| name | ontomcp-driver |
| description | Use OntoSkills MCP tools to discover and apply structured skill knowledge. |
Tools
- prefetch_knowledge — One call: search + fetch context + compact. Use this first.
- search — Find skills by keyword, alias, or structured filters.
- get_skill_context — Full skill context with knowledge nodes (procedures, constraints, anti-patterns).
- evaluate_execution_plan — Validate a multi-skill plan against state chains.
- query_epistemic_rules — Cross-skill knowledge rules filtered by kind/severity.
Responses are compact by default. Use format: "raw" for full JSON.
Workflow
- Call
prefetch_knowledge with a query describing the task goal.
- Read the returned knowledge nodes — they contain procedures, constraints, and anti-patterns.
- For multi-skill plans: call
evaluate_execution_plan to validate state chains.
- Write code following the knowledge nodes.
Critical rules
- Always prefetch first — don't guess skill names.
- CRITICAL/HIGH severity nodes are hard constraints — never skip them.
- Check requiresState — skills fail without their preconditions.
State semantics
Skills form a state machine: requiresState (preconditions) / yieldsState (outcomes).
Skill A's yieldsState must match Skill B's requiresState for valid chaining.
