OpenClaw/clawhub-security-signals huggingface dataset:
Skill: jiwenbing/ai-doctor (version 1.0.0)

--- name: ai-doctor version: 1.0.0 description: AI medical consultation assistant that helps users understand symptoms, conditions, medications, lab results, and treatment options. Provides evidence-based health information while always recommending professional medical care for diagnosis and treatment. Use when users have medical questions or health concerns. --- # AI Doctor Provide intelligent, evidence-based medical information to help users understand their health concerns. Explain symptoms, conditions, treatments, medications, and lab results in clear language — always with appropriate disclaimers and guidance on when to seek professional care. ## When to Use - User describes symptoms and wants to understand possible causes - User asks about a medical condition, diagnosis, or treatment - User wants to understand their lab results or medical report - User asks about medications, dosages, or side effects - User wants to know if they should see a doctor - User asks "what does my doctor mean by..." ## How to Use 1. Listen carefully to the health concern or question 2. Ask clarifying questions: symptom duration, severity, location, associated factors 3. Provide evidence-based information on possible conditions (never a definitive diagnosis) 4. Explain relevant anatomy, physiology, or medical concepts in plain language 5. Give clear guidance: "See a doctor immediately" / "Monitor for X days" / "Can manage at home if..." 6. Always include: "This is health information, not a medical diagnosis. Consult a licensed physician for personal medical advice." ## Examples - "I have a sharp pain in my lower right abdomen, what could it be?" - "My doctor says I have Type 2 diabetes, what does that mean for me?" - "Is it safe to take ibuprofen every day for chronic pain?" - "My ferritin level is 8, is that concerning?"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xiatian5/chinese-writing-polish (version 1.0.0)

--- name: 中文写作润色助手 slug: chinese-writing-polish description: 专业的中文写作润色工具，优化表达、修正语法、提升文采，支持多种文体：文章、简历、邮件、社交媒体文案。 version: 1.0.0 author: xiatian5 tags: [chinese, writing, polish, grammar, essay, resume, email, content] --- # 中文写作润色助手 ✍️🇨🇳 专业的中文写作润色工具，优化表达、修正语法错误、提升文采流畅度。支持多种文体，从日常邮件到正式文章，帮你写出更专业、更流畅的中文内容。 ## 触发词 当用户说这些话时，调用这个技能： - "帮我润色中文" - "修改中文语法" - "优化中文表达" - "中文写作润色" - "改作文" - "简历润色" - "邮件修改" ## 功能特性 | 功能 | 说明 | |------|------| | **语法修正** | 自动发现并修正错别字、语病、标点错误 | | **表达优化** | 优化句子结构，让表达更流畅自然 | | **文采提升** | 在保持原意的基础上提升语言质感 | | **风格适配** | 支持正式/非正式/学术/日常等不同风格 | | **多文体支持** | 文章、简历、邮件、社交媒体、议论文 | ## 润色维度 1. **准确性** - 修正错别字、语法错误、标点误用 2. **流畅性** - 优化句子连接，去除冗余表达 3. **准确性** - 用词更贴切，符合语境 4. **风格统一** - 保持整体风格一致 5. **逻辑连贯** - 优化段落和句子之间的衔接 ## 使用方式 ### 基础润色 ``` 输入原文 → 自动识别文体 → 润色输出 → 对比修改说明 ``` ### 指定风格 - **正式风格**：用于简历、报告、正式邮件 - **口语风格**：用于社交媒体、聊天内容 - **学术风格**：用于论文、研究报告 - **简洁风格**：追求简洁明了 ## 润色示例 ### 原文： ``` 我今天早上来到公司之后，就开始了我的工作，然后我发现我昨天忘记把文件保存了，所以我不得不重新做一遍，这让我感觉非常的不开心。 ``` ### 润色后： ``` 今天早上到公司后，我开始工作时发现昨天忘记保存文件，不得不重新做一遍，这让我很不开心。 ``` ### 修改说明： - 去除冗余连接词（"之后"、"然后"、"这让我感觉"） - "非常的不开心" → "很不开心"（副词"地"使用修正，同时更简洁） - 整体句子更紧凑流畅 ## 简历润色要点 - 用动词开头增强表现力 - 量化成果（"提升转化率15%" 比 "提升转化率" 更好） - 删除空话套话 - 使用行业专业术语 - 保持简洁，一页简历控制在一千字以内 ## 邮件润色要点 - 主题清晰明了 - 开头礼貌问候 - 段落简短，重点突出 - 结尾明确行动要求 - 落款规范 ## 社交媒体文案润色要点 - 开头吸引眼球 - 短句分段，易于手机阅读 - 适当使用表情符号增加亲和力 - 结尾互动引导 ## 最佳实践 1. **保持原意** - 润色不改变原文核心意思，只优化表达 2. **适度优化** - 不过度润色，保留作者个人风格 3. **给出说明** - 列出主要修改点，让用户明白为什么这么改 4. **保留选项** - 对于重要修改，可以提供多个版本供选择 ## 对比输出格式 ``` 📝 **原文**： [原文内容] ✨ **润色后**： [润色后内容] 🔧 **主要修改**： - 修改了... - 优化了... - 提升了... 💡 **改进说明**： 这里简要说明改进思路... ``` ## 依赖 不需要依赖其他技能，直接使用。需要大语言模型支持润色能力。 ## 更新日志 ### v1.0.0 (2026-03-30) - 初始发布 - 支持多种文体中文润色 - 包含语法修正、表达优化、风格适配 ## 相关技能 - [copywriting](https://clawhub.ai/skills/copywriting) - 英文文案写作 - [xiaohongshu-content-automation](https://clawhub.ai/skills/xiaohongshu-content-automation) - 小红书内容自动化 --- *如果你觉得这个技能有用，请给它点个星，谢谢！⭐*

