mrsladoje

Sweet Search — AI skill for Claude Code

AI community

Local code search for AI agents: six fast, purpose-built tools that return ranked answers, not raw grep.

How to install Sweet Search

This entry records only its repository, not the path inside it, so there is no exact command to give. Open mrsladoje/sweet-search and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Sweet Search does

Local code search for AI agents: six fast, purpose-built tools that return ranked answers, not raw grep. Because maybe grep isn't all you need... 🍬

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README

**Local code search for AI coding agents.** Six fast, purpose-built tools that hand *Claude Code*, *Codex* & friends ranked answers, not raw grep. Zero API keys, 100% on-device.

*Maybe grep isn't all you need…* 🍬
Every coding agent today reaches for grep + Read by reflex. *sweet-search* challenges the narrative. 😎

[![npm](https://img.shields.io/npm/v/sweet-search?color=cb3837&label=npm)](https://www.npmjs.com/package/sweet-search) [![GitHub stars](https://img.shields.io/github/stars/mrsladoje/sweet-search?style=social)](https://github.com/mrsladoje/sweet-search/stargazers) [![license](https://img.shields.io/badge/license-Apache--2.0-blue)](LICENSE) [![node](https://img.shields.io/badge/node-%E2%89%A518-brightgreen)](package.json) [![platforms](https://img.shields.io/badge/platform-macOS%20%7C%20Linux-lightgrey)](#platform-support) [![inference](https://img.shields.io/badge/inference-100%25%20local-success)](#-gpu-accelerated-indexing-fully-local)

✨ Highlights

Hybrid retrieval — one of the six tools uses BM25F lexical + dense semantic + structural graph signals, fused per query and reranked by late-interaction
Agent-native by design — token-budgeted output tiers, an optional MCP server (and default zero-overhead CLI), and a GEPA-evolved system prompt — one init installs it into Claude Code by default (Codex, Gemini CLI, and Cursor via flags)
Indexed grep, ~10× faster than ripgrep — a sparse n-gram prefilter skips the files that provably can't match
ColBERT-style reranking, locally — per-token MaxSim late interaction on hand-written SIMD kernels
GPU-accelerated indexing — Apple Metal, CUDA, CoreML Neural Engine, or plain CPU via ORT; same engine, auto-selected
Never stale — incremental indexing keeps the index aligned with your working tree, uncom