Policy APIs

Policy APIs make tool selection and action execution inspectable, enforceable, and replayable.

Endpoints

POST /v1/memory/rules/evaluatePOST /v1/memory/tools/selectPOST /v1/memory/tools/decisionPOST /v1/memory/tools/runPOST /v1/memory/tools/feedback

Typical sequence

1. Evaluate rules with normalized runtime context.
2. Select candidate tools under policy constraints.
3. Persist decision and run linkage.
4. Submit feedback for closed-loop learning.

What each endpoint does

1. rules/evaluate returns policy matches for the current context.
2. tools/select narrows tool candidates under active rules.
3. tools/decision persists the chosen decision and provenance.
4. tools/run links execution to the prior decision.
5. tools/feedback records whether the outcome was useful or needs adjustment.

Required IDs

1. run_id
2. decision_id
3. request_id

Minimal evaluate request

curl -sS "$BASE_URL/v1/memory/rules/evaluate" \
  -H 'content-type: application/json' \
  -d '{"tenant_id":"default","scope":"default","run_id":"run_001","context":{"intent":"support_triage"}}' | jq

Example response (rules/evaluate, trimmed)

{
  "status": "ok",
  "request_id": "req_rules_001",
  "tenant_id": "default",
  "scope": "default",
  "data": {
    "matched": [],
    "applied": []
  }
}

Tool selection request skeleton

{
  "tenant_id": "default",
  "scope": "default",
  "run_id": "run_001",
  "context": {
    "intent": "support_triage",
    "tool": { "name": "ticket_router" }
  },
  "candidates": ["ticket_router", "email_sender"]
}

Error example and fix

Example error:

{
  "error": "invalid_request",
  "message": "run_id is required for policy flow"
}

Fix:

1. Ensure the same run_id is passed across evaluate/select/decision/feedback.
2. Send normalized context with stable keys.
3. Validate required payload shape before request submission.

Production guidance

1. Normalize context keys before they reach Aionis.
2. Reuse one run_id for the full agent execution, not per tool call.
3. Persist decision_id immediately after selection or decision recording.
4. Feed outcome quality back into tools/feedback if you expect policy tuning to improve over time.