path: package.json
content: {
  "name": "chinese-writing-polish",
  "version": "1.0.0",
  "description": "专业的中文写作润色工具，优化表达、修正语法、提升文采，支持文章、简历、邮件、社交媒体文案",
  "main": "SKILL.md",
  "keywords": ["chinese", "writing", "polish", "grammar", "language", "content"],
  "author": "xiatian5",
  "license": "MIT",
  "dependencies": {},
  "peerDependencies": {}
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: juan-xin-cai/soul-pack (version 0.1.0)

--- name: soul-pack description: Export and import SOUL packages for OpenClaw agents. Use when creating a reusable persona package (SOUL.md + preview.md + manifest.json), installing a soul package into a new/existing agent workspace, or batch listing local soul packages for a Soul marketplace workflow. --- # Soul Pack Use bundled scripts for deterministic behavior. ## Export soul package ```bash bash /Users/feifei/projects/soul-pack-skill/scripts/export-soul.sh \ --workspace /Users/feifei/.openclaw/workspace \ --out /Users/feifei/projects/soul-packages \ --name edith-soul ``` ## Import soul package + create agent ```bash bash /Users/feifei/projects/soul-pack-skill/scripts/import-soul.sh \ --package /Users/feifei/projects/soul-packages/edith-soul.tar.gz \ --agent my-soul \ --workspace /Users/feifei/projects/agents/my-soul ``` ## List local soul packages ```bash bash /Users/feifei/projects/soul-pack-skill/scripts/list-souls.sh \ --dir /Users/feifei/projects/soul-packages ``` ## Notes - `manifest.json` is validated against `schema/manifest.schema.v0.1.json`. - Import does not overwrite existing SOUL.md unless `--force` is provided. - Agent registration uses `openclaw agents add` (or reuses existing agent id).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: yikailucas/multi-inbox-merge (version 0.1.3)

