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Smart Model Router
作者
Solomon Watkins
· GitHub ↗
· v1.0.0
· MIT-0
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在 OpenClaw 中安装
/install smart-router-ai
功能描述
Intent-based model router that auto-detects your intent (fix/plan/flow) and routes to optimal AI model. Stop choosing models manually. Better results, less f...
使用说明 (SKILL.md)
Smart Model Router
Never choose an AI model manually again.
How It Works
- You type your prompt naturally
- Router analyzes trigger words and routes to optimal model
- Response streams back immediately
- Override with
--intentflag when needed
Trigger Detection
| Intent | Trigger Words | Routes To |
|---|---|---|
| fix | bug, error, crash, broken, exception, fail, debug, issue, problem, stuck | cloud-code (CodeLLaMA) |
| plan | design, architect, structure, how should, approach, strategy, pattern | deepseek-r1 (Architect) |
| flow | (default) creative, conversational, general | kimi-k2.5:cloud (main) |
Perfect For
- OpenClaw users with multiple agents
- Teams standardizing model usage
- Anyone tired of manual model switching
- Workflows needing consistent routing
What's Included
- Intent detection engine (keyword + pattern matching)
- Shell aliases for quick access (fix/plan/flow/ask commands)
- Confidence scoring on detections
- Override flags for manual control
- Router dashboard for monitoring
Why It Sells
- Cognitive offload: Stop choosing, start solving
- Better results: Right tool for the right job
- Time saver: No more manual model switching
- Learns your patterns: Intent detection improves with use
- Override-friendly: Force specific model when needed
Quick Start
# Setup router
bash scripts/setup.sh
# Add aliases to shell
echo 'source ~/.openclaw/workspace/intent-router-aliases.sh' >> ~/.zshrc
source ~/.zshrc
# Test detection
router-test "my app keeps crashing with null pointer"
# Output: Detected intent: fix (confidence: 94%) → Routing to cloud-code
# Use in practice
fix "TypeError: Cannot read property 'map' of undefined in cart.js"
plan "How should I structure a multi-tenant SaaS database?"
flow "Write a creative product description for our new AI tool"
# Override when needed
ask --intent fix --model deepseek-r1 "Debug this race condition"
Router Dashboard
# View routing stats
router-dashboard
# See recent detections
router-history --last 20
# Export analytics
router-dashboard --export report.json
Requirements
- Termux (Android) or Linux environment
- OpenClaw agent system
- At least 2 agents configured (main + cloud-code or deepseek-r1)
Support
Email: [email protected]
安全使用建议
Review this before installing if you work with private code, credentials, customer data, or regulated information. Confirm which providers receive prompts, whether routing happens automatically or after confirmation, what history or analytics are stored, how to disable or delete stored data, and how to undo the shell startup change.
能力评估
Purpose & Capability
The stated purpose is coherent: detect fix/plan/flow intent and route prompts to configured models. The concern is that it handles arbitrary user prompts, uses broad trigger words, and routes to cloud models such as cloud-code, deepseek-r1, and kimi-k2.5:cloud without clearly defining privacy boundaries or confirmation behavior.
Instruction Scope
The trigger table and override flag are disclosed, but routing is presented as automatic and immediate. Common words like issue, problem, design, and approach can route unrelated or sensitive prompts to a different model than the user expected.
Install Mechanism
The artifact contains only markdown and JSON, with no executable scripts included. However, the quick start references bash scripts/setup.sh and instructs users to append a source command to ~/.zshrc, which is a persistent shell-environment change.
Credentials
For a model router, prompt inspection and model dispatch are purpose-aligned, but the documentation also advertises routing history, dashboards, learning user patterns, and analytics export without explaining what prompt data or metadata is stored, retained, or exported.
Persistence & Privilege
The shell alias setup is visibly documented, but it modifies shell startup behavior without an upfront security warning, uninstall path, or explanation of ongoing effects. The advertised history/export features also imply persistence without clear controls.
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 smart-router-ai - 安装完成后,直接呼叫该 Skill 的名称或使用
/smart-router-ai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 - Intent-based auto-routing for fix/plan/flow workflows (renamed to avoid conflict)
元数据
常见问题
Smart Model Router 是什么?
Intent-based model router that auto-detects your intent (fix/plan/flow) and routes to optimal AI model. Stop choosing models manually. Better results, less f... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 53 次。
如何安装 Smart Model Router?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install smart-router-ai」即可一键安装,无需额外配置。
Smart Model Router 是免费的吗?
是的,Smart Model Router 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Smart Model Router 支持哪些平台?
Smart Model Router 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 Smart Model Router?
由 Solomon Watkins(@wizelements)开发并维护,当前版本 v1.0.0。
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