# Ontomcp Driver

> Use OntoSkills MCP tools to discover and apply structured skill knowledge.

- Skill: `mareasw/ontomcp-driver` (Agent Skill)
- Install (CLI): `npx skillmds@latest add mareasw/ontomcp-driver`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mareasw/ontomcp-driver/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: mareasw (https://skillmd.com/u/mareasw)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/mareasw/ontomcp-driver

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## 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

1. Call `prefetch_knowledge` with a query describing the task goal.
2. Read the returned knowledge nodes — they contain procedures, constraints, and anti-patterns.
3. For multi-skill plans: call `evaluate_execution_plan` to validate state chains.
4. 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.