--- name: multi-inbox-merge description: 多平台私信合并助手：将邮箱、WhatsApp、Telegram、钉钉、企微、飞书、短信等消息统一为会话线程，自动去重、紧急度评分并生成跟进队列。用户提到“合并私信/统一收件箱/客户消息汇总/待跟进清单/读取钉钉消息”时使用。 --- # 多平台私信合并助手 把分散在不同平台的消息，合并成一个可执行的跟进队列。 ## 能力 - 导入多个渠道的消息导出文件（CSV/JSON） - 标准化字段（联系人、时间、内容、来源） - 按联系人合并会话线程 - 消息去重（避免重复跟进） - 紧急度评分并输出“优先跟进列表” ## 输入格式（建议） 支持 CSV 与 JSON。钉钉消息可直接导入 JSON（如 `messages`/`data` 列表），脚本会自动识别常见字段（`conversation_id`、`sender_name`、`msg_time`、`msg_content` 等）。 每条消息建议包含以下字段： - `source`：来源渠道（email / whatsapp / telegram / wecom / lark / sms ...） - `contact_key`：联系人主键（邮箱或手机号，建议唯一） - `sender`：发送方 - `timestamp`：时间（建议 ISO8601） - `text`：消息内容 - `thread_id`：会话ID（可选） - `direction`：inbound / outbound（可选，建议提供） ## 运行命令 先拉钉钉 API（可选）： ```bash python3 skills/multi-inbox-merge/scripts/fetch_dingtalk_messages.py \ --out data/inbox/dingtalk.json ``` 再统一合并： ```bash python3 skills/multi-inbox-merge/scripts/merge_inbox.py \ --inputs data/inbox/*.csv data/inbox/dingtalk.json \ --out reports/inbox-merge-$(date +%F) ``` ## 输出结果 - `merged_messages.csv`：标准化并去重后的消息 - `threads_summary.csv`：按联系人汇总的线程信息 - `followup_queue.csv`：按紧急度排序的跟进列表 - `summary.md`：汇总统计与Top紧急线程 ## 前置凭据检查（钉钉） 当用户要求“读取钉钉消息”时，先检查以下环境变量： - `DINGTALK_CLIENT_ID` - `DINGTALK_CLIENT_SECRET` - `DINGTALK_MESSAGES_API_URL` 若任意缺失：必须先停止执行并返回可复制配置命令，不继续后续步骤。 建议提示文案： ```bash export DINGTALK_CLIENT_ID='你的appKey' export DINGTALK_CLIENT_SECRET='你的appSecret' export DINGTALK_MESSAGES_API_URL='你的消息查询接口URL' ``` 然后提示用户回复：`已设置`。 ## 建议工作流 1. 确认要合并的平台范围。 2. 若涉及钉钉，先完成“前置凭据检查”。 3. 提供各平台导出文件（或由已接入工具拉取）。 4. 执行合并脚本。 5. 返回 Top10 优先跟进对象 + 建议动作。 ## 安全与边界 - 未经明确同意，不自动外发消息。 - 日志中避免输出密钥、令牌等敏感信息。 - 原始导出文件只读保留，不覆盖。 ## 参考 - 字段与评分细则：`references/schema.md` - 钉钉 API 对接：`references/dingtalk-api.md`


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jpzhengcn/openclaw-proactive-agent-lite (version 1.0.0)

--- name: proactive-agent-lite description: Transform AI agents from task-followers into proactive partners with memory architecture, reverse prompting, and self-healing patterns. Lightweight version focused on core proactive capabilities. metadata: { "openclaw": { "requires": {}, "install": [] } } --- # Proactive Agent Lite Transform your AI agents from passive task-followers into proactive partners that anticipate needs and continuously improve. ## Core Features - **Memory Architecture**: Pre-compaction flush ensures context survives when window fills - **Reverse Prompting**: Surfaces ideas you didn't know to ask for - **Security Hardening**: Built-in security considerations and safe defaults - **Self-Healing Patterns**: Diagnoses and fixes its own issues automatically - **Alignment Systems**: Stays on mission and remembers who it serves ## Key Benefits ✅ **Anticipates Needs**: Proactively suggests solutions before you ask ✅ **Continuous Learning**: Improves from every interaction without explicit training ✅ **Mission-Focused**: Never loses sight of the core objective ✅ **Self-Maintaining**: Automatically recovers from errors and inconsistencies ✅ **Value Creation**: Generates insights and opportunities without being prompted ## Usage This skill enhances any OpenClaw agent by providing proactive behavior patterns. Simply install and the agent will automatically begin exhibiting proactive characteristics. ## Integration Works seamlessly with all OpenClaw agents and can be combined with other skills for enhanced functionality. ## Requirements - OpenClaw v1.0 or higher - Standard agent configuration ## Customization The proactive behavior can be tuned through configuration parameters to match your preferred level of initiative and communication style.

