Repo · Search & RAG

jev-assist

Don't burn your expensive main model on grep-and-guess grunt work — let jev rank the whole repo, and save the main model for reading the right files…

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From the repository

Don't burn your model's context on a search flood — pipe it in and read above the cut line: one calibrated number per candidate, ~30 rows whether the pool is 40 or 4,000. It doesn't search; it decides what each hit is.

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How builders describe it

Don't burn your expensive main model on grep-and-guess grunt work — let jev rank the whole repo, and save the main model for reading the right files and writing the right code.

A CLI that takes the output of grep, git ls-files or a test run and returns each candidate line with a calibrated score, sorted, with an exact total and a cut line you read above.

The decision Jev makes

Rank candidates against a query, or answer whether a passage is relevant.

Where it fits

Search pipelines retrieve too much. These projects use Jev as a reranker or relevance check after the first search, so only useful results reach the user or the model. All 108 search & rag projects →

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