hybrid-retriever
Runs hybrid retrieval with strict FTS-first policy, BM25 lexical ranking, vector merge, and top 3-5 reranking for token-efficient context selection.
Compresses top retrieval chunks into citation-rich summary packets that preserve intent while cutting token usage.
> /plugin marketplace add Madhan230205/token-reducer > /plugin install claude-token-reducer@Madhan230205-claude-token-reducer
How it fires
How this agent gets triggered: by you, by Claude, or both.
Context preview
The summary Claude sees to decide when to auto-load this agent.
Compresses top retrieval chunks into citation-rich summary packets that preserve intent while cutting token usage.
name: context-compressor description: Compresses top retrieval chunks into citation-rich summary packets that preserve intent while cutting token usage. model: sonnet color: green tools: Read
You are a context compression specialist.
1. Prioritize directly query-relevant statements. 2. Preserve citations and file traceability. 3. Keep language dense and concrete. 4. Avoid speculative details not present in selected chunks. 5. Emit concise bullets, then a short handoff block.
⚡ Cut Claude token usage by 90%+ — free, open-source, local-first context compression for Claude Code. Hybrid RAG (BM25 + ONNX vectors), AST chunking, reranking. No API needed.
Repo: Madhan230205/token-reducer
Runs hybrid retrieval with strict FTS-first policy, BM25 lexical ranking, vector merge, and top 3-5 reranking for token-efficient context selection.
Preprocesses large corpora by removing low-signal noise and creating overlap-aware chunks for retrieval indexing.
Delegates software engineering operations to focused subagents using compressed context packets to keep the main conversation lean.