villani-code

作者 mmprotest已验证

Some tools help. Some tools assist. Villani Code intervenes.

114
Stars
16
Forks
Python
语言
2026/8/23
添加时间

⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/mmprotest/villani-code

快速入门

使用 villani-code 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

Villani Code

Flagship coding-agent performance from small local models.

Villani Code is a local-first coding-agent runtime designed to make smaller open models do real repository work: navigate files, run commands, make patches, survive verification, and keep working through messy terminal environments.

The thesis is simple: small models do not just need better weights. They need a better runtime.

Terminal-Bench 2.0: Qwen3.6 27B full-suite run

Villani Code achieved a 196/445 lower-bound score on the full Terminal-Bench 2.0 suite using Qwen3.6 27B.

That is 44.0% across 89 tasks with 5 attempts per task.

Villani Code: Flagship performance from small local models

Headline result

SystemModelTerminal-Bench 2.0 accuracy
Codex CLIGPT-5-Codex44.3%
Villani CodeQwen3.6 27B44.0%
Mini-SWE-AgentGPT-5-Codex41.3%
Claude CodeClaude Sonnet 4.540.1%
Dakou AgentQwen 3 Coder 480B27.2%
little-coderQwen3.6-35B-A3B24.6%
Bash AgentTermiGen-32B19.3%
little-coderQwen3.5-9B9.2%

Villani Code lands within 0.3 percentage points of Codex CLI + GPT-5-Codex and ahead of Claude Code + Claude Sonnet 4.5, while running a much smaller local Qwen model.

Full report

The full visual report is available here:

Villani Code Terminal-Bench 2.0 Qwen3.6 27B Report

Run status: self-run lower-bound benchmark result, not yet Terminal-Bench team verified.

Why this matters

Most coding-agent performance is attributed to the foundation model.

Villani Code shows the runtime can move the frontier too.

The runner matters. Tool handling matters. Failure recovery matters. State management matters. The execution loop matters. The boring engineering around the model matters.

A smaller local model should not be dismissed as weak just because it is small. In the right runtime, it can perform in the same band as much larger flagship coding-agent stacks.

Qwen3.5 9B same-model runtime comparison

Villani Code was also tested against Claude Code using the same model: Qwen3.5 9B.

Same model. Same tasks. Different agent runtime.

Villani Code won.

Claude Code vs Villani Code

RunnerScoreSuccess rate
Villani Code + Qwen3.5 9B38/6063.3%
Claude Code + Qwen3.5 9B26/6043.3%

Villani Code delivered a 46% relative performance improvement over Claude Code.

This comparison covers 12 overlapping Terminal-Bench tasks, with 5 runs per task, for 60 runs per agent.

Villani Code won 6 tasks, tied 6 tasks, and lost 0.

What Villani Code is

Villani Code is a terminal-first coding agent for:

  • bounded bug fixes
  • repo navigation and localization
  • command-driven debugging
  • test-guided patching
  • local inference setups
  • privacy-sensitive codebases
  • smaller open model backends

It is built for the environment where most coding agents start to fall apart: smaller models, hard verification, constrained context, terminal noise, failed commands, and real repositories.

What changed in the upgraded runtime

The latest Villani Code upgrade includes:

  • new execution loop
  • better local model integration
  • cleaner tool handling
  • improved failure recovery
  • task-scoped memory system
  • better state tracking across long-running coding tasks

The benchmark comparison evaluates the upgraded runtime as a whole.

Quickstart

Install with TUI support:

pip install .[tui]

Headless CLI only:

pip install .

Development dependencies:

pip install .[dev]

Interactive session:

villani-code interactive --base-url http://127.0.0.1:1234 --model your-model --repo /path/to/repo

One-shot task:

villani-code run "Add retry handling to API client and update tests." --base-url http://127.0.0.1:1234 --model your-model --repo /path/to/repo

Autonomous pass:

villani-code --villani-mode --base-url http://127.0.0.1:1234 --model your-model --repo /path/to/repo

Use Villani Code in Pi

@mmprotest/pi-villani

Install with:

pi install npm:@mmprotest/pi-villani

Provides /villani <task>.

Runtime version: v0.1.5.

Pi Usage

Run Villani with /villani <task>. Active runs are still cleaned up automatically on process/session cancellation or error cleanup.

Reports

常见问题

What is villani-code?

villani-code is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by mmprotest. Some tools help. Some tools assist. Villani Code intervenes. It has 114 GitHub stars.

Is villani-code safe to use?

Yes. villani-code passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install villani-code?

Clone the repository with "git clone https://github.com/mmprotest/villani-code" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is villani-code written in?

villani-code is primarily written in Python. It is open-source under mmprotest on GitHub, so you can review or fork the full source.

Are there alternatives to villani-code?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh villani-code against similar tools.

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