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Mistral Codestral
作者
Twin Geeks
· GitHub ↗
· v1.0.2
· MIT-0
135
总下载
0
收藏
2
当前安装
3
版本数
在 OpenClaw 中安装
/install mistral-codestral
功能描述
Mistral and Codestral — run Mistral Large, Mistral-Nemo, Codestral, and Mistral-Small locally. Mistral AI's open-source LLMs for code generation and reasonin...
安全使用建议
This skill appears to do what it says: help you run Mistral/Codestral models locally via an ollama-herd router. Before you proceed: 1) Verify the upstream project (GitHub repo) and the PyPI package 'ollama-herd' authors/versions to ensure you trust the code you will pip install. 2) Run pip installs in a virtualenv or isolated system; inspect package contents if you can. 3) Be aware that running the 'herd' daemon creates a local HTTP service (default port 11435) — ensure it is bound to localhost and protected by your firewall to avoid exposing inference APIs. 4) Model downloads can be very large and will consume disk and network bandwidth; the SKILL.md claims downloads require explicit confirmation but validate that yourself. 5) The SKILL.md metadata references ~/.fleet-manager logs/db — these files may contain usage telemetry; review their contents and permissions. If you want more confidence, ask for the exact pip package metadata (author, homepage, SHA256 of the release) or request a repository snapshot to review the code before installing.
能力评估
Purpose & Capability
The name/description claim local hosting of Mistral/Codestral models; the SKILL.md only asks for curl/wget and optionally python3/pip and shows examples talking to a localhost endpoint (http://localhost:11435). Those requirements are proportional. Minor mismatch: the registry metadata at top lists no required config paths, but the SKILL.md metadata includes configPaths (~/.fleet-manager/latency.db and ~/.fleet-manager/logs/herd.jsonl) — reasonable for a fleet router but inconsistent with the registry summary.
Instruction Scope
Runtime instructions stay within the stated purpose: install ollama-herd via pip, run herd/herd-node, and call a local HTTP API. Commands reference local endpoints and monitoring endpoints. The SKILL.md does not instruct reading unrelated system files or exfiltrating data to external endpoints. It does reference local config/log paths in metadata (see purpose_capability note).
Install Mechanism
There is no registry-level install spec, but the document instructs 'pip install ollama-herd' which pulls code from PyPI (moderate risk compared to no-install). This is expected for this purpose, but pip installs should be treated as untrusted code unless you verify the package source and integrity.
Credentials
The skill requests no environment credentials and only requires common network/CLI tools (curl/wget, optional python/pip), which is proportionate. The metadata's configPaths reference user-local fleet manager DB/logs; while plausible for a fleet router, you should be aware the fleet software may read/write those files and they could contain usage or telemetry data.
Persistence & Privilege
The skill is not forced always-on and is user-invocable; it allows autonomous invocation (the platform default). The main privilege is that running the recommended 'herd' daemon opens a local service (port 11435) to serve models — standard for local inference but worth securing and restricting to localhost/firewalls.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install mistral-codestral - 安装完成后，直接呼叫该 Skill 的名称或使用
/mistral-codestral触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.2
Cross-platform support: macOS, Linux, and Windows. Updated OS metadata, descriptions, and hardware recommendations.
v1.0.1
- Updated documentation (SKILL.md) for improved clarity and emphasis on Mistral AI branding.
- Expanded multilingual and international description for broader audience reach.
- Reorganized setup, usage, and monitoring instructions with more examples focused on Mistral models.
- Added "Contribute" section and clarified guardrails for user safety.
- No changes to functionality; update is documentation only.
v1.0.0
Initial release: Run Mistral and Codestral models across your local fleet with optimized routing.
- Supports Mistral Large, Mistral-Nemo, Codestral, Mistral-Small, and Mistral 7B models.
- Enables code generation (Codestral) trained on 80+ programming languages.
- Routes model requests to the best device in your local network for efficiency.
- Simple OpenAI-compatible API, with endpoints for code, reasoning, image generation, speech-to-text, and embeddings.
- No automatic downloads; all model pulls and deletions require user confirmation.
- Includes web dashboard for monitoring, hardware fit guidance, and comprehensive documentation links.
元数据
常见问题
Mistral Codestral 是什么？
Mistral and Codestral — run Mistral Large, Mistral-Nemo, Codestral, and Mistral-Small locally. Mistral AI's open-source LLMs for code generation and reasonin... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 135 次。
如何安装 Mistral Codestral？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mistral-codestral」即可一键安装，无需额外配置。
Mistral Codestral 是免费的吗？
是的，Mistral Codestral 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Mistral Codestral 支持哪些平台？
Mistral Codestral 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（darwin, linux, windows）。
谁开发了 Mistral Codestral？
由 Twin Geeks（@twinsgeeks）开发并维护，当前版本 v1.0.2。
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