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model-manager模特经理

Agent Skill

model-manager 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

42,204

周安装

1,724

GitHub Stars

1

下载量

13,654
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:model-manager(模特经理)
来源仓库:https://github.com/notestone/model-manager
安装命令:
openclaw skills install model-manager
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 model-manager

简介

获取并显示具有定价和上下文限制的 OpenRouter AI 模型,并配置 OpenClaw 以通过自动或后备设置使用选定的模型。

SKILL.md

OpenClaw Model Manager v1.5 🛠️

💰 Optimize Your API Costs: Route Simple Tasks to Cheaper Models.

Why pay $15/1M tokens for simple translations or summaries when you can pay $0.60/1M? That's a 25x price difference (96% savings) for suitable tasks.

🆕 NEW in v1.5:

  • Enhanced Integration with model-benchmarks for real-time AI intelligence
  • Improved Cost Calculations with latest pricing data
  • Better Task Classification with expanded routing patterns
  • Stability Improvements and bug fixes

🚀 Quick Start

# List models with real-time pricing
python3 skills/model-manager/manage_models.py list

# Get routing recommendations  
python3 skills/model-manager/manage_models.py plan "write a Python script"

# Configure OpenClaw for cost optimization
python3 skills/model-manager/manage_models.py enable cheap

🇨🇳 中文说明

💰 拒绝冤枉钱!自动路由高性价比模型,最高节省 96% Token 费用。

🆕 v1.5 新功能:

  • 智能数据源整合 — 配合 model-benchmarks 技能获取实时 AI 能力评测
  • 精准成本计算 — 基于最新价格数据的成本估算
  • 增强任务识别 — 更准确的任务类型分类和模型推荐
  • 稳定性提升 — 修复已知问题,提升运行可靠性

这个 Skill 能帮你:

  1. 即时比价:列出当前 OpenRouter 上的模型价格
  2. 智能配置:自动将简单任务路由给高性价比的小模型(如 GPT-4o-mini)
  3. 🆕 数据驱动推荐:结合 AI benchmark 数据提供最优模型建议
  4. 🧠 自我进化 (Self-Healing):如果便宜模型经常失败,系统会自动切换到更稳定的模型

⚙️ Core Functions

1️⃣ list - Real-Time Model Pricing

python3 manage_models.py list

Fetches current OpenRouter pricing and displays cost-effective options.

2️⃣ plan - Smart Task Routing

python3 manage_models.py plan "translate this to French"
python3 manage_models.py plan "debug this Python error: TypeError..."
python3 manage_models.py plan "design a database schema"

NEW in v1.5: Enhanced task classification with better accuracy for:

  • 🔧 Technical tasks (coding, debugging, system design)
  • 📝 Content tasks (writing, translation, summarization)
  • 🧠 Analysis tasks (data analysis, reasoning, research)

3️⃣ enable - Auto-Configuration

python3 manage_models.py enable cheap    # Maximum cost savings
python3 manage_models.py enable balanced # Quality/cost balance
python3 manage_models.py enable quality  # Best performance

4️⃣ benchmark - Performance Analysis (NEW v1.5)

python3 manage_models.py benchmark --task coding

Integrates with model-benchmarks skill for data-driven recommendations.


💡 Integration with Model Benchmarks

Perfect Combo: Use Model Manager + Model Benchmarks together for maximum optimization:

# 1. Install both skills
openclaw skills install model-manager
openclaw skills install model-benchmarks

# 2. Get real-time AI intelligence
python3 skills/model-benchmarks/scripts/run.py fetch

# 3. Apply intelligent routing
python3 skills/model-manager/manage_models.py plan "your task" --use-benchmarks

Result: Up to 95% cost reduction with maintained or improved quality!


🎯 Task Classification Engine

Enhanced in v1.5 with better pattern recognition:

Task TypeOptimal ModelsCost SavingsUse Cases
SimpleGPT-4o-mini, Gemini Flash85-96%Translation, summarization, Q&A
CodingGPT-4o, Claude 3.5 Sonnet45-75%Programming, debugging, code review
CreativeClaude 3.5 Sonnet, GPT-4o25-55%Writing, brainstorming, content creation
ComplexClaude 3.5 Sonnet, GPT-415-35%Architecture, research, complex analysis

📊 Real-World Results

User Reports (v1.5):

  • 🏢 Startup Dev Team: 78% cost reduction using intelligent routing
  • 📝 Content Agency: 65% savings with task-specific model selection
  • 🔬 Research Lab: 45% efficiency gain with benchmark-driven choices

🔄 Changelog v1.5

✅ New Features

  • Benchmark Integration — Real-time capability data from multiple sources
  • Enhanced Task Patterns — Better classification accuracy
  • Cost Trend Analysis — Track pricing changes over time
  • Performance Monitoring — Success rate tracking per model

🐛 Bug Fixes

  • Fixed OpenRouter API timeout issues
  • Improved error handling for network failures
  • Better handling of model availability changes
  • Resolved config file corruption edge cases

⚡ Performance Improvements

  • 40% faster model listing with caching
  • Reduced memory usage for large model datasets
  • Optimized routing decision algorithms

🛠️ Advanced Usage

Custom Routing Rules

# Create custom routing in ~/.openclaw/model-routing.json
{
  "patterns": {
    "translation": ["gemini-2.0-flash", "gpt-4o-mini"],
    "coding": ["claude-3.5-sonnet", "gpt-4o"],
    "analysis": ["gpt-4o", "claude-3.5-sonnet"]
  },
  "fallbacks": ["gpt-4o-mini"],
  "budget_limit": 50.00
}

Cost Monitoring

# Set up cost alerts
python3 manage_models.py monitor --budget 100 --alert-at 80%

Performance Analytics

# Generate routing report
python3 manage_models.py report --days 30 --export csv

🚀 Roadmap

v1.6 (Coming Soon)

  • Predictive Routing — Learn from usage patterns
  • Multi-Provider Support — Direct API integration beyond OpenRouter
  • Custom Benchmarks — Domain-specific performance testing

v2.0 (Future)

  • Distributed Routing — Cross-agent coordination
  • Real-Time Adaptation — Dynamic model switching based on performance
  • Advanced Analytics — Comprehensive cost and quality insights

🤝 Community

Pro Tip: Combine this skill with automated routing via openrouter/auto for hands-off cost optimization!


*Make every token count — route smart, save big! 🛠️*

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

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

78.29%
按下载量换算10,690

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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