What is OntoSkills?
OntoSkills is a complete neuro-symbolic platform for building deterministic, enterprise-grade AI agents. It transforms natural language skill definitions into validated OWL 2 ontologies — queryable knowledge graphs that enable deterministic reasoning.
Why OntoSkills?
The Determinism Problem
LLMs read skills probabilistically. Same query, different results. Long skill files are expensive for large models and confusing for small ones.
- Non-deterministic reading — LLMs interpret text differently each time
- Token waste — Large models burn tokens parsing long documentation
- Small model limits — Complex skills are unreadable by edge models
The Ontological Solution
OntoSkills transforms skills into formal ontologies with Description Logics (OWL 2):
- Deterministic queries — SPARQL returns exact answers, every time
- Entailment reasoning — Infer dependencies, conflicts, capabilities
- Democratized intelligence — Small models query what large models read
Performance Comparison
| Operation | Reading Files | Ontology Query |
|---|---|---|
| Find skill by intent | O(n) text scan | O(1) indexed lookup |
| Check dependencies | Parse each file | Follow dependsOn edges |
| Detect conflicts | Compare all pairs | Single SPARQL query |
For 100 skills: ~500KB text scan → ~1KB query
How It Works
Key Capabilities
| Capability | Description |
|---|---|
| LLM Extraction | Claude extracts structured knowledge from SKILL.md files |
| Knowledge Architecture | Follows the “A is a B that C” definition pattern (genus + differentia) |
| OWL 2 Serialization | Outputs valid OWL 2 ontologies in RDF/Turtle format |
| SHACL Validation | Constitutional gatekeeper ensures logical validity before write |
| State Machines | Skills can define preconditions, postconditions, and failure handlers |
| Security Pipeline | Defense-in-depth: regex patterns + LLM review for malicious content |
Components
| Component | Language | Status | Description |
|---|---|---|---|
| OntoCore | Python | ✅ Ready | Skill core to OWL 2 ontology |
| OntoSkills | Turtle | Generated | Compiled ontology output |
| OntoMCP | Rust | ✅ Ready | MCP server with 12 semantic tools |
| OntoStore | TBD | 🚧 Planned | Versioned skill registry |
| OntoClaw | Python/Rust | 📋 Planned | Enterprise AI agent (future phase) |
| skills/ | Markdown | ✅ Ready | Input skill definitions |
| specs/ | Turtle | ✅ Ready | SHACL shapes constitution |
Get Started
Get Started with OntoSkills in minutes.