User Input
  ↓
┌─────────────────────────────────┐
│ 1️⃣ AI Keyword Analysis          │
│    Extract core keywords and expand related terms │
└─────────────────────────────────┘
  ↓
┌─────────────────────────────────┐
│ 2️⃣ Multi-channel Parallel Search │
│    skills.sh API + SkillHub + GH │
└─────────────────────────────────┘
  ↓
┌─────────────────────────────────┐
│ 3️⃣ Result Merging and Deduplication │
│    Sort by installation count/quality │
└─────────────────────────────────┘
  ↓
Output Recommended Results

User Input
  ↓
Single technology? ("Java", "React", "Docker")
  ├─ Yes → Extract core keywords + domain expansion terms
  └─ No ↓

Technology + domain? ("Java backend", "React mobile")
  ├─ Yes → Split into: Technology + domain, search in parallel
  └─ No ↓

Multiple keywords? ("Kotlin Android backend communication")
  ├─ Yes → Extract all keywords, search in parallel
  └─ No → Single intent, search directly

Final: Merge and deduplicate → Display by category

Analyze user input and extract search keywords.

User Input: "{query}"

**Key Rules**:
- Extract all important keywords, do not miss any
- Perform reasonable English conversion for domain terms
- Each core keyword is independently valuable and needs to be searched separately

Output JSON:
{
  "core": ["all core keywords"],
  "expanded": {
    "domain": ["technology/function domain expansions"],
    "i18n": ["Chinese-English variants"]
  }
}

Example:
Input: "User Authentication"
Output: {
  "core": ["authentication"],
  "expanded": {
    "domain": ["auth", "login", "security", "jwt", "oauth", "session", "token"],
    "i18n": ["user authentication", "login"]
  }
}

Input: "Android Development"
Output: {
  "core": ["android"],
  "expanded": {
    "domain": ["mobile", "kotlin", "java", "jetpack", "compose"],
    "i18n": ["android"]
  }
}

Input: "Kotlin Android Backend Communication"
Output: {
  "core": ["Kotlin", "Android", "backend", "communication", "API"],
  "expanded": {
    "domain": ["server", "networking", "microservice"],
    "i18n": ["kotlin android", "backend communication"]
  }
}

Input: "Python Data Analysis Visualization"
Output: {
  "core": ["Python", "data-analysis", "visualization"],
  "expanded": {
    "domain": ["pandas", "matplotlib", "plotly", "data-science"],
    "i18n": ["data analysis", "data visualization"]
  }
}

# Step 1: Get root directory structure
gh api repos/{owner}/{repo}/contents --jq '.[].name'

# Step 2: Recursively check if each subdirectory contains SKILL.md
gh api repos/{owner}/{repo}/contents/{potential-skill-dir}/{subdir}/SKILL.md

# Step 3: Parse SKILL.md to get name and description
gh api repos/{owner}/{repo}/contents/{skill-path}/SKILL.md --jq '.content' | base64 -d | grep -E "^(name|description):"

# Step 4: Confirm it is a valid skill → Return
{
  "name": "frontend-dev",
  "description": "Full-stack frontend development...",
  "path": "skills/frontend-dev"
}

# Scanned 14 valid skills:
✅ frontend-dev (name + description + SKILL.md)
✅ fullstack-dev (name + description + SKILL.md)
✅ minimax-pdf (name + description + SKILL.md)
...

# Output Format:
📦 MiniMax-AI/skills (14 skills)
   🎯 frontend-dev: Full-stack frontend development...
   🎯 fullstack-dev: Full-stack backend architecture...
   🎯 minimax-pdf: Professional PDF creation...

Analyze the directory structure and identify potential skill directories:

Verification Steps:
1. Check if the directory contains SKILL.md file
2. Parse SKILL.md to see if it has name and description fields
3. Confirm it is a valid skill

Directory Structure:
{gh_api_contents_json}

Return:
{
  "valid_skills": [
    {
      "name": "{skill-name}",
      "description": "{skill-description}",
      "path": "{owner}/{repo}/{skill-path}"
    }
  ]
}

# Keyword: "authentication"

# 1. skills.sh API
curl "https://skills.sh/api/search?q=authentication&limit=20"

# 2. SkillHub CLI
skillhub search authentication

# 3. GitHub
gh search repos "authentication" --topic claude-skill --limit 10

Repository: legout/data-platform-agent-skills
Contains skills:
  - data-science-eda
  - data-science-visualization
  - data-science-feature-engineering

Installation Commands:
  npx skills add legout/data-platform-agent-skills/data-science-eda
  npx skills add legout/data-platform-agent-skills/data-science-visualization

🎯 {skill-name}
   {One-sentence description}

📦 {Source} | 📊 {Installation Count}
Installation: npx skills add {full path}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 Search Results: {Keyword} (Total N items)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

🟢 Official Certification
───────────────────────────────────────
🎯 {skill-1}
   {Description}
   📦 skills.sh | 📊 50,000+
   Installation: npx skills add {owner}/{repo}/{skill-id}

⭐ Community Recommended
───────────────────────────────────────
🎯 {skill-2}
   {Description}
   📦 GitHub | ⭐ 1,000+
   Installation: npx skills add {owner}/{repo}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

#### Multiple Results

---

## Channel Configuration

> 📋 **Full Configuration**: `references/channels.json`

### Search Method Priority

**API > CLI > Web**

Execute search according to the `search_method` field in the configuration file.

---

## Official Priority Principle

Official skills from major companies are displayed first:

- **Anthropic** - Official Claude
- **MiniMax** - Domestic AI major
- **ByteDance** - Official Douyin/Lark
- **Alibaba Qwen** - Official Tongyi Qianwen
- **Vercel Labs** - Official Next.js

Use 🟢 to mark official skills when outputting.

---

## Installation Assistance

```bash
# Check tool status
./scripts/install-helper.sh status

# Install all tools
./scripts/install-helper.sh all

# Install single tool
./scripts/install-helper.sh gh        # GitHub CLI
./scripts/install-helper.sh skillhub  # SkillHub CLI