code-chunker

To get a structural overview of a large source file, you can generate a navigable map that parses the code to identify top-level declarations like functions and classes. This produces a table of contents with section names, line ranges, and summaries for quick navigation.

Yes, code structure analysis can be output as JSON or tree views. The parser supports multiple output formats, allowing you to choose the structure representation that best fits your development workflow or downstream tooling requirements.

The best way to help an agent navigate unfamiliar code files is to provide a structured map of the file's logical sections. This prevents wasted context window space by allowing the agent to quickly locate and process specific methods or classes instead of loading the entire file.

Yes, this code chunking tool caches generated maps for session reuse. Caching the navigable structure maps allows repeated access to the same source files without needing to reparse the code, speeding up development cycles.

You need to analyze file structure for logical sections and line ranges when refactoring large or unfamiliar files. Generating a map of top-level declarations allows you to focus on specific methods or classes without reading the entire file, saving context and time.

Parsing source files to generate a navigable map focuses on identifying top-level declarations and grouping them into logical sections. Limitations may arise with highly dynamic or non-standard file structures that prevent clear static analysis of line ranges and section summaries.