Jev Review

Jevgrep is a command-line tool for coding agents that finds relevant files and source context in unfamiliar repositories from natural-language questions. It uses Jev to judge relevance across folders, files, and declarations, explores qualifying branches of the repository hierarchy, selects files through content previews, identifies useful source units and surrounding context, and returns a summary followed by file locations, reading leads, and verbatim excerpts with line references. Python and TypeScript/JavaScript support declaration parsing, while other text uses a fallback. It also includes an agent skill that teaches supported coding agents when to invoke the CLI and how to use its results. The CLI is distributed through npm as @dzhng/jevgrep, requires Node.js 22 or later on macOS or Linux, and requires authentication with a supported AI provider. Searches send eligible source content to Jev through the selected provider; local filtering excludes ignored, hidden, dependency/build, binary, and obvious credential files but is not a guarantee that sensitive data is removed. The project is MIT-licensed.

CodeJury is a terminal-first, knowledge-grounded multi-agent software delivery pipeline for scoping requirements, implementing changes, running tests, and gating pull requests. It divides delivery into six terminal-driven stages and uses isolated development branches, human approval gates, deterministic QA, and ensemble code review. The system indexes a repository into a persistent code graph and uses semantic search to retrieve relevant code during later work. Its review stage sends the same change to independent models from different providers; both must approve it for the change to pass, while a rejection returns the reason to the developer. A configurable panel can use up to six specialist reviewers and a foreperson to reconcile their findings. The project is distributed as a Python package installable with pip and documents support for macOS, Linux, and Windows. Its repository describes a one-command run and operation without an API key.

Jevmind is a Python decision layer for software agents. It turns agent decisions into typed answers such as yes/no results, choices, and scores with confidence values, then applies a code-defined gate: uncertain answers escalate, trusted positive answers may act, and trusted negative answers are held. Its decisions are recorded in an append-only, hash-chained ledger, graded against later outcomes, and optionally recalibrated with Platt scaling. It includes nine skills for compacting tool output, navigating repositories, reviewing diffs, routing tasks to model tiers, checking completion claims, curating training data, walking linked markdown vaults, guarding commands, and running a structured-state control-loop demo. The default local brain uses readable rules, reflexes, and BM25 retrieval without a language model; an optional Jev HTTP brain can answer the same typed questions, while replay mode uses recorded answers. Jevmind runs as a command-line tool and MCP server, includes a Claude Code hook for shell-command screening, supports Python 3.10+, has no runtime dependencies, and is distributed under the MIT license.

fast-jev-compaction is an npm library and Claude Code plugin that compacts tool-call history without rewriting the original text. It pairs each tool call with its result, sends the conversation state and questions about each non-pinned call to Jev, and then keeps the call and result, keeps only the call while truncating the result, or removes both according to Jev's scores. Recent messages and the first message are pinned; state fitting progressively truncates inputs, abridges long text, collapses older messages, and reduces old tool calls to one-line records so requests fit within configured token estimates. User and assistant text is never removed or shortened in the returned transcript, and retained content stays verbatim. The package exposes compaction, decision, batching, state-fitting, and transport-building functions, while the Claude Code hook replaces built-in compaction and falls back to Claude Code's summary when Jev fails or reduction is insufficient. It uses the TypeSafe API by default and requires a TypeSafe API key.

Code Review Graph is an open-source, local-first code intelligence tool that provides a command-line interface and MCP server. It builds a persistent structural map of a codebase with Tree-sitter, representing relationships such as functions, classes, imports, calls, inheritance, and test coverage, while tracking changes incrementally. The graph supplies focused repository context to AI coding tools so they can read relevant code instead of repeatedly scanning large portions of a project. It also supports code-review workflows such as blast-radius analysis and risk-scored pull-request reviews. The Python package can be installed with pip or pipx; its install command detects supported AI coding platforms and configures MCP settings, hooks, skills, and graph-aware instructions.