Agent Policy & Guardrails Engine#

Use This Skill When#

• You need to add or change policy enforcement behavior.
• You need to add policy types (financial, privacy, communication, operational, approval, time-based).
• You need to extend decision outputs ( ALLOW, DENY, MODIFY, REQUIRE_APPROVAL).
• You need to update APIs, persistence, or audit logging.

Project Layout#

• app/main.py: FastAPI endpoints.
• app/service.py: orchestration for policy CRUD + evaluation + audit writes.
• app/engine.py: core policy evaluation and conflict resolution.
• app/policy_parser.py: JSON/YAML/NL policy parsing into structured definitions.
• app/schemas.py: request/response and policy schemas.
• app/models.py: SQLAlchemy models ( policies, audit_logs).
• app/seed.py: baseline policies.
• tests/test_api.py: API-level behavior.
• tests/test_engine.py: decision logic behavior.

Standard Workflow#

1. Implement schema/model changes first if policy structure changes.
2. Update parser and engine evaluation paths.
3. Update API/service layer only as needed.
4. Add or update tests for both engine and API.
5. Run tests before finalizing.

Commands#

Install and test:

bash

python3 -m pip install -r requirements.txt
python3 -m pytest

Run locally:

bash

python3 -m uvicorn app.main:app --reload

Enforcement Contract#

All external agent/tool actions must be sent to POST /evaluate before execution.

Runtime handling expectations:

• DENY: block execution.
• REQUIRE_APPROVAL: pause and require explicit human approval.
• MODIFY: apply returned modifications, then execute.
• ALLOW: execute.

Conflict Resolution Rules#

When multiple policies match the same action:

1. Highest priority wins.
2. If tied on priority, effect severity wins: DENY > REQUIRE_APPROVAL > MODIFY > ALLOW.

Adding New Guardrails#

1. Add a structured policy in app/seed.py (optional baseline).
2. Ensure action_types and conditions map to real runtime payload fields.
3. Add API test coverage in tests/test_api.py using /evaluate.
4. Add engine-level tests in tests/test_engine.py for edge/conflict cases.

Notes#

• Keep policy evaluation deterministic.
• Prefer structured JSON/YAML policies for complex controls.
• Natural-language rules should compile into the same structured policy schema.