Ontology-Grounded Agent Compliance Checker

Agent that validates its own tool calls and outputs against a domain ontology before returning results

Difficulty: 1-week | Stack: Python, FastAPI, owlready2, Claude API (tool use), Pydantic, Redis

Who this is for

Enterprise teams deploying agents in regulated domains (finance, healthcare, legal) who need auditable constraint enforcement

Build steps

1. Model a domain ontology in OWL (e.g., financial instruments or medical terms) using owlready2 — define classes, properties, and constraint axioms
2. Build an OntologyValidator middleware layer: intercepts agent tool call arguments and return values, runs consistency check against loaded ontology, returns structured violation report
3. Wrap Claude tool-use agent so every tool invocation passes through validator before execution and every tool result passes through before being added to context
4. Implement violation handling: minor violations → agent self-correction prompt injected; major violations → halt + human escalation flag written to Redis queue
5. Expose FastAPI endpoint /agent/run that accepts task + ontology_id, returns final answer + full audit trail of constraint checks
6. Write 10 test cases: 5 valid paths, 5 that should trigger violations — confirm validator catches all 5

Risks

• OWL reasoning via owlready2 is slow on large ontologies — cache reasoner state or violations become a latency bottleneck
• Ontology coverage gaps mean valid agent actions get flagged as violations — need fast ontology editing workflow baked in from day one
• Claude’s tool call schemas and OWL class hierarchies don’t map cleanly — bridging layer requires careful design or type mismatches silently pass