Catch AI-written code that doesn't fit your repo — foreign deps, reinvented functions, gamed tests — learned from your git history. 100% local, no LLM.
git clone https://github.com/get-tmonier/argot && cp argot/*.md ~/.claude/agents/Subagents overview
<p align="center"> <img src="docs/argot-logo.svg" alt="argot" width="200" /> </p> <p align="center"> <strong>Review changes against the patterns your repository has already accepted.</strong><br/> <em>argot surfaces repository-grounded divergence; you decide what to accept.</em> </p> <p align="center"> <a href="https://argot.tmonier.com"><strong>argot.tmonier.com</strong></a> · <a href="https://argot.tmonier.com/docs/">Documentation</a> · <a href="https://argot.tmonier.com/benchmarks">Evidence</a> · <a href="docs/research/README.md">Research log</a> </p> <p align="center"> <a href="https://github.com/get-tmonier/argot/releases/latest"><img src="https://img.shields.io/github/v/release/get-tmonier/argot?color=E67E45" alt="Release" /></a> <a href="https://www.npmjs.com/package/@tmonier/argot"><img src="https://img.shields.io/npm/v/@tmonier/argot?logo=npm" alt="npm" /></a> <a href="https://github.com/get-tmonier/argot/actions/workflows/ci.yml"><img src="https://github.com/get-tmonier/argot/actions/workflows/ci.yml/badge.svg" alt="CI" /></a> <a href="https://github.com/get-tmonier/argot/blob/main/LICENSE"><img src="https://img.shields.io/github/license/get-tmonier/argot?color=E67E45" alt="License" /></a> </p> ## Start with an audit `argot audit` needs no prior Argot fit or configuration. It fits a historical base in a temporary worktree, then evaluates the surviving base-to-HEAD net diff. Your working tree is left untouched. It is a review prompt—not a census of who wrote code, or proof that a finding is a defect. ```sh # macOS / Linux curl --proto '=https' --tlsv1.2 -LsSf https://github.com/get-tmonier/argot/releases/latest/download/argot-installer.sh | sh cd your-repository argot audit ``` Windows: `powershell -c "irm https://github.com/get-tmonier/argot/releases/latest/download/argot-installer.ps1 | iex"`. The npm package is also available as `npm install -g @tmonier/argot`. Audit needs usable Git history and supported source. It has no fixed runtime promise. Semantic analysis may download a local code-embedding model once; see [Getting started](https://argot.tmonier.com/docs/getting-started/) for install, offline, and fit details. If the audit gives you a useful lead, fit the current repository and score the changes you intend to review: ```sh argot init argot check ``` `check` reports configured findings on the selected changeset; a clean result does not prove the change correct or fully idiomatic. Read the [Audit](https://argot.tmonier.com/docs/audit/), [Init and Fit](https://argot.tmonier.com/docs/init-and-fit/), and [Check](https://argot.tmonier.com/docs/check/) guides for the exact contracts. ## What it surfaces argot is a probabilistic review guardrail, not a correctness oracle. Its current detector composition can surface a foreign dependency/API/idiom, a function that duplicates one already present, code placed away from its peers, an internal import that reverses a learned direction, or a test weakened, disabled, or deleted alongside the production change it covers. Repositories can also add their own versioned scripted rules. Each finding carries repository evidence. Treat it as a prompt to inspect and make the human decision explicit—never as proof that the code is wrong. ## Choose how to run it The CLI is the complete, explicit changeset check. Other routes have narrower triggers and coverage; none provides a universal acceptance-time check. | Route | Execution class | Prerequisites and coverage | Evidence status | | ------------------ | -------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- | | CLI | Invoked by a user or agent | Run `audit`, `init`, or the full `check`; fitting is required where the command needs it. | CLI/source inventory, 2026-07-22 | | Skills | Invoked | Six on-demand workflows for a compatible skill host; installation does not schedule commands, configure MCP, or add a hook. | Manifest/source inventory, 2026-07-22 | | MCP | Passive | A configured client selects read-only context/check tools; a fitted repository is required for model-dependent tools. Use the CLI for a complete changeset check. | Focused test and source inspection, 2026-07-22 | | Claude Code plugin | Automatic when configured, plus invoked/passive surfaces | Its opt-in pre-write hook, in a fitted repository, asks only when a `Write`, `Edit`, or `MultiEdit` introduces a foreign import. It never blocks and is not a full or end-of-turn check. | Manifest/source inspection, 