ClawHub

Skill 激活器

Security

Skill 激活器——帮助用户发现自动化需求、匹配已有 Skill、融合生成新 Skill。 解决"装了 OpenClaw 不知道用来做什么"的核心问题。 Use when: (1) User says "帮我看看能自动化什么", "我能用 OpenClaw 做什么", "帮我体检", "激活", "scan my skills" (2) User says "帮我把这几个 Skill 组合起来", "融合 Skill", "fuse skills", "combine skills" (3) User says "我是产品经理/程序员/博主，有什么推荐", "推荐自动化方案" (4) User says "这个 Skill 不够用，能不能增强", "进化 Skill", "upgrade skill" (5) User asks "什么 Skill 适合我", "帮我找需求", "我该装什么 Skill" (6) User mentions "拿着锤子找钉子", "不知道该做什么", "Skill 吃灰了"

Install

openclaw skills install skill-activator

Skill 激活器

"你的 Skill 该醒了。"

Core Workflow

Three-layer process: Discover → Match → Fuse.

Layer 1: Discover Needs (需求发现)

Choose the appropriate discovery mode based on context:

Mode A — Environment Scan (数字生活体检)

  1. Run bash scripts/scan_environment.sh to collect:
    • Installed skills list with descriptions
    • User identity from SOUL.md / USER.md / IDENTITY.md
    • Connected channels (feishu, wecom, telegram, etc.)
    • Workspace state (memory files, heartbeat config)
  2. Analyze scan results to identify:
    • 🟢 Skills actively in use
    • 🟡 Skills installed but underutilized (have the skill, not using it)
    • 🔴 Capability gaps (needs not covered by any installed skill)
  3. Generate personalized activation report with specific, actionable recommendations

Mode B — Role-Based Recommendations (角色推荐)

  1. Identify user's role from SOUL.md or conversation
  2. Read references/role-templates.md for role-specific pain points and automation ideas
  3. Cross-reference with installed skills
  4. Present top 3-5 recommendations ranked by: pain severity × ease of implementation

Mode C — Pain Point Interview (痛点挖掘对话)

  1. Ask user to walk through their daily workflow
  2. Listen for time-wasting patterns, repetitive tasks, context-switching pain
  3. Quantify: "You spend ~X minutes/day on Y — automatable?"
  4. Map each pain point to a concrete Skill combination
  5. Prioritize by time saved per week

Layer 2: Match Skills (智能匹配)

After discovering needs:

  1. Check installed skills that match the need
  2. Search ClawHub for additional skills: clawhub search "<need description>"
  3. Identify gaps — needs no existing skill covers
  4. Present matching plan:
    • ✅ Already have: installed skills that apply
    • 📦 Recommend install: available on ClawHub via clawhub install <name>
    • 🔧 Can fuse: combine existing skills to cover this need
    • 🆕 Need to create: no skill exists, suggest building one

Layer 3: Fuse & Generate (融合生成)

When combining skills into a new workflow:

  1. Read references/fusion-guide.md for fusion patterns and templates
  2. Read each source skill's SKILL.md to understand inputs, outputs, dependencies
  3. Design the pipeline (sequential, fan-out, aggregation, or enhancement)
  4. Generate new fused SKILL.md with proper frontmatter, workflow steps, and error handling
  5. Add any glue scripts to scripts/ if data format conversion is needed
  6. Package with package_skill.py for distribution

Output Format

Activation Report

🔍 Skill 激活报告
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

👤 身份：{role from SOUL.md}
🔌 已连接：{channels}
📦 已安装：{N} 个 Skill

💡 发现 {N} 个自动化机会：

1️⃣ {pain point description}
   ⏱ 预计每周节省：{X} 分钟
   🧩 需要：{Skill A} + {Skill B}
   📊 可行度：⭐⭐⭐⭐⭐
   → [一键激活]

2️⃣ {pain point description}
   ...

🟡 沉睡的 Skill（装了没用）：
   - {skill name}: 它能帮你 {what it does}

📦 推荐安装：
   - {skill name}: 解决 {what problem}
   - 安装命令：clawhub install {name}

Fused Skill Output

When generating a fused skill, output:

  1. The complete SKILL.md content
  2. Any required glue scripts
  3. Installation/usage instructions
  4. Packaging command: package_skill.py <path>

Key Principles

  • Be specific, not generic: "你每周花2小时做周报" > "你可以自动化一些任务"
  • Quantify savings: Always estimate time/effort saved
  • One-click actionable: Every recommendation should be immediately executable
  • Respect what's installed: Prioritize solutions using skills the user already has
  • Progressive: Start with quick wins, then suggest more advanced automations
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