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Quickstart¶

Use a native ACS manifest for policy and an Agent OS adapter for framework lifecycle mediation.

Install¶

pip install agent-governance-toolkit[full]

Create a starter bundle¶

python -m agent_os.cli.cmd_policy_gen \
  --template strict \
  --output policies/
agt lint-policy policies/manifest.yaml

The generated directory contains manifest.yaml and policy.rego. The manifest binds the Rego policy to native intervention points.

Evaluate a tool call¶

from agent_control_specification import AgentControl, HostSession

runtime = AgentControl.from_path("policies/manifest.yaml")
session = HostSession(
    runtime,
    agent_id="quickstart-agent",
    session_id="quickstart-session",
)

evaluation = session.pre_tool_call(
    tool_name="delete_file",
    args={"path": "report.txt"},
)

print(evaluation.verdict)
print(evaluation.reason_code)

Attempted tool calls are charged before evaluation, including denied attempts. The runtime itself remains free of session counters.

Attach a framework¶

from agent_os.integrations.langchain_adapter import LangChainKernel

kernel = LangChainKernel(runtime=runtime)

Every supported adapter receives the native runtime through runtime=. Policy definitions, blocked content, tool catalogs, budgets, transforms, and approval belong in the manifest rather than the adapter constructor.

Handle a denial¶

from agent_os.exceptions import PolicyViolationError

if not evaluation.verdict.decision.permits:
    error = PolicyViolationError.from_evaluation_result(evaluation)
    print(str(error))
    print(error.evaluation_result.audit_record())

The public exception text is sanitized. Trusted code can use the attached PolicyEvaluation for structured audit and dispatch.

Next steps¶