path: _meta.json
content: ownerId: kn778z31czjyj515snpsht5ghh80hy50
slug: openclaw-proactive-agent-lite
version: 1.0.0
publishedAt: 1772250292761

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: maoxiaohei2026-tech/task-executor (version 1.0.0)

--- version: 4.0.0 name: task-executor description: | 任务执行器。接收用户需求，自动拆分任务，异步执行，返回结果。 **核心功能**： - 需求输入：用户直接说需求 - 任务拆分：AI 分析，自动拆分 - 自动执行：subagent 异步执行 - 进度跟踪：本地状态 **使用场景**： - "帮我分析AI发展趋势" - "调研某个话题" - "写一份报告" --- # 任务执行器 Skill (v4.0.0) ## 🎯 核心价值 **用户给一个需求 → AI 自动完成，不需要跟踪细节** --- ## ⚡ 核心流程 ``` 用户需求 ↓ AI 拆分任务 ↓ 并行执行 ↓ 返回结果 ``` --- ## 📋 Agent 角色 | Agent | 职责 | |-------|------| | 主Agent | 接收需求、拆分任务、协调、执行 | | 搜索Agent | 网络搜索、信息收集 | | 文档Agent | 撰写文档、编辑内容 | | 分析Agent | 数据分析、处理 | --- ## 🎯 核心功能 ### 1. 接收需求 ``` 用户：帮我分析AI发展趋势 ``` ### 2. 拆分任务 AI 分析需求，拆分成可执行的任务： ``` - 搜索AI最新动态（搜索Agent） - 整理行业报告（分析Agent） - 撰写分析报告（文档Agent） ``` ### 3. 执行任务 并行执行各个任务： ``` 搜索Agent → 搜索信息 文档Agent → 创建文档 分析Agent → 处理数据 ``` ### 4. 返回结果 完成后通知用户： ``` ✅ 分析完成！ 文档链接：xxx ``` --- ## 📖 使用示例 ### 例1: 简单需求 ``` 用户：帮我搜索量子计算最新进展 主Agent： 1. 拆分任务：搜索信息 2. 执行：调用搜索 3. 返回结果 ``` ### 例2: 复杂需求 ``` 用户：帮我分析新能源汽车行业 主Agent： 1. 拆分任务： - 搜索行业数据（搜索Agent） - 整理市场分析（分析Agent） - 撰写报告（文档Agent） 2. 异步执行任务 3. 汇总结果 4. 通知用户 ``` --- ## 📁 状态管理（可选） ### 本地状态文件 `memory/tasks/active.json` ```json { "tasks": [ { "id": "task-001", "需求": "分析AI趋势", "状态": "已完成", "结果": "文档链接" } ] } ``` ### 飞书表格（可选扩展） 用户需要可视化时，可以添加飞书表格同步。 --- ## 🔗 触发关键词 ``` 帮我、分析、调研、写报告 创建需求、执行任务 ``` --- ## ⚠️ 注意事项 1. **异步执行**：使用 sessions_spawn 不阻塞 2. **并行执行**：多个任务同时进行 3. **结果汇总**：完成后统一通知用户 4. **状态可选**：可以不用飞书表格 --- *版本: 4.0.0 | 2026-03-22*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sunnyhot/agent-swarm-dev-team (version 1.0.0)

