts for injection vulnerabilities
agt red-team scan ./prompts/ --min-grade B

# Validate policy YAML files
agt lint-policy policies/

The agt verify command checks your setup against all 10 categories of the OWASP Agentic AI Top 10 — a particularly useful gate to add to CI/CD pipelines before deploying agents to production.

How AGT Works at the Architecture Level

Agent ──► Policy Engine ──► Identity ──► Audit Log
            (YAML/OPA/Cedar)  (SPIFFE/DID/mTLS)  (Tamper-evident)
                 │                                      │
                 ├── Allowed ──► Tool executes           │
                 └── Denied  ──► GovernanceDenied        │
                                                        ▼
                                                 Decision Record

Every layer is optional — most teams start with policy enforcement plus audit logging, which covers the majority of compliance requirements without needing the full stack.

What the OWASP Agentic Top 10 Coverage Means

AGT documents coverage across all 10 OWASP Agentic AI risk categories. These include prompt injection, excessive agency, insecure output handling, and supply-chain risks — the complete set of failure modes that OWASP has identified for production agentic systems.

For organizations preparing for AI audits or regulatory reviews, the agt verify output produces structured evidence that can support compliance documentation directly.

Next Steps

Sources

  1. Microsoft/agent-governance-toolkit — GitHub README
  2. MarkTechPost — Microsoft Agent Governance Toolkit Implementation Tutorial
  3. Microsoft Open Source Blog — Agent Governance Toolkit Release (April 2, 2026)
  4. OWASP Agentic AI Top 10

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260531-2000

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