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Agent Skill · AI 工具

intelligent-routing(智能路由)

intelligent-routing 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

intelligent-routing 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证为 MIT,第三方扫描有提醒项,按安装量在AI 工具类的 2,536 个 Skill 里排第 578。

总安装 3,045周安装 122GitHub Stars 7,197下载 986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

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:intelligent-routing(智能路由)
来源仓库:https://github.com/vudovn/antigravity-kit
仓库路径:skills/intelligent-routing
安装命令:
npx skills add https://github.com/vudovn/antigravity-kit --skill intelligent-routing
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vudovn/antigravity-kit --skill intelligent-routing

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

智能路由技能可以: ✅ 零命令操作(无需/orchestrate ) ✅ 根据请求分析自动选择专家 ✅ 透明地沟通正在应用哪些专业知识 ✅ 与现有工作流程无缝集成 ✅ 覆盖明确代理提及的功能 ✅ 回退到协调器来处理复杂的任务 结果:用户无需了解系统架构即可获得专家级响应。

后续步骤:将此技能集成到 GEMINI.md TIER 0 规则中。每周安装量 122 存储库 vudovn/反重力套件 GitHub 之星 7.2K 第一次看到 1 天前 安全审计 Gen Agent Trust Hub 通行证 插座警告 斯尼克通行证

来源仓库内路径:skills/intelligent-routing

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/vudovn/antigravity-kit --skill intelligent-rou…;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

    它需要操作浏览器,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

intelligent-routing 怎么安装?

在终端执行 npx skills add https://github.com/vudovn/antigravity-kit --skill intelligent-routing。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

intelligent-routing 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

intelligent-routing 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

intelligent-routing 是免费的吗?

来源标注的许可证是 MIT。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。

intelligent-routing 用的人多吗?

公开数据是累计安装 3,045 次,近一周安装 122 次,下载 986 次,GitHub 7,197 星。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。

intelligent-routing 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 来源仓库有 7,197 星,维护活跃度相对可查。

先想清楚的地方

  • 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 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
intelligent-routing

智能路由 · 本页

3,0457,197操作浏览器MIT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

Intelligent Agent Routing

Purpose: Automatically analyze user requests and route them to the most appropriate specialist agent(s) without requiring explicit user mentions.

Core Principle

The AI should act as an intelligent Project Manager, analyzing each request and automatically selecting the best specialist(s) for the job.

How It Works

1. Request Analysis

Before responding to ANY user request, perform automatic analysis:

graph TD
    A[User Request: Add login] --> B[ANALYZE]
    B --> C[Keywords]
    B --> D[Domains]
    B --> E[Complexity]
    C --> F[SELECT AGENT]
    D --> F
    E --> F
    F --> G[security-auditor + backend-specialist]
    G --> H[AUTO-INVOKE with context]

2. Agent Selection Matrix

Use this matrix to automatically select agents:

User IntentKeywordsSelected Agent(s)Auto-invoke?
Authentication"login", "auth", "signup", "password"security-auditor + backend-specialist✅ YES
UI Component"button", "card", "layout", "style"frontend-specialist✅ YES
Mobile UI"screen", "navigation", "touch", "gesture"mobile-developer✅ YES
API Endpoint"endpoint", "route", "API", "POST", "GET"backend-specialist✅ YES
Database"schema", "migration", "query", "table"database-architect + backend-specialist✅ YES
Bug Fix"error", "bug", "not working", "broken"debugger✅ YES
Test"test", "coverage", "unit", "e2e"test-engineer✅ YES
Deployment"deploy", "production", "CI/CD", "docker"devops-engineer✅ YES
Security Review"security", "vulnerability", "exploit"security-auditor + penetration-tester✅ YES
Performance"slow", "optimize", "performance", "speed"performance-optimizer✅ YES
Product Def"requirements", "user story", "backlog", "MVP"product-owner✅ YES
New Feature"build", "create", "implement", "new app"orchestrator → multi-agent⚠️ ASK FIRST
Complex TaskMultiple domains detectedorchestrator → multi-agent⚠️ ASK FIRST

3. Automatic Routing Protocol

TIER 0 - Automatic Analysis (ALWAYS ACTIVE)

Before responding to ANY request:

// Pseudo-code for decision tree
function analyzeRequest(userMessage) {
    // 1. Classify request type
    const requestType = classifyRequest(userMessage);

    // 2. Detect domains
    const domains = detectDomains(userMessage);

    // 3. Determine complexity
    const complexity = assessComplexity(domains);

    // 4. Select agent(s)
    if (complexity === "SIMPLE" && domains.length === 1) {
        return selectSingleAgent(domains[0]);
    } else if (complexity === "MODERATE" && domains.length <= 2) {
        return selectMultipleAgents(domains);
    } else {
        return "orchestrator"; // Complex task
    }
}

4. Response Format

When auto-selecting an agent, inform the user concisely:

🤖 **Applying knowledge of `@security-auditor` + `@backend-specialist`...**

[Proceed with specialized response]

Benefits:

  • ✅ User sees which expertise is being applied
  • ✅ Transparent decision-making
  • ✅ Still automatic (no /commands needed)

Domain Detection Rules

Single-Domain Tasks (Auto-invoke Single Agent)

