Tencent SkillHub · AI

OpenClaw Model Manager

Fetch and display OpenRouter AI models with pricing and context limits, and configure OpenClaw to use selected models via automatic or fallback settings.

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Fetch and display OpenRouter AI models with pricing and context limits, and configure OpenClaw to use selected models via automatic or fallback settings.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: consolidate_memory.py, manage_models.py, run.sh, README.md, smart_find.py, prompts.json

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I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.5.0

Provenance

Publisher: Notestone
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 19 sections Open source page

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：即时比价：列出当前 OpenRouter 上的模型价格智能配置：自动将简单任务路由给高性价比的小模型（如 GPT-4o-mini） 🆕 数据驱动推荐：结合 AI benchmark 数据提供最优模型建议 🧠 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

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 CasesSimpleGPT-4o-mini, Gemini Flash85-96%Translation, summarization, Q&ACodingGPT-4o, Claude 3.5 Sonnet45-75%Programming, debugging, code reviewCreativeClaude 3.5 Sonnet, GPT-4o25-55%Writing, brainstorming, content creationComplexClaude 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

✅ 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

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

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

GitHub: openclaw-model-manager Issues: Report bugs and request features Discord: Join #model-optimization channel Companion: Use with model-benchmarks for best results Pro Tip: Combine this skill with automated routing via openrouter/auto for hands-off cost optimization! Make every token count — route smart, save big! 🛠️

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

4 Scripts1 Docs1 Config

README.md Docs
consolidate_memory.py Scripts
manage_models.py Scripts
run.sh Scripts
smart_find.py Scripts
prompts.json Config