Skill: mrcuo/auto-model-switcher (version 1.1.0)

--- 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: { "openclaw": { "emoji": "🤖", "homepage": "https://github.com/mrcuo/auto-model-switcher" } } --- # 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) | Model | Context | Multimodal | Best For | Cost | |-------|---------|------------|----------|------| | **qwen3.5-plus** | 1M | ✅ Text+Image | General tasks, creative writing, balanced performance | Low | | **qwen3-max** | 262K | ❌ Text only | Complex reasoning, deep analysis, research | High | | **qwen3-coder-plus** | 1M | ❌ Text only | Code generation, debugging | Medium | ### Third-party Models (bailian provider) | Model | Context | Multimodal | Best For | |-------|---------|------------|----------| | **glm-5** | 1M | ✅ Text+Image | Multimodal tasks, Chinese optimization | | **kimi-k2.5** | 200K | ✅ Text+Image | Multimodal, research-oriented | | **MiniMax-M2.5** | 1M | ✅ Text+Image | Long context multimodal | ## Selection Logic ### Task Type Detection **Code Tasks** → `bailian/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 Analysis** → `bailian/qwen3-max` - Keywords: analyze, research, compare, evaluate, strategy, deep dive, business analysis - Tasks requiring multi-step reasoning - Financial/strategic analysis **Research Tasks** → `bailian/qwen3-max` - Keywords: research, investigate, study, survey, academic, literature review - Complex information synthesis - Multi-source analysis and comparison **Writing/Copywriting Tasks** → `bailian/qwen3.5-plus` - Keywords: write, draft, copywriting, content, article, blog, email, proposal, creative - Marketing copy, social media content - Creative writing and storytelling **Multimodal Tasks** → `bailian/glm-5` - Image analysis, OCR, visual understanding - Audio processing (when supported) - Mixed text+image inputs **Long Context** → `bailian/qwen3.5-plus` - Document processing > 200K tokens - Summarization of large documents - Historical context analysis **General Tasks** → `bailian/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


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)