oss-pr-reviewer

Open Code Review is an open-source, AI-powered command-line code-review tool developed from Alibaba Group’s internal review assistant. It reads Git diffs and sends changed files to a configurable LLM through an agent with tool-use capabilities; the agent can read complete files, search the repository, and inspect other changed files for context before producing structured comments tied to source lines. Its hybrid architecture combines deterministic engineering with dynamic agent decisions: deterministic stages select and bundle files, match rules to file characteristics, and apply independent comment-positioning and reflection modules, while scenario-specific prompts and tools guide context retrieval and review. The `ocr scan` command audits complete files or directories without requiring a meaningful diff, and the project provides multilingual rules for issues including null-pointer exceptions, thread safety, cross-site scripting, and SQL injection. It supports configurable model endpoints, including OpenAI- and Anthropic-compatible endpoints, and requires Git 2.41 or newer.

SlopMonster is a Python linter for detecting formulaic or suspicious AI-generated writing in HTML pages, Markdown, plain text, landing pages, READMEs, emails, and scripts. Its scorer checks AI-associated vocabulary, sentence constructions, punctuation cadence, rule-of-three rhythms, and unsupported sales claims, assigns a score out of 5, and can fail a build when copy scores below 5/5. Its workflow scores the draft, performs a three-pass rewrite that removes suspect vocabulary and sentence shapes and replaces them with specific copy, sends the draft to a different model family for cleansing, and scores the result again. The cleansing script can use a Codex or Claude CLI, refuses to route a draft back to its own model family, and prints a prompt when no supported rival CLI is available. A GitHub Actions workflow is included as a reusable build gate; the scorer itself uses only Python's standard library, while the cleansing step requires an external AI CLI or manual prompt handling. The repository also includes regression tests, a catalogue of detection rules, rewrite principles, and worked before-and-after examples. It is distributed under the MIT license and can also be installed as an agent skill for Claude Code or used by other agents through its plain-Markdown instructions.

Repowise is an open-source, self-hosted codebase-intelligence tool for developers and coding agents. It builds a local index of source code, dependency and symbol relationships, Git history, tests, documentation, architectural decisions, dead code, and code-health signals, then exposes the indexed evidence through an MCP server, local dashboard, CLI, editor integrations, and pull-request analysis. Its graph is built from AST-parsed code and Git data, with confidence-stamped call resolution, change-impact and co-change analysis, hotspot and ownership history, documentation-drift checks, decision evidence, and deterministic code-health detectors. The MCP interface provides task-oriented tools for repository overviews, cited answers, file and symbol context, code search, risk analysis, change risk, architectural rationale, dead-code detection, and health and refactoring plans. Optional model-written documentation and prose can be generated through a configured provider, while the core graph, risk, health, test, and dead-code analysis does not require LLM calls or an API key. Repowise also includes reversible command-output distillation for agents, proactive context hooks, generated agent instruction files, a GitHub PR bot, multi-repository workspace analysis, contract and cross-repository blast-radius mapping, and a VS Code extension. It can be installed with pip and run locally; the repository states that raw source is processed transiently and not persisted, while indexed graph data, embeddings, wiki pages, and Git metadata are stored. The core project is licensed under AGPL-3.0, with commercial licensing available for specified enterprise capabilities and embedding scenarios.

Codex Security is an OpenAI CLI and TypeScript SDK for finding, validating, and fixing security vulnerabilities in authorized code repositories. It scans directories and codebases, including repository changes, uses AI-assisted analysis to trace attack paths and apply custom threat models, validates findings, and can generate reviewable patches and exports in SARIF, JSON, and CSV formats. The CLI supports CI use with an API key and can stop builds at a selected severity threshold. The package also supports configurable deep scans, worker and subagent counts, time limits, containerized bulk scans, and a preview findings service. The service stores findings and embeddings in SQLite, provides paginated listings and a read-only dashboard, identifies potential duplicates through embedding similarity, and allows completed findings to be published and deduplicated through the CLI or SDK. It requires Node.js 22.13.0 or later and Python 3.10 or later, and can use OpenAI or other documented inference providers.

OpenResearch is a local-first workspace for research agents and autoresearch, available as a desktop application and a macOS/Linux CLI. It turns Claude Code, Codex, or OpenCode into agents that can review literature, develop hypotheses, run experiments, and produce research artifacts. The workspace assigns independent agent sessions and isolated Git worktrees to parallel research directions. It tracks experiment variants in a Git-native experiment tree, archives each run against its recorded commit, and keeps logs, diffs, files, results, and artifacts tied to the work that produced them. Its autoresearch loop can propose an idea, modify code, launch an experiment, inspect evidence, and choose the next direction. The same committed source snapshot can run locally or through SSH, Slurm, Kubernetes, Ray, Hugging Face Jobs, Modal, Tinker, or managed OpenResearch compute. By default, projects and run data remain on the user's machine in a local SQLite store, with a browser dashboard served on localhost. An OpenResearch account is used for service-owned capabilities such as organizations and managed compute. The CLI also installs an OpenResearch skill into supported coding agents and provides commands for projects, runs, logs, experiments, discovery, and paper lookup.