README.md

Agent Control Models

Shared Pydantic models used by the server and SDKs. These models define the API contract for agents, controls, evaluation requests, and responses.

What this package provides

• Strongly typed request/response schemas
• Consistent validation and serialization across server and SDKs
• A single source of truth for model changes

Usage

from agent_control_models import Agent, Step

agent = Agent(agent_name="support-bot", agent_description="Support agent")
step = Step(type="llm", name="chat", input="hello")

Control execution duration

Evaluation responses include an optional top-level execution_duration_ms on each ControlMatch in matches, non_matches, and errors. It measures that control's condition evaluation in wall-clock milliseconds, including the visited condition leaves, evaluator work, and time waiting for an evaluator concurrency slot. Control loading and request/response overhead are outside this measurement.

Completed evaluations include a nonnegative value, including evaluator failures. Precheck failures have no duration, and canceled evaluations produce no result. Older responses without the field remain valid. The Python SDK copies the value to ControlExecutionEvent.execution_duration_ms; the TypeScript SDK exposes it as executionDurationMs.

Tests

cd models
uv run pytest

Full guide: https://docs.agentcontrol.dev/components/models