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ontoly-software-graph【数据与研究】Use Ontoly's deterministic Software Graph and MCP capabilities for repository architecture, request tracing, dependency analysis, configuration lookup, and impact analysis before falling back to source search.
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Use this skill when a coding agent needs graph-backed understanding of a TypeScript repository. Ontoly is the source of truth; the skill only teaches the workflow.
Check whether an Ontoly graph already exists: .ontoly/, SoftwareGraph.json, diagnostics.json, validation reports, graph hash, or MCP setup.
If the graph is missing and local analysis is allowed, run:
ontoly build .
Inspect graph health before answering: diagnostics, graph hash, semantic coverage, trust or quality score, framework detection, and build timestamp.
Prefer Ontoly CLI or MCP capabilities over repository search for graph-answerable questions.
Search source files only when Ontoly cannot answer, the graph is stale or incomplete, or the user explicitly asks for file-level verification.
Always cite graph evidence: node IDs, edge types, file paths, source locations, diagnostics, framework analyzer output, and confidence.
ExplainArchitectureFindDependenciesImpactAnalysisTraceExecutionFindConfigurationUsageFrameworkReportFindDeadCodeReturn the direct answer first, then evidence:
AuthController handles authentication.
Evidence:
- node: class:src/auth/auth.controller.ts:AuthController
- route edges: HANDLES POST /login and POST /logout
- dependency edges: USES AuthService and JwtService
Confidence: high, because the graph has controller, route, and dependency edges with source locations.
NOT_FOUND with the closest graph evidence instead of inventing an answer.