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auto-model-switcher自动模型切换器

Agent Skill

auto-model-switcher 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

6,240

周安装

250

GitHub Stars

公开资料未说明

下载量

2,020
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-switcher(自动模型切换器)
来源仓库:https://github.com/mrcuo/auto-model-switcher
安装命令:
openclaw skills install auto-model-switcher
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-switcher

简介

auto-model-switcher 用于查找、检索和筛选相关信息,适合在 OpenClaw 中根据关键词快速定位候选结果时使用。

  • 支持根据任务需求自动切换 AI 模型,适用于多模型优化。
  • 通过 clawhub 安装,命令为 openclaw skills install auto-model-switcher,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-switcher
description
Automatically selects the best model based on task type and requirements. Use when: (1) Task requires specific capabilities (coding, analysis, multimodal, writing, research), (2) Need optimal performance/cost balance, (3) Working with long context or complex reasoning.
metadata

Auto Model Switcher

Intelligently selects the optimal model from available providers based on task characteristics.

When to Use

  • Task requires specific capabilities (coding, analysis, multimodal, writing, research)
  • Need optimal performance/cost balance
  • Working with long context or complex reasoning
  • User doesn't specify a model preference

Available Models Analysis

Qwen Series (bailian provider)

ModelContextMultimodalBest ForCost
qwen3.5-plus1M✅ Text+ImageGeneral tasks, creative writing, balanced performanceLow
qwen3-max262K❌ Text onlyComplex reasoning, deep analysis, researchHigh
qwen3-coder-plus1M❌ Text onlyCode generation, debuggingMedium

Third-party Models (bailian provider)

ModelContextMultimodalBest For
glm-51M✅ Text+ImageMultimodal tasks, Chinese optimization
kimi-k2.5200K✅ Text+ImageMultimodal, research-oriented
MiniMax-M2.51M✅ Text+ImageLong context multimodal

Selection Logic

Task Type Detection

Code Tasksbailian/qwen3-coder-plus

  • Keywords: code, programming, debug, fix, implement, develop, coding, script
  • File extensions: .py, .js, .ts, .java, .cpp, etc.
  • Commands: git, npm, docker, build, compile

Complex Analysisbailian/qwen3-max

  • Keywords: analyze, research, compare, evaluate, strategy, deep dive, business analysis
  • Tasks requiring multi-step reasoning
  • Financial/strategic analysis

Research Tasksbailian/qwen3-max

  • Keywords: research, investigate, study, survey, academic, literature review
  • Complex information synthesis
  • Multi-source analysis and comparison

Writing/Copywriting Tasksbailian/qwen3.5-plus

  • Keywords: write, draft, copywriting, content, article, blog, email, proposal, creative
  • Marketing copy, social media content
  • Creative writing and storytelling

Multimodal Tasksbailian/glm-5

  • Image analysis, OCR, visual understanding
  • Audio processing (when supported)
  • Mixed text+image inputs

Long Contextbailian/qwen3.5-plus

  • Document processing > 200K tokens
  • Summarization of large documents
  • Historical context analysis

General Tasksbailian/qwen3.5-plus (default)

  • Chat, simple queries, basic tasks
  • When no specific requirements detected

Fallback Strategy

  1. Primary model selection based on task type
  2. If primary model fails, fallback to qwen3.5-plus
  3. If still failing, use current session model

Usage Examples

Automatic Selection

User: Help me debug this Python code
→ Model: bailian/qwen3-coder-plus

User: Analyze our Q4 financial performance vs competitors  
→ Model: bailian/qwen3-max

User: Research the latest AI trends in marketing
→ Model: bailian/qwen3-max

User: Write a compelling product description for our new service
→ Model: bailian/qwen3.5-plus

User: What's in this image?
→ Model: bailian/glm-5

User: Summarize this 500-page document
→ Model: bailian/qwen3.5-plus

Manual Override

Users can always specify models directly:

  • /model bailian/qwen3-max
  • Use coder model for this task

Implementation Notes

  • Always check if target model is available before switching
  • Preserve current session context when switching
  • Log model selections for learning and optimization
  • Respect user's explicit model preferences

Security Considerations

  • Only switch between pre-configured models in openclaw.json
  • Never attempt to use unconfigured or unknown models
  • Validate model names against available list before switching

Performance Metrics

Track these metrics for continuous improvement:

  • Task completion success rate by model
  • Response time by model and task type
  • User satisfaction feedback
  • Cost per task type

This skill enables intelligent model routing without user intervention while maintaining full control when needed.

Iteration Support

  • Skills can be updated via clawhub sync --all
  • Version updates maintain backward compatibility
  • New task types can be added without breaking existing functionality

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

84.59%
按下载量换算1,709

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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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