Skill: love5209/skill-activator (version 1.0.0)

--- name: skill-activator description: | 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" --- # 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


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)