CodeScope Q&A

CodeScope indexes source code into a two-layer knowledge graph — structure (functions, calls, imports, classes, modules) and evolution (commits, file changes, function modifications) — plus semantic embeddings for every function. Supports Python, JavaScript/TypeScript, C, and Java (including Hadoop-scale repositories with 8K+ files). This combination enables analyses that grep, LSP, or pure vector search cannot do alone. It can also fetch GitHub issues and trace bugs to code — mapping bug reports to root cause candidates using the graph + vector infrastructure.

When to Use This Skill

• User asks about call chains, callers, callees, or dependencies
• User wants to find dead code, hotspots, or architectural layers
• User asks about code history, who changed what, or why something was modified
• User wants to find semantically similar functions across a codebase
• User wants a full architecture analysis or report
• User asks about module coupling, circular dependencies, or bridge functions
• User wants to index or analyze a Java project (Maven, Gradle, plain Java)
• User wants to analyze GitHub issues or bug reports to find root causes
• User asks "why does this project have so many bugs" or "what code is most buggy"
• User wants to trace a bug report to the most relevant code locations
• A .codegraph directory (or similar index) exists in the workspace

Getting Started