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local-config-model-recommender
作者
garygou1024
· GitHub ↗
· v1.0.0
· MIT-0
265
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当前安装
1
版本数
在 OpenClaw 中安装
/install local-config-model-recommender
功能描述
Intelligently recommends optimal AI models based on task requirements. Dynamically reads the user's OpenCLAW configuration and provides context-aware model s...
使用说明 (SKILL.md)
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 found
Usage 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
安全使用建议
This skill appears to do what it says, but before enabling it: 1) inspect your ~/.openclaw/openclaw.json to confirm it contains only model IDs/metadata and not API keys or secrets; 2) note that the skill's metadata does not declare the config path it will read — prefer skills that explicitly declare required config access; 3) if you are concerned about data exfiltration, restrict network access for the agent or run the skill in a sandbox until you've verified behavior; and 4) if you need stronger guarantees, ask the author to add the required-config-path to the metadata and to limit parsing to non-sensitive fields.
功能分析
Type: OpenClaw Skill
Name: local-config-model-recommender
Version: 1.0.0
The skill instructs the AI agent to read and parse the user's local configuration file (~/.openclaw/openclaw.json) in SKILL.md. This file is highly sensitive as it typically contains API keys and provider credentials for various AI services. While this access is plausibly needed to determine which models are available for recommendation, the broad instruction to read the entire config file poses a significant risk of exposing secrets within the agent's context. No explicit evidence of data exfiltration or malicious intent was found, but the behavior is high-risk.
能力评估
Purpose & Capability
The skill's name and description align with its runtime instructions (it reads the OpenClaw config and recommends models). However, the package metadata declares no required config paths even though SKILL.md explicitly instructs the agent to parse ~/.openclaw/openclaw.json — a mismatch in declared vs. actual resource access.
Instruction Scope
Instructions are narrowly scoped: parse the OpenClaw config, analyze task keywords, and match model IDs. They do not instruct network exfiltration or broad system reads. One minor concern: the guidance to 'analyze user's task requirements' is vague and could allow broader context gathering unless the agent's runtime policies restrict that.
Install Mechanism
This is an instruction-only skill with no install spec or code files, so nothing is written to disk and there is no external install risk.
Credentials
The skill declares no environment variables or credentials, which is reasonable. But it reads ~/.openclaw/openclaw.json; depending on your setup that file could contain more than model IDs (e.g., endpoint URLs or API keys). The skill does not declare this config access in its metadata, so verify what is stored in that file before allowing the skill to read it.
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent privileges in the metadata. Autonomous invocation is allowed by default (platform normal) and is not a standalone red flag here.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install local-config-model-recommender - 安装完成后，直接呼叫该 Skill 的名称或使用
/local-config-model-recommender触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
- Initial release of local-config-model-recommender.
- Dynamically reads user’s OpenCLAW configuration to list available models.
- Recommends optimal AI models based on keyword pattern matching aligned to task requirements.
- Supports a wide range of both global and domestic models including OpenAI, Claude, Gemini, DeepSeek, Kimi, Zhipu GLM, Qwen, and MiniMax.
- Covers multimodal, code generation, advanced reasoning, premium tier, and lightweight models for various needs.
- Ensures recommendations are tailored to models actually available in your configuration.
元数据
常见问题
local-config-model-recommender 是什么？
Intelligently recommends optimal AI models based on task requirements. Dynamically reads the user's OpenCLAW configuration and provides context-aware model s... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 265 次。
如何安装 local-config-model-recommender？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install local-config-model-recommender」即可一键安装，无需额外配置。
local-config-model-recommender 是免费的吗？
是的，local-config-model-recommender 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
local-config-model-recommender 支持哪些平台？
local-config-model-recommender 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 local-config-model-recommender？
由 garygou1024（@garygou1024）开发并维护，当前版本 v1.0.0。
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