- name
- local-config-model-recommender
- description
- Intelligently recommends optimal AI models based on task requirements. Dynamically reads the user's OpenCLAW configuration and provides context-aware model suggestions. Supports all major global and domestic models including OpenAI, Claude, Gemini, DeepSeek, Kimi, Zhipu GLM, Qwen, and MiniMax.
Model Recommender
An intelligent model selection assistant that dynamically analyzes your OpenCLAW configuration and recommends the most suitable AI model for your specific task.
Overview
This skill reads your local OpenCLAW configuration to determine available models, then applies keyword-based capability matching to provide intelligent recommendations based on the task at hand.
Supported Models
Global Providers
| Provider | Models |
|---|---|
| OpenAI | gpt-5-pro, gpt-4o, gpt-4o-mini, o3, o1 |
| Anthropic Claude | claude-opus-4.6, claude-sonnet-4.6, claude-haiku-4.5 |
| Google Gemini | gemini-3.1-pro, gemini-3.1-flash, gemini-2.5-flash |
| Mistral | mistral-large, mistral-small |
| xAI | grok-4.20-beta, grok-4-fast |
Domestic (China) Providers
| Provider | Models |
|---|---|
| Alibaba Qwen | qwen3-max, qwen3-vl, qwen3.5-plus, qwen3-coder-plus |
| MiniMax | minimax-m2.5, minimax-m2.1 |
| DeepSeek | deepseek-v3.2, deepseek-chat, deepseek-coder |
| Moonshot (Kimi) | kimi-k2.5, kimi-k2 |
| Zhipu GLM | glm-5, glm-4.7-flash, glm-4.6v |
| Baidu ERNIE | ernie-4.5-thinking, ernie-4.5-vl |
| ByteDance Seed | seed-2.0-lite, seed-2.0-mini |
Capability Mapping
The skill uses keyword-based pattern matching to infer model capabilities:
| Keyword | Capability | Primary Use Case |
|---|---|---|
vl, vision, image, 4v, 4o | Vision/Multimodal | Image analysis, OCR, chart interpretation |
code, coder, codex | Code Generation | Programming, debugging, refactoring |
o1, o3, o4, reasoning, thinking | Advanced Reasoning | Mathematical reasoning, complex logic |
max, pro, premium, large, opus | Premium/Tier-1 | High-quality output, complex tasks |
mini, small, lite, flash, haiku, nano | Lightweight | Fast response, simple tasks, cost-sensitive |
Recommendation Logic
1. Parse ~/.openclaw/openclaw.json to extract configured models
2. Analyze user's task requirements
3. Match task to model capabilities via keyword detection
4. Return the best-matching model from available configuration
5. Fall back to default model if no specific match foundUsage Examples
User: "Which model should I use for coding?" → Recommend: minimax-m2.5, deepseek-coder, qwen3-coder-plus
User: "I need to analyze an image" → Recommend: qwen3-vl, glm-4.6v, gpt-4o, gemini-1.5-pro
User: "For complex reasoning tasks" → Recommend: o3, claude-opus-4.6, qwen3-max, gemini-3.1-pro
Notes
- Automatically adapts to your specific configuration
- Prioritizes models that are actually available in your setup
- Falls back gracefully when exact capability matches aren't found
- Supports both global (OpenAI, Claude, Gemini) and domestic (Chinese) model providers