DomainPatternsAgent
Securityauth, login, jwt, password, hash, tokensecurity-auditor
Frontendcomponent, react, vue, css, html, tailwindfrontend-specialist
Backendapi, server, express, fastapi, nodebackend-specialist
Mobilereact native, flutter, ios, android, expomobile-developer
Databaseprisma, sql, mongodb, schema, migrationdatabase-architect
Testingtest, jest, vitest, playwright, cypresstest-engineer
DevOpsdocker, kubernetes, ci/cd, pm2, nginxdevops-engineer
Debugerror, bug, crash, not working, issuedebugger
Performanceslow, lag, optimize, cache, performanceperformance-optimizer
SEOseo, meta, analytics, sitemap, robotsseo-specialist
Gameunity, godot, phaser, game, multiplayergame-developer

Multi-Domain Tasks (Auto-invoke Orchestrator)

If request matches 2+ domains from different categories, automatically use orchestrator:

Example: "Create a secure login system with dark mode UI"
→ Detected: Security + Frontend
→ Auto-invoke: orchestrator
→ Orchestrator will handle: security-auditor, frontend-specialist, test-engineer

Complexity Assessment

SIMPLE (Direct agent invocation)

  • Single file edit
  • Clear, specific task
  • One domain only
  • Example: "Fix the login button style"

Action: Auto-invoke respective agent

MODERATE (2-3 agents)

  • 2-3 files affected
  • Clear requirements
  • 2 domains max
  • Example: "Add API endpoint for user profile"

Action: Auto-invoke relevant agents sequentially

COMPLEX (Orchestrator required)

  • Multiple files/domains
  • Architectural decisions needed
  • Unclear requirements
  • Example: "Build a social media app"

Action: Auto-invoke orchestrator → will ask Socratic questions

Implementation Rules

Rule 1: Silent Analysis

DO NOT announce "I'm analyzing your request..."
  • ✅ Analyze silently
  • ✅ Inform which agent is being applied
  • ❌ Avoid verbose meta-commentary

Rule 2: Inform Agent Selection

DO inform which expertise is being applied:

🤖 **Applying knowledge of `@frontend-specialist`...**

I will create the component with the following characteristics:
[Continue with specialized response]

Rule 3: Seamless Experience

The user should not notice a difference from talking to the right specialist directly.

Rule 4: Override Capability

User can still explicitly mention agents:

User: "Use @backend-specialist to review this"
→ Override auto-selection
→ Use explicitly mentioned agent

Edge Cases

Case 1: Generic Question

User: "How does React work?"
→ Type: QUESTION
→ No agent needed
→ Respond directly with explanation

Case 2: Extremely Vague Request

User: "Make it better"
→ Complexity: UNCLEAR
→ Action: Ask clarifying questions first
→ Then route to appropriate agent

Case 3: Contradictory Patterns

User: "Add mobile support to the web app"
→ Conflict: mobile vs web
→ Action: Ask: "Do you want responsive web or native mobile app?"
→ Then route accordingly

Integration with Existing Workflows

With /orchestrate Command

  • User types /orchestrate: Explicit orchestration mode
  • AI detects complex task: Auto-invoke orchestrator (same result)

Difference: User doesn't need to know the command exists.

With Socratic Gate

  • Auto-routing does NOT bypass Socratic Gate
  • If task is unclear, still ask questions first
  • Then route to appropriate agent

With GEMINI.md Rules

  • Priority: GEMINI.md rules > intelligent-routing
  • If GEMINI.md specifies explicit routing, follow it
  • Intelligent routing is the DEFAULT when no explicit rule exists

Testing the System

Test Cases

Test 1: Simple Frontend Task
User: "Create a dark mode toggle button"
Expected: Auto-invoke frontend-specialist
Verify: Response shows "Using @frontend-specialist"
Test 2: Security Task
User: "Review the authentication flow for vulnerabilities"
Expected: Auto-invoke security-auditor
Verify: Security-focused analysis
Test 3: Complex Multi-Domain
User: "Build a chat application with real-time notifications"
Expected: Auto-invoke orchestrator
Verify: Multiple agents coordinated (backend, frontend, test)
Test 4: Bug Fix
User: "Login is not working, getting 401 error"
Expected: Auto-invoke debugger
Verify: Systematic debugging approach

Performance Considerations

Token Usage

  • Analysis adds ~50-100 tokens per request
  • Tradeoff: Better accuracy vs slight overhead
  • Overall SAVES tokens by reducing back-and-forth

Response Time

  • Analysis is instant (pattern matching)
  • No additional API calls required
  • Agent selection happens before first response

User Education

Optional: First-Time Explanation

If this is the first interaction in a project:

💡 **Tip**: I am configured with automatic specialist agent selection.
I will always choose the most suitable specialist for your task. You can
still mention agents explicitly with `@agent-name` if you prefer.

Debugging Agent Selection

Enable Debug Mode (for development)

Add to GEMINI.md temporarily:

## DEBUG: Intelligent Routing

Show selection reasoning:

- Detected domains: [list]
- Selected agent: [name]
- Reasoning: [why]

Summary

intelligent-routing skill enables:

✅ Zero-command operation (no need for /orchestrate) ✅ Automatic specialist selection based on request analysis ✅ Transparent communication of which expertise is being applied ✅ Seamless integration with existing workflows ✅ Override capability for explicit agent mentions ✅ Fallback to orchestrator for complex tasks

Result: User gets specialist-level responses without needing to know the system architecture.


Next Steps: Integrate this skill into GEMINI.md TIER 0 rules.

平台分布

Claude Code

25.31%
按下载量换算250

Cursor

24.14%
按下载量换算238

Gemini CLI

16.5%
按下载量换算163

windsurf

13.31%
按下载量换算131

Antigravity

8.13%
按下载量换算80

trae

3.63%
按下载量换算36

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。

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