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Agent Skill · 研究检索

openclaw-model-router(OpenClaw model router 搜索)

openclaw-model-router 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。

openclaw-model-router 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 6,808。

总安装 20,864周安装 844GitHub Stars 公开资料未说明下载 6,549核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

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:openclaw-model-router(OpenClaw model router 搜索)
来源仓库:https://github.com/jsgoecke/openclaw-model-router
安装命令:
openclaw skills install openclaw-model-router
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 openclaw-model-router

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

openclaw-model-router 智能路由任务至最优模型,平衡成本与性能。适合在 OpenClaw 中处理复杂度不一的任务流时自动选择模型。通过 clawhub 安装,使用 openclaw skills install 命令,无需手动指定模型。安装前应配置各模型定价与延迟参数,确保路由策略准确。

可将简单任务导向廉价模型,节省整体运行开销。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install openclaw-model-router;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openclaw-model-router 怎么安装?

在终端执行 openclaw skills install openclaw-model-router。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-model-router 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openclaw-model-router 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install openclaw-model-router 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

openclaw-model-router 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openclaw-model-router 用的人多吗?

公开数据是累计安装 20,864 次,近一周安装 844 次,下载 6,549 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openclaw-model-router 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openclaw-model-router

OpenClaw model router 搜索 · 本页

20,864—执行命令MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
model-router
description
Intelligent cost-aware model routing that classifies task complexity and selects the optimal AI model. Automatically routes simple tasks to cheap models and complex tasks to premium models. Use when you need "which model should I use", "route this task", "optimize cost", "switch model", "cheapest model for this", "use the right model", or to balance quality vs cost across AI providers. Supports progressive escalation, 5-tier routing, and current model pricing.
version
2.0.0

Smart Model Router

Intelligent cost-aware model routing for OpenClaw agents.

Before executing any task via sessions_spawn or delegating to a sub-agent, classify the task complexity using the rules below and route to the optimal model. This saves 60-90% on LLM costs by using cheap models for simple work and reserving premium models for tasks that genuinely need them.

Core Principle

Route every request to the cheapest model that can handle it well.

Step 1: Classify Task Complexity

Score the task on these dimensions. Count how many COMPLEX/REASONING indicators are present:

SIMPLE indicators (route to Tier 1)

  • Greetings, small talk, status checks, heartbeats
  • Single factual questions ("What is X?", "Define Y")
  • Simple translations, format conversions
  • File lookups, directory listings, basic shell commands
  • Calendar checks, weather queries
  • Tasks under 50 tokens with no technical depth
  • Keywords: "what is", "define", "translate", "list", "check", "hello", "status"

MODERATE indicators (route to Tier 2)

  • Summarization of documents or conversations
  • Single-file code edits, bug fixes, simple refactors
  • Writing emails, messages, short-form content
  • Data extraction, parsing, formatting
  • Explaining concepts, answering "how to" questions
  • Research requiring synthesis of a few sources
  • Keywords: "summarize", "explain", "write", "fix this", "how to", "extract"

COMPLEX indicators (route to Tier 3)

  • Multi-file code generation or refactoring
  • Architecture design, system design
  • Creative writing (stories, long-form, nuanced tone)
  • Debugging complex issues across multiple systems
  • Analysis requiring multiple perspectives
  • Tasks with constraints ("optimize for X while maintaining Y")
  • Keywords: "build", "design", "architect", "refactor", "create", "implement", "analyze"

REASONING indicators (route to Tier 4)

  • Mathematical proofs, formal logic
  • Multi-step reasoning chains ("first X, then Y, therefore Z")
  • Security vulnerability analysis
  • Performance optimization with tradeoffs
  • Scientific analysis, hypothesis testing
  • Any task with 2+ of: "prove", "derive", "why does", "compare and contrast", "evaluate tradeoffs", "step by step"
  • Keywords: "prove", "derive", "reason", "why does", "evaluate", "theorem"

Special Rules

  • 2+ reasoning keywords → always Tier 4 (high confidence)
  • Code blocks or multi-file references → minimum Tier 2
  • "Debug" + stack traces → Tier 3
  • Heartbeats and /status → always Tier 1
  • When uncertain, default to Tier 2 (fast, cheap, good enough)

Step 2: Select Model from Tier

Tier 0 — FREE (OpenRouter free tier)

ModelCostBest For
Gemini 2.5 Flash (free)$0.00High-volume simple tasks, translation
Gemini 2.5 Flash-Lite (free)$0.00Translation, marketing
Gemini 3 Flash Preview (free)$0.00Technology, health, science
DeepSeek V3.2 (free)$0.00Roleplay, creative writing
Moonshot Kimi K2.5 (free)$0.00Technology, programming
Arcee Trinity Large Preview (free)$0.00Creative writing, storytelling, agents

Default Tier 0 model: openrouter/free (auto-selects from available free models)

Access via OpenRouter with model IDs like google/gemini-2.5-flash, deepseek/deepseek-v3.2-20251201, moonshotai/kimi-k2.5-0127. Or use openrouter/free to auto-route across all free models.