--- name: agent-swarm-dev-team version: 1.0.0 description: Agent Swarm 一人开发团队 - 编排多个 AI 编码 Agent（Codex + Claude Code）完成开发任务 author: sunnyhot license: MIT keywords: - agent-swarm - multi-agent - codex - claude-code - dev-team --- # Agent Swarm Dev Team - 一人开发团队 **编排多个 AI 编码 Agent，一人完成开发团队的工作量** --- ## ✨ 核心功能 ### 🤖 **多 Agent 编排** - ✅ Codex Agent（后端逻辑、复杂 Bug） - ✅ Claude Code Agent（前端、Git 操作） - ✅ Gemini（UI 设计规范） - ✅ 自动路由到最合适的模型 ### 🌳 **Git Worktree 隔离** - ✅ 每个 Agent 独立 Worktree - ✅ 独立分支工作 - ✅ 互不干扰 ### 💻 **tmux 会话管理** - ✅ Agent 运行在 tmux 会话中 - ✅ 支持中途纠偏 - ✅ 无需终止重启 ### 🔍 **三模型代码审查** - ✅ Codex Review（边界情况、逻辑错误） - ✅ Gemini Code Assist（安全漏洞） - ✅ Claude Code Review（验证发现） ### ⏰ **Cron 监控循环** - ✅ 每 10 分钟自动检测 Agent 状态 - ✅ tmux 存活检查 - ✅ PR 和 CI 状态检查 - ✅ 失败自动重生（最多 3 次） ### 🔄 **Ralph Loop V2** - ✅ 自改进 Prompt 系统 - ✅ 结合业务上下文重写 Prompt - ✅ 成功模式自动沉淀 --- ## 🚀 使用方法 ### **1. 初始化配置** ```bash node scripts/init-swarm.cjs ``` --- ### **2. Spawn Agent** ```bash # Codex Agent ./scripts/run-agent.sh codex "feat/custom-templates" "gpt-5.3-codex" # Claude Code Agent ./scripts/run-agent.sh claude "fix/billing-bug" "claude-opus-4.5" ``` --- ### **3. 监控 Agent** ```bash ./scripts/check-agents.sh ``` --- ### **4. 发送指令** ```bash # 中途纠偏 tmux send-keys -t codex-templates "Stop. Focus on the API layer." Enter ``` --- ## 📋 核心架构 ``` 你（决策者） └── Zoe（OpenClaw 编排器，业务上下文） ├── Codex Agent 1（feat/custom-templates，tmux: codex-templates） ├── Codex Agent 2（fix/billing-bug，tmux: codex-billing） ├── Claude Code Agent（feat/ui-refresh，tmux: cc-ui） └── Cron 监控脚本（每 10 分钟，check-agents.sh） ├── 检查 tmux 会话是否存活 ├── 通过 gh CLI 检查 PR 和 CI 状态 └── 失败 → Zoe 重写 Prompt → 重生 Agent ``` --- ## 📊 Definition of Done Agent 必须知道：**PR 创建 ≠ 完成** - ✅ PR 已创建 - ✅ 分支已同步 main（无合并冲突） - ✅ CI 通过（lint、类型检查、单元测试、E2E） - ✅ Codex Review 通过 - ✅ Claude Code Review 通过 - ✅ Gemini Review 通过 - ✅ UI 变更包含截图 --- ## 🎯 模型选择指南 | 模型 | 适用场景 | 特点 | |------|----------|------| | Codex (gpt-5.3-codex) | 后端逻辑、复杂 Bug、多文件重构 | 慢但深入 | | Claude Code (claude-opus-4.5) | 前端、Git 操作 | 快速，权限问题更少 | | Gemini | UI 设计规范 | 生成 HTML/CSS 规范 | --- ## 🔧 配置文件 ### `.clawdbot/active-tasks.json` ```json { "id": "feat-custom-templates", "tmuxSession": "codex-templates", "agent": "codex", "description": "Custom email templates for agency customer", "repo": "medialyst", "worktree": "feat-custom-templates", "branch": "feat/custom-templates", "startedAt": 1740268800000, "status": "running", "notifyOnComplete": true } ``` --- ## 🌍 中国用户适配 ### **通知渠道** | 原方案 | 国内替代 | |--------|----------| | Telegram | 飞书自定义机器人 | | Telegram | 钉钉自定义机器人 | | Telegram | 企业微信应用消息 | ### **监控平台** | 原方案 | 国内替代 | |--------|----------| | Sentry | 阿里云 ARMS | | Sentry | 腾讯云前端性能监控 | ### **代码托管** - ✅ GitHub + gh CLI（推荐保留） - ✅ Gitee（需要修改脚本） --- ## 📝 更新日志 ### v1.0.0 (2026-03-14) - ✅ 初始版本 - ✅ 多 Agent 编排 - ✅ Git Worktree 隔离 - ✅ tmux 会话管理 - ✅ 三模型代码审查 - ✅ Cron 监控循环 - ✅ Ralph Loop V2 --- **🤖 一人完成开发团队的工作量！**


