Build a semantic code knowledge graph to resolve definitions and usages.
npx skills add https://github.com/jangtrinh/demo-Lam --skill ck-gkg-jangtrinh
Please help me install this Agent Skill. Skill: ck:gkg Source: https://github.com/jangtrinh/demo-Lam/tree/main/.claude/skills/gkg Command: npx skills add https://github.com/jangtrinh/demo-Lam --skill ck-gkg-jangtrinh
It eliminates the guesswork of figuring out where symbols live and how changes will ripple through a large codebase by building a semantic knowledge graph of definitions and references.
Use case: Before refactoring a frequently used method, index the repository, locate the symbol definition, and retrieve all references to confirm every affected call site across the workspace.
Ask the AI to: index your current Git repository with GitLab Knowledge Graph, start the local server, then find all usages of a given symbol or query by name.
High-intent search queries and answers about installing and using this skill.
Impact analysis works by building a semantic code knowledge graph that resolves definitions and fetches all reference call sites across a repository. This confirms every affected location before modifying a frequently used method.
A semantic code knowledge graph maps definitions and references across a repository to support go-to-definition, find-usages, and architecture visualization. It enables multi-file code understanding by indexing project context into queryable graph endpoints.
You index a Git repository for code navigation by running the GKG CLI or server to process project context. The operation builds a semantic graph and stores the resulting data locally in the ~/.gkg/ directory for querying.
Yes, MCP integration supports go-to-definition queries by leveraging the local GKG server. After indexing the repository, you query the graph search and reference endpoints with project context to quickly locate where symbols are defined.
Yes, semantic code analysis supports architecture visualization by generating an explorable graph view of definitions and references. This architecture-oriented visualization also provides RAG-ready code comprehension for AI assistants.
A limitation of impact analysis using a local code graph is that it requires prior indexing via the GKG CLI or server and stores data strictly in the local ~/.gkg/ directory. The analysis depends entirely on this local indexing step to resolve references.
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