Note: Free models have rate limits and may have variable availability. Use for non-critical tasks only.

Tier 1 — SIMPLE (near-zero cost)

ModelInput $/MTokOutput $/MTokBest For
Gemini 2.0 Flash$0.10$0.40Default simple tier — fast, multimodal, 1M context
GPT-4o-mini$0.15$0.60Simple tasks, multimodal
GPT-5 Nano$0.05$0.40Cheapest OpenAI option
DeepSeek V3$0.27$1.10Budget general-purpose
Gemini 2.5 Flash-Lite$0.10$0.40Most economical Google model

Default Tier 1 model: gemini-2.0-flash (best cost/reliability balance)

Tier 2 — MODERATE (balanced)

ModelInput $/MTokOutput $/MTokBest For
Claude Haiku 4.5$1.00$5.00Near-frontier, fast, great coding
GPT-4o$2.50$10.00Multimodal, tool use, solid all-rounder
Gemini 2.5 Flash$0.15$0.60Thinking-enabled, fast reasoning
GPT-5 Mini$0.25$2.00Balanced performance, 400K context
Mistral Medium 3$0.40$2.00European languages, balanced

Default Tier 2 model: claude-haiku-4-5 (best quality-to-price at this tier)

Tier 3 — COMPLEX (premium)

ModelInput $/MTokOutput $/MTokBest For
Claude Sonnet 4.5$3.00$15.00Best coding-to-cost ratio, most popular
GPT-5$1.25$10.00Flagship coding and agentic tasks
GPT-5.3 Codex$1.75*$14.00*Most capable agentic coding model
Gemini 2.5 Pro$1.25$10.00Coding, reasoning, up to 2M context
Claude Opus 4.5$5.00$25.00Maximum intelligence, agentic tasks
Grok 4$3.00$15.00Frontier reasoning, real-time data

*GPT-5.3 Codex API pricing not yet officially released; estimated from GPT-5.2 Codex rates.

Default Tier 3 model: claude-sonnet-4-5 (best balance of quality, coding, and cost)

Tier 4 — REASONING (maximum capability)

ModelInput $/MTokOutput $/MTokBest For
Claude Opus 4.6$5.00$25.00Latest frontier reasoning, extended thinking, 1M context (beta)
Claude Opus 4.5$5.00$25.00Extended thinking, frontier reasoning
o3$2.00$8.00Deep STEM reasoning
DeepSeek R1$0.55$2.19Budget reasoning (20-50x cheaper than o1)
o4-mini$1.10$4.40Efficient reasoning

Default Tier 4 model: claude-opus-4-6 with extended thinking enabled

Step 3: Apply Optimization Mode

🟢 Balanced Mode (DEFAULT)

Use the default model for each tier as listed above. Escalate to next tier if the model produces low-quality output or fails.

🔵 Aggressive Mode (Maximum Savings)

Override tier defaults to cheapest option:

  • Tier 0-1: openrouter/free ($0.00) for simple tasks, fall back to gemini-2.0-flash ($0.10/$0.40)
  • Tier 2: gemini-2.5-flash ($0.15/$0.60)
  • Tier 3: gemini-2.5-pro ($1.25/$10.00)
  • Tier 4: deepseek-r1 ($0.55/$2.19)

Savings: 70-99% vs always using Opus

🟡 Quality Mode (Maximum Quality)

Override tier defaults to best-in-class:

  • Tier 1: claude-haiku-4-5 ($1.00/$5.00)
  • Tier 2: claude-sonnet-4-5 ($3.00/$15.00)
  • Tier 3: claude-opus-4-6 ($5.00/$25.00) or gpt-5.3-codex for coding
  • Tier 4: claude-opus-4-6 ($5.00/$25.00) with extended thinking

Step 4: Execute with sessions_spawn

# Simple task — Tier 1
sessions_spawn --task "What's on my calendar today?" --model gemini-2.0-flash

# Moderate task — Tier 2
sessions_spawn --task "Summarize this document" --model claude-haiku-4-5

# Complex task — Tier 3
sessions_spawn --task "Build a React auth component with tests" --model claude-sonnet-4-5

# Reasoning task — Tier 4
sessions_spawn --task "Prove this algorithm is O(n log n)" --model claude-opus-4-6

Progressive Escalation Pattern

When uncertain about complexity, start cheap and escalate:

# 1. Try Tier 1 with timeout
sessions_spawn --task "Fix this bug" --model gemini-2.0-flash --runTimeoutSeconds 60

# 2. If output is poor or times out, escalate to Tier 2
sessions_spawn --task "Fix this bug" --model claude-haiku-4-5

# 3. If still failing, escalate to Tier 3
sessions_spawn --task "Fix this complex bug" --model claude-sonnet-4-5

Maximum escalation chain: 3 attempts. If Tier 3 fails, surface the error to the user rather than burning tokens.