2026-07-22 | | pre-commit | Automatic when user-configured | Scores staged supported files in a fitted repository. The `argot-check` hook is advisory for findings; `argot-check-gate` is opt-in for error-severity exits. | Manifest inspection, 2026-07-22 | | GitHub Action | Automatic when user-configured | Scores the configured ref/range in a workflow; it needs checkout history and release-download access. `fail-on-hits` defaults to `false`. | Action manifest inspection, 2026-07-22 | Canonical setup and host details: [Claude Code](https://argot.tmonier.com/docs/plugin/), [other agents and MCP](https://argot.tmonier.com/docs/agents/), and [CI and pre-commit](https://argot.tmonier.com/docs/ci/). ## Evidence and limits Current public measurements are detector-specific, not a product-wide accuracy or combined-brief claim. The [approved claim manifest](landing/src/data/claims/manifest.json) records: - visible foreign-symbol fixtures: **595/605** across 22 corpora; - layering fixtures: **264/272** across 25 corpora and 12 languages; - test-integrity fixtures: **155/164** across 23 corpora and 12 languages. Each number has a distinct corpus, denominator, and qualifier. The combined briefing/noise result, semantic aggregate, and ordinary-repository timing are not yet measured public claims. See the [benchmark methodology and sources](https://argot.tmonier.com/benchmarks). Argot ships adapters for 12 languages. The five tested release targets are macOS arm64/x64, Linux x64/arm64, and Windows x64. The local analysis path uses statistical, graph, scripted, and embedding evidence; no generative or opinion-forming model decides a finding. Fit health matters. A repository with shallow, generated, vendored, or otherwise unsuitable history may not produce a useful model. Argot is also least reliable for an incorrect choice made entirely with familiar vocabulary, masked prose, and code outside the selected range. Read [Limitations](https://argot.tmonier.com/docs/limitations/) before relying on a specific detector. ## Reproducible authored proof  This is an **authored fixture**, not a wild-case corpus. Its pinned command, version, receipts, checksums, regeneration procedure, and the visual’s non-byte-stable GIF qualification are documented in [the proof receipt](docs/demo/proof/README.md). The image is a reproducible companion to the [auditable Markdown receipt](docs/demo/proof/audit.md). ## Privacy and open source Argot analyzes source, history, and findings locally. The individual local core is free, MIT-licensed open source, and requires no account or cloud service. Argot has no default telemetry and does not upload source code. It can still use network paths for a one-time local model download, update/version checks, release downloads, or an explicitly configured review/update/CI integration. Set `ARGOT_OFFLINE=1` to prevent network use; semantic checks without a cached model are then skipped with a diagnostic while other checks continue. Read the complete [privacy and security boundary](https://argot.tmonier.com/privacy/), [security policy](SECURITY.md), and [MIT license](LICENSE). ## Contribute Contributions are welcome. Start with [CONTRIBUTING.md](CONTRIBUTING.md), then see the [product strategy](docs/strategy/ARGOT_STRATEGY.md) for the maintained decision record and [research log](docs/research/README.md) for evidence.
What people ask about argot
What is get-tmonier/argot?
+
get-tmonier/argot is subagents for the Claude AI ecosystem. Catch AI-written code that doesn't fit your repo — foreign deps, reinvented functions, gamed tests — learned from your git history. 100% local, no LLM. It has 9 GitHub stars and was last updated today.
How do I install argot?
+
You can install argot by cloning the repository (https://github.com/get-tmonier/argot) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is get-tmonier/argot safe to use?
+
get-tmonier/argot has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.
Who maintains get-tmonier/argot?
+
get-tmonier/argot is maintained by get-tmonier. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to argot?
+
Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.
Deploy argot to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/get-tmonier-argot)<a href="https://claudewave.com/repo/get-tmonier-argot"><img src="https://claudewave.com/api/badge/get-tmonier-argot" alt="Featured on ClaudeWave: get-tmonier/argot" width="320" height="64" /></a>More Subagents
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
The agent that grows with you
Java 面试 & 后端通用面试指南,覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
The agent engineering platform.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.