tool-prune: prune 50+ tool schemas down to candidates in 0.4ms (-92% prompt tokens, zero deps)

Reddit r/LocalLLaMA Tools
tool-prune pruning prompt-optimization local-llm developer-tools

Summary

tool-prune is a tool that prunes tool schemas before calling local LLM models, reducing prompt tokens by 92% and avoiding hallucinations with no extra LLM round-trips.

When running local 7B/8B models with tools, 50+ schemas in context degrades attention and causes distractor hallucinations. Using in-band progressive search (tool_search) costs an entire extra LLM generation turn (+2s), and small models frequently forget to call the search tool or get stuck in discovery loops. tool-prune runs pre-flight in the client before the model is called: const topTools = await router.filter(userPrompt); 0 extra LLM round-trips 0.4ms offline via FWHT (pure JS & Python, 23µs with SIMD) -92% prompt tokens Direct dispatch option for deterministic queries in <1ms Zero external dependencies Playground: https://hemanth.github.io/tool-prune/ GitHub: https://github.com/hemanth/tool-prune
Original Article

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