Parallel Processing for Batch Tasks

Route batch/parallel tasks to Tier 1 models for massive savings:

# Batch summaries in parallel with cheap model
sessions_spawn --task "Summarize doc A" --model gemini-2.0-flash &
sessions_spawn --task "Summarize doc B" --model gemini-2.0-flash &
sessions_spawn --task "Summarize doc C" --model gemini-2.0-flash &
wait

# Then analyze results with premium model
sessions_spawn --task "Synthesize findings from all summaries" --model claude-sonnet-4-5

Special Routing Rules

ScenarioRoute ToWhy
Heartbeat / status checkTier 0 (openrouter/free) or Tier 1Zero intelligence needed, save every cent
Vision / image analysisgemini-2.5-proBest multimodal + huge context
Long context (>100K tokens)gemini-2.5-pro or gpt-51M-2M context windows
Chinese language tasksdeepseek-v3 or glm-4.7Optimized for Chinese
Real-time web data neededgrok-4.1-fastBuilt-in X/web search, 2M context
Agentic coding tasksgpt-5.3-codex or claude-sonnet-4-5Purpose-built for agentic code workflows
Code generationclaude-sonnet-4-5 minimumBest code quality per dollar
Math / formal proofso3 or claude-opus-4-6 with thinkingSpecialized reasoning

Cost Comparison (Typical Workload)

For a typical OpenClaw day (24 heartbeats + 20 sub-agent tasks + 10 user queries):

StrategyMonthly CostSavings
All Opus 4.6~$200baseline
Smart routing (balanced)~$4578%
Smart routing (aggressive)~$1592%
Smart routing (aggressive + free tier)~$597%
All free models (OpenRouter)~$0100% (but rate-limited & unreliable)

When NOT to Route Down

Always use Tier 3+ for:

  • Security-sensitive code review
  • Financial calculations where errors are costly
  • Architecture decisions that affect the whole codebase
  • Anything the user explicitly asks for premium quality
  • Tasks where the user says "be thorough" or "take your time"

Mode Switching

Users can switch modes mid-conversation:

  • "Use aggressive routing" → Switch to cheapest models per tier
  • "Use quality mode" → Switch to best models per tier
  • "Use balanced routing" → Return to defaults
  • "Use [specific model] for this" → Override routing for one task

Pricing Reference (February 2026)

All prices per million tokens. Models are listed from cheapest to most expensive output:

ModelInputOutputContextProvider
OpenRouter Free Models$0.00$0.00VariesOpenRouter
GPT-5 Nano$0.05$0.40400KOpenAI
Gemini 2.0 Flash$0.10$0.401MGoogle
Gemini 2.5 Flash-Lite$0.10$0.401MGoogle
GPT-4o-mini$0.15$0.60128KOpenAI
Gemini 2.5 Flash$0.15$0.601MGoogle
Grok 4.1 Fast$0.20$0.502MxAI
GPT-5 Mini$0.25$2.00400KOpenAI
DeepSeek V3$0.27$1.1064KDeepSeek
DeepSeek R1$0.55$2.1964KDeepSeek
Claude Haiku 4.5$1.00$5.00200KAnthropic
o4-mini$1.10$4.40200KOpenAI
Gemini 2.5 Pro$1.25$10.001MGoogle
GPT-5$1.25$10.00400KOpenAI
GPT-5.3 Codex$1.75*$14.00*400KOpenAI
o3$2.00$8.00200KOpenAI
GPT-4o$2.50$10.00128KOpenAI
Claude Sonnet 4.5$3.00$15.00200KAnthropic
Grok 4$3.00$15.00256KxAI
Claude Opus 4.5$5.00$25.00200KAnthropic
Claude Opus 4.6$5.00$25.00200K (1M beta)Anthropic

*GPT-5.3 Codex pricing estimated from GPT-5.2 Codex; official API pricing pending.

Note: Prices change. Check provider pricing pages for current rates. Batch API discounts (50% off) and prompt caching (50-90% off) can reduce costs further. OpenRouter free models have rate limits — see openrouter.ai/collections/free-models for current availability.

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

平台分布

OpenClaw

97.47%
按下载量换算6,383

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install openclaw-model-router 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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