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intelligent-routing智能路由

Agent Skill

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。

总安装

3,045

周安装

122

GitHub Stars

7,197

下载量

986
CodexClaudeCursorGemini CLI

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

3

许可证

MIT

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: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

简介

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

SKILL.md

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

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

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安装前确认

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