ToolDescriptionsearch_corpus(query)Hybrid BM25 + dense vector search via reciprocal rank fusion (RRF) over a Chroma collection. 50 candidates are retrieved, and then reranked. The top results are returned within a token budget.grep_corpus(pattern)Regex search over the corpus. Returns up to 5 matching chunks.read_document(doc_id)Read the full content of a document by ID. Chunks are reranked and truncated to fit the remaining token budgetprune_chunks(chunk_ids)Removes specified chunks from the conversation contextThe search_corpus tool queries both sparse vectors and dense embeddings in each Chroma collection. A search issues both queries in parallel, and the results are fused via reciprocal rank fusion (RRF) to combine the strengths of keyword and semantic matching. The top 50 fused results are scored by a reranker, which selects the top results within a per-call token budget.
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as mentioned in the previous post, the F# version gets a lot of its speed from .NET’s SIMD infrastructure - SearchValues<T, Teddy multi-string search, right-to-left vectorized scanning. the rust version doesn’t have any of that yet, so it’s not going to win on literal-heavy patterns. but where the DFA loop dominates and there’s less reliance on vectorized prefilters, it holds up well:
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