Token Reducer: A Claude Code Plugin for Intelligent Context Compression
Token Reducer is a Claude Code plugin that addresses the problem of excessive token consumption when working with medium-to-large repositories. The tool processes repository context locally before sending it to Claude, significantly reducing context size without losing relevant code.
How It Works
The plugin uses several techniques to intelligently compress context:
- AST-based chunking — Parses code into meaningful units (functions, classes, blocks) instead of naive text splitting
- Hybrid retrieval — Combines BM25 (keyword matching) with vector similarity to find the most relevant chunks
- TextRank compression — Applies extractive summarization to keep important parts and drop noise
- Import graph mapping — Traces dependencies so related code stays together
- 2-hop symbol expansion — When working on function A that calls function B, it automatically pulls in B's context
Performance and Testing
In testing across Python, TypeScript, and JavaScript repositories, the developer reports 90-98% reduction in context size without losing code relevant to the task. The tool was built using Claude itself to iterate on the architecture, starting with a basic chunker and testing against real coding tasks until compression was tight but context-preserving.
Installation and Availability
Token Reducer is completely free and MIT licensed. To install:
/plugin marketplace add Madhan230205/token-reducerThe source code is available on GitHub at github.com/Madhan230205/token-reducer. The developer is seeking feedback on where compression helps workflows, cases where important context gets dropped, and which languages or repository structures need better handling.
Technical Details
The plugin runs entirely locally with no cloud APIs and no data leaving your machine. It was packaged as a Claude Code plugin after working reliably on the developer's own projects. The repository is open for contributions, with room to optimize for different languages, add smarter caching, or tune retrieval parameters.
📖 Read the full source: r/ClaudeAI
👀 See Also
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