LLM Enhancement
Mandatory rules for using Ontoly from LLM-capable agents, MCP clients, and Agent Skills.
LLM Enhancement
LLM Enhancement is mandatory every time Ontoly is used by an LLM.
Ontoly remains deterministic: the compiler, Software Graph, Semantic Index, Query Engine, capabilities, MCP runtime, and Enhancers do not depend on LLM output. LLM Enhancement is the required orchestration layer for LLM-capable clients that consume Ontoly.
Rule
Any LLM-facing Ontoly workflow must:
- Declare or install
LLM Enhancement. - Use Ontoly artifacts, CLI commands, Query Engine results, or MCP capabilities before repository search.
- Cite graph evidence, including node ids, relationship types, source spans, capability name, graph hash, and confidence when available.
- Separate graph facts from inference.
- Mark fallback file inspection explicitly.
- Never claim software understanding from the LLM alone.
Agent Skills
Official Agent Skills declare:
metadata:
ontoly.enhancement: "LLM Enhancement"ontoly skills validate fails when an official skill omits the enhancement,
uses another enhancement value, or fails the LLM Enhancement agent-evaluation
check.
MCP Clients
LLM-capable MCP clients must use Ontoly MCP through an LLM Enhancement workflow. The MCP runtime exposes deterministic graph capabilities; it does not provide LLM reasoning, source parsing, or graph mutation.
Non-LLM tools may call the same MCP capabilities directly, but any LLM that turns those results into user-facing answers must follow LLM Enhancement.
Non-Goals
LLM Enhancement does not add:
- LLM calls
- vector search
- embeddings
- probabilistic graph construction
- repository understanding outside Ontoly evidence
It is a usage contract for LLM consumers, not a new reasoning engine.