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Analyze large codebases hierarchically and build a queryable knowledge map.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "codebase-rlm" yet — see the docs or source repo.
Use codebase-rlm to analyze this repository hierarchically, build a knowledge map of core modules, call relationships, entry files, and main business flows, then suggest the 10 files a new team member should read first.
A structured codebase knowledge map, module relationship overview, and a beginner-friendly reading path.
Using the codebase-rlm knowledge map, identify which modules, classes, or functions contain the logic for login failure retries and rate limiting, and rank them by relevance.
A ranked list of the most relevant code locations with hierarchical context and relationship notes.
Use codebase-rlm to build a persistent knowledge map for this project and answer: what is the configuration loading flow, how is cache invalidation handled, and which modules are most affected by context window limits?
A persistently queryable project knowledge summary with answers grounded in global codebase context.
Analyze, match, and transform code structures across multiple programming languages.
Index repositories into a persistent graph for fast code search and understanding.
Search code semantically and answer questions about a codebase.
Gives AI coding agents a structural map of your repository fast.
Index codebases into Neo4j for analysis, dependency mapping, and impact assessment.
Analyze code, collect code assets, and generate technical documentation automatically.