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Every user prompt is analyzed by an in-process BM25 search engine (JavaScript, runs on Bun -- Claude Code's runtime). If high-confidence matches are found (score >= 0.5), they're injected as context before Claude responds. User: \"review my authentication code for security issues\" -> Hook finds: security-auditor (0.89), code-reviewer (0.71) -> Claude sees suggestions in additionalContext -> Loads the best match and follows its instructions No manual search step. Runs in ~100ms. Fails silently on any error -- never blocks the user. The math (140 agents example): Before: 16.4k tokens (all agents loaded) After: 2.7k tokens (registry index loaded, agents on-demand) Savings: 13.7k tokens saved -> 83% reduction","readmeExcerpt":"e what you need (~2-4k tokens) (instant) (~200-300 tokens) Saves 70-90% of agent-related tokens Automatic Discovery (Hook) A UserPromptSubmit hook makes agent discovery fully automatic . 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