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auto-model-router汽车模型路由器

Agent Skill

auto-model-router 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

12,395

周安装

527

GitHub Stars

1

下载量

4,342
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:auto-model-router(汽车模型路由器)
来源仓库:https://github.com/joyyyced/auto-model-router
安装命令:
openclaw skills install auto-model-router
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install auto-model-router

简介

auto-model-router 用于补充开发相关能力,适合在 OpenClaw 中承接开发任务时使用。

  • 支持根据任务类型自动选择最佳 AI 模型,适用于多模型调度。
  • 通过 clawhub 安装,命令为 openclaw skills install auto-model-router,需结合来源仓库进一步确认具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 当前功能描述基于原始 README,实际能力以官方文档为准。

SKILL.md

name
auto-model-router
description
>
version
0.2.0
metadata
openclaw
requires
bins
env
description
Anthropic API key (for Claude models)
required
false
description
OpenAI API key (for GPT models and embeddings)
required
false
description
DeepSeek API key (for DeepSeek models)
required
false
description
MiniMax API key (for MiniMax models)
required
false
description
Google API key (for Gemini models)
required
false
description
Optional: URL of a self-hosted router service for learning mode (Mode B). If not set, the skill runs fully locally (Mode A).
required
false
description
Optional: API key for the self-hosted router service
required
false
user-invocable
true
emoji
🧠
homepage
https://github.com/JoyyyceD/auto-model-router
privacy
>

Auto Model Router Skill

You have intelligent model routing. For every substantive task, follow this procedure.

Task Categories

Classify tasks into one of these categories:

CategoryWhen to use
codingWriting code, debugging, implementing features, architecture
code_reviewReviewing existing code, security/performance analysis
math_reasoningMath problems, logic puzzles, quantitative analysis
writing_longArticles, reports, essays, long documents
writing_shortTitles, slogans, social posts, short copy
translationTranslating between languages
summarizationSummarizing long texts, meeting notes
data_analysisAnalyzing data, writing SQL, interpreting charts
image_understandingAnalyzing or describing images
daily_chatCasual Q&A, simple questions, general assistance

Procedure

Check whether AUTO_MODEL_ROUTER_URL is set to determine which mode to use.


Mode A — Local (default, no router needed)

Use this when AUTO_MODEL_ROUTER_URL is NOT set.

Step 1 — Classify the task yourself

Read the user's task and determine the best category from the table above. Be decisive — pick one category.

Step 2 — Call the model

python3 ~/.claude/skills/auto-model-router/scripts/call_model.py "<category>" "<user task text>"

Exit codes:

  • 3 — API key missing: tell the user which env var to set
  • 4 — Config not found: tell the user to run python3 scripts/setup.py
  • 5 — No routes configured at all: tell the user to run python3 scripts/setup.py

Step 3 — Present the result

Show the response naturally. Add a subtle footer: _[auto-model-router: used {category} → {model}]_


Mode B — Router (with learning)

Use this when AUTO_MODEL_ROUTER_URL is set.

Privacy note: Task text and an anonymous session ID are sent to the router at AUTO_MODEL_ROUTER_URL. This URL is always set by the user — the skill has no built-in remote endpoint. If the user has not explicitly set this variable, always use Mode A.

Step 1 — Get recommendation

python3 ~/.claude/skills/auto-model-router/scripts/recommend.py "<user task text>" "<USER_ID>"
  • Capture stdout as the model response.
  • Extract TASK_ID from stderr (line starting with TASK_ID=).

Exit codes:

  • 2 — Router offline: fall back to Mode A automatically
  • 3 — API key missing: tell the user which env var to set

Step 2 — Present the result

Same as Mode A Step 3.

Step 3 — Collect feedback

Ask once after presenting the result:

"Was this response helpful? Reply 👍, 👎, or skip."

If 👍:

python3 ~/.claude/skills/auto-model-router/scripts/feedback.py "<TASK_ID>" 1 "<USER_ID>"

If 👎:

python3 ~/.claude/skills/auto-model-router/scripts/feedback.py "<TASK_ID>" -1 "<USER_ID>"

If skip, do nothing.


Changing Model Assignments

When the user says things like "switch to GPT-4o for translation" or "use DeepSeek for coding":

python3 ~/.claude/skills/auto-model-router/scripts/update_route.py <category> <provider> <model>

Examples:

python3 ~/.claude/skills/auto-model-router/scripts/update_route.py translation openai gpt-4o
python3 ~/.claude/skills/auto-model-router/scripts/update_route.py coding deepseek deepseek-chat
python3 ~/.claude/skills/auto-model-router/scripts/update_route.py daily_chat google gemini-2.0-flash

Confirm to the user: "Done, {category} tasks will now use {model}."

First-time Setup

If config is missing, tell the user to run:

python3 ~/.claude/skills/auto-model-router/scripts/setup.py

Manual Invocation

/auto-model-router <your task>

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

78.19%
按下载量换算3,395

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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