jevgrep

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图片：jevgrep — Find the context. Start coding.

jevgrep

图片：npm 图片：MIT license 图片：Node.js 22+ 图片：Release

Find code by asking what it does.

Coding agents spend part of every unfamiliar task finding the right files. Jevgrep gives them a place to start: ask a repository question, and jg returns relevant files, reading leads, and verbatim source excerpts in one stdout response. It uses Jev to judge relevance across folders, files, and declarations. Your coding agent then implements and tests the change.

npm install -g @dzhng/jevgrep
jg auth
jg skill
jg "How are telemetry events recorded and sent?" ./my-project

Requires Node.js 22+, macOS or Linux, and a key for Vercel AI Gateway, TypeSafe, or OpenRouter. No separate Python, Bun, or ripgrep installation is required to use jg.

Provider selection requires 0.3.0 or newer. Upgrade an older installation with npm install --global @dzhng/jevgrep@latest.

Install the agent skill — required for agent setup

Installing the CLI alone does not teach your coding agent to use it. Install the skill as well, from the project where your agent works:

jg skill

The installer detects your coding agents (Claude Code, Codex, OpenCode and others) and asks where to install. Add --global for a user-wide install, or --yes for unattended installation. The skill teaches the agent when to call jg, how to use returned context, and when to fill gaps with its normal tools. It skips redundant retrieval when the needed context is already known. The current repository skill checks for jg and installs the CLI if it is missing; authentication still needs your selected provider’s key. The skill installer itself does not configure credentials.

jg skill delegates to the skills CLI and needs npm/npx plus network access. You can also run that installer directly, without the CLI installed:

npx skills add dzhng/jevgrep --skill jevgrep

In 0.1.0, jg skill only prints the bundled skill; use npx skills with that version.

Upgrade

There is currently no jg upgrade command. Upgrade the CLI with npm:

npm install -g @dzhng/jevgrep@latest
jg --version

Update the installed skill separately by rerunning jg skill. Updating the npm package does not overwrite skill files in your projects. See the package guide for authentication details.

Start with a question, leave with source

Use jg when you know the behavior you need to understand but not where it lives:

jg "Where is authentication checked before a request reaches a handler?" .
jg "How are database connections created, pooled, and closed?" ./src
jg "Which tests cover retry behavior when a request times out?" .

Jevgrep explores the repository hierarchy and follows qualifying branches. It selects files using content previews, then identifies useful source units and surrounding context. It keeps qualifying file locations even when it cannot confidently return an excerpt; it does not force every search into a fixed top-two list.

The summary comes first, followed by file locations, reading leads, and selected source with line references. Python and TypeScript/JavaScript support declaration parsing; other text uses a fallback. The output is evidence for the agent to use, not a generated answer or a guarantee that every relevant file was found. See a recorded output example.

When you already know an exact symbol or path, a direct read or rg search may be all you need. Jevgrep is most useful for questions that span unfamiliar files.

What we measured

图片：Jevgrep workflow and benchmark: 40% lower Sol task cost in one ten-task SWE-bench repeat, with 7/10 solves versus 8/10 baseline. Jev cost excluded.

About 40% lower coding-agent cost in one ten-task SWE-bench repeat. Full Sol cost fell from $7.62 to $4.52, including failed tasks and excluding Jev costs. Solve rate was 7/10 with jg, versus 8/10 for the saved baseline. This is a cost reduction with a quality tradeoff, not evidence of equal or better solve quality.

The earlier run of the same corrected runtime solved 6/10 at $5.54. Both runs remain separate; baselines were run once and reused, and outcomes were never pooled. Both failed the original quality gate. The sample is a tuned Python subset evaluated with Sol, so it does not establish general savings, faster execution, or results for other coding agents.

The full results and paired trace analysis include exact costs, failed tasks, and separately observed Jev charges. See the evaluation guide for methodology.

Source, credentials, and local state

Searches send eligible source content to Jev through the provider selected during auth. Default filesystem filtering respects ignore files and excludes hidden, dependency/build, binary, and obvious credential files. These filters are not a guarantee that all sensitive information has been removed; choose a search root you intend to send.

jg auth asks for your provider, then saves its key in an owner-only config file. Re-running auth replaces that setup; searches always use the saved provider. jg doctor checks it with synthetic input. Existing saved keys without a provider remain Vercel keys. Environment-based credentials and endpoint overrides are not used; run jg auth if you previously relied on them. Evaluation answers are cached locally by default. The CLI writes its output to stdout and does not create report files. Use jg --help for cache controls, search overrides, and incomplete-result behavior.

Development

The repository uses TypeScript, Bun workspaces, and Turborepo. From a checkout:

bun install --frozen-lockfile
bun run dev --help
bun run verify

Verification includes Docker tests of the installed Node-only package. For the reasoning behind retrieval, parsing, caching, and failure handling, start with the architecture and implementation record. Release guidance covers tag-triggered npm publication and verification of the exact public package.

MIT. Artwork and generation prompts.