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in the next version of OpenCode, file search is powered by fff - files the agent opens start ranking higher - tool calls reuse the same search layer instead of starting cold - less wasted context - fast af here’s me searching around the linux repo, a ~40m line codebase

nexxel

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254,297 次观看 • 5 个月前 •via X (Twitter)

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AI coding agents re-explore the same codebase every single session. Repowise indexes a repo once and gives Claude Code, Codex, or any MCP agent a real dependency graph, git history, and a bug-predictive code health score. No re-grepping the same files. No stale docs. No guessing which file is about to break. The loop is simple: measure every file > locate where the risk concentrates > generate the exact refactoring plan to fix it Indexing a repo takes under 30 seconds and updates automatically on every commit. Paired benchmarks show up to 96% fewer tokens spent loading context and 70% fewer agent tool calls, at the same answer quality.

AI coding agents re-explore the same codebase every single session. Repowise indexes a repo once and gives Claude Code, Codex, or any MCP agent a real dependency graph, git history, and a bug-predictive code health score. No re-grepping the same files. No stale docs. No guessing which file is about to break. The loop is simple: measure every file > locate where the risk concentrates > generate the exact refactoring plan to fix it Indexing a repo takes under 30 seconds and updates automatically on every commit. Paired benchmarks show up to 96% fewer tokens spent loading context and 70% fewer agent tool calls, at the same answer quality.

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The most exciting thing that I've been working on lately in the file search field is the GPU acceleration of file search. You might think that I'm dumb or something, but it is a real next step. fff is already on the edge of what is possible on CPU, but our design with the storage is actually oriented on the embarrassingly parallel search, which couldn't be more effective than on GPU. If you'd think about this deeper: 99% of the time file search happens on the local machine of the user. Your melting macbook pro that is using precious CPU cycles to build your Rust project right now is getting wasted on the smart typo-resistant fuzzy matching which is a quadratic complexity algorithm that needs more resources the longer your query is. What if we use GPU instead? Cause we already have it and it is likely idle if user is typing into a search box. And honestly there are some good results so far. I was able to bring fff down to 20% cpu usage at all times no matter how absurdly long your queries are and no matter how many files you have Here is a little sneak peak. Running on M4 max 1.6TB home dir

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