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Install in OpenClaw
/install 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, wr...
README (SKILL.md)
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
- Primary model selection based on task type
- If primary model fails, fallback to
qwen3.5-plus - 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-maxUse 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
Usage Guidance
This skill appears to do what it says: automatically pick a model from your pre-configured list. Before installing: (1) confirm your openclaw.json lists only provider models you trust, (2) verify where model-selection logs are written or sent (local vs remote) and whether that meets your privacy needs, (3) ensure the agent already has the provider credentials/configuration needed to check model availability, and (4) test the skill in a limited environment to confirm it preserves session context and respects manual overrides.
Capability Analysis
Type: OpenClaw Skill
Name: auto-model-switcher
Version: 1.1.0
The skill bundle contains only metadata and instructional markdown (SKILL.md) designed to guide an AI agent in selecting appropriate LLM models based on task types (e.g., coding, analysis, research). There is no executable code, no network activity, and no evidence of malicious prompt injection or data exfiltration logic.
Capability Assessment
Purpose & Capability
Name and description match the instructions: the SKILL.md contains model lists, selection logic by task type, fallback rules, manual overrides, and notes to validate against openclaw.json. No unrelated env vars, binaries, or installs are requested.
Instruction Scope
Instructions remain within the stated purpose (detect task type, pick a configured model, preserve session). Two ambiguous items: (1) 'Log model selections for learning and optimization' does not specify where logs are stored or sent; (2) 'Always check if target model is available' implies reading openclaw.json or querying provider status — that may require the agent to access config or provider endpoints that are outside the skill text but are reasonable operational requirements.
Install Mechanism
Instruction-only skill with no install spec and no code files — minimal install risk because nothing is fetched or written by the skill itself.
Credentials
No environment variables, credentials, or config paths are required by the skill. The SKILL.md explicitly restricts switching to pre-configured models in openclaw.json, which is proportionate. Note: actual model availability checks or provider interactions will rely on existing agent configuration and credentials outside this skill.
Persistence & Privilege
The skill is not always-enabled and does not request elevated persistence. There is no instruction to modify other skills or system-wide agent settings. Autonomous invocation is allowed by platform default but is not combined with other high-risk flags.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install auto-model-switcher - After installation, invoke the skill by name or use
/auto-model-switcher - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
Add support for writing and research tasks
v1.0.0
Initial release of auto-model-switcher.
- Automatically selects the most suitable model based on task type (coding, analysis, multimodal, context length).
- Optimizes for performance and cost without manual intervention.
- Supports fallback and manual override for flexibility and reliability.
- Ensures safe switching by only allowing pre-configured models.
- Tracks key performance metrics for ongoing improvement.
Metadata
Frequently Asked Questions
What is Auto Model Switcher?
Automatically selects the best model based on task type and requirements. Use when: (1) Task requires specific capabilities (coding, analysis, multimodal, wr... It is an AI Agent Skill for Claude Code / OpenClaw, with 198 downloads so far.
How do I install Auto Model Switcher?
Run "/install auto-model-switcher" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Auto Model Switcher free?
Yes, Auto Model Switcher is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Auto Model Switcher support?
Auto Model Switcher is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Auto Model Switcher?
It is built and maintained by mrcuo (@mrcuo); the current version is v1.1.0.
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