Skip to main content
The engine is the runtime that evaluates controls, resolves selectors, and runs evaluators. It is used by the server and SDK to apply control logic consistently.

​
Responsibilities

  • Evaluator Discovery: Auto-discover evaluators via Python entry points
  • Selector Evaluation: Extract data from payloads using selector paths
  • Evaluator Execution: Run evaluators against selected data
  • Caching: Cache evaluator instances for performance

​
Evaluator Discovery

The engine provides the public API for evaluator discovery: 
from agent_control_engine import discover_evaluators, list_evaluators

# Discover all evaluators (runs once, safe to call multiple times)
discover_evaluators()

# Get all available evaluators
evaluators = list_evaluators()  # Returns dict[str, EvaluatorClass]

# Access a specific evaluator
regex_evaluator = evaluators.get("regex")
Evaluators are discovered via the agent_control.evaluators entry point group. Discovery:
  1. Scans all installed packages for the entry point
  2. Loads each evaluator class
  3. Checks is_available() to verify dependencies
  4. Registers available evaluators

​
Key Functions

FunctionDescription
discover_evaluators()Scan entry points and register evaluators
list_evaluators()Get all registered evaluators (triggers discovery)
ensure_evaluators_discovered()Ensure discovery has run
get_evaluator_instance(config)Get cached evaluator instance
evaluate_control(control, payload)Evaluate a single control

​
Source Code

View the complete engine source code and implementation: Agent Control Engine