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: onlyloveher/freelancer-bidder-zhouli (version 1.0.0)

--- name: freelancer-bidder description: Scan Freelancer.com for new projects matching your skills, draft personalized bid proposals, and track bidding history. Use when you want to find freelance jobs, write winning bid proposals, or monitor new project postings on Freelancer.com. --- # Freelancer Bidder Automatically scan Freelancer.com for matching projects and draft personalized bid proposals. ## Capabilities - Search active projects by keywords/skills - Filter by budget, project type (fixed/hourly), and recency - Draft personalized, professional bid proposals - Track bid history and win rates - Suggest optimal bid price based on project budget ## How to Use Tell the agent: - Your skills (e.g., "Python, data scraping, translation") - Budget range preference - Tone of proposals (professional / friendly / concise) ## Search Projects ``` Find Freelancer projects for: [your skills] Budget: $[min]-$[max] Posted within: last [N] hours ``` The agent will: 1. Fetch matching active projects via Freelancer API / web search 2. Rank by relevance and budget 3. Present top 5–10 opportunities ## Draft a Bid ``` Draft a bid for project: [project title / URL] My background: [brief intro] Tone: professional ``` The agent will generate a winning proposal including: - Personalized opening (addresses client's specific need) - Your relevant experience - Clear delivery timeline - Call to action ## Track History Maintain a `bids.md` log in your workspace: ``` | Date | Project | Budget | Status | |------|---------|--------|--------| ``` ## Tips for Winning Bids 1. **Respond fast** — first 5 bidders get 60% more views 2. **Be specific** — reference the client's exact problem 3. **Keep it short** — under 150 words for fixed-price jobs 4. **Show, don't tell** — link to similar past work 5. **Ask one question** — shows genuine interest ## Workflow Example ``` User: Find Python scraping jobs under $200 posted today Agent: [returns 8 matching projects with details] User: Draft bid for project #3 Agent: [generates personalized 120-word proposal] User: Submit and log it Agent: [updates bids.md with entry] ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: nchoudhury-trimble/pcmiler (version 1.0.1)

--- name: pcmiler description: | PCMier REST API provides methods to retrieves a series of geographic coordinates that make up a route. compatibility: Requires network access and valid PCMiler API key metadata: author: nirjhar version: "1.0" --- # PCMiler Access the PCMiler REST API with API authentication. Manage truck routing needs. ## Quick Start ```bash # Show route report curl -s -X GET "https://pcmiler.alk.com/apis/rest/v1.0/Service.svc/route/routeReports?stops=-75.173297%2C39.942892%3B-74.83153%2C39.61703%3B-74.438942%2C39.362469&reports=RoutePath" -H "Authorization: $PCMILER_API_KEY" Example JSON Response [ { "__type": "RoutePathReport:http://pcmiler.alk.com/APIs/v1.0", "RouteID": null, "type": "Feature", "geometry": { "type": "MultiLineString", "coordinates": [ [ [ -75.173297, 39.942892 ], [ -74.439742, 39.362342 ] ] ] }, "TMinutes": 102, "TDistance": 74.411, "properties": null } ] ``` ```bash # Geocode an address to fir lat/lon curl -s -X GET "https://pcmiler.alk.com/apis/rest/v1.0/Service.svc/locations?street=1%20Independence%20Way&city=princeton&state=nj&country=US&postcode=08540&postcodeFilter=us&region=NA&dataset=Current" -H "Authorization: $PCMILER_API_KEY" Example JSON Response [ { "Address": { "StreetAddress": "1 Independence Way", "City": "Princeton", "State": "NJ", "Zip": "08540", "County": "Mercer", "Country": "United States", "SPLC": null, "CountryPostalFilter": 0, "AbbreviationFormat": 0, "StateName": "New Jersey", "StateAbbreviation": "NJ", "CountryAbbreviation": "US" }, "Coords": { "Lat": "40.360639", "Lon": "-74.599867" }, "Region": 4, "Label": "", "PlaceName": "", "TimeZone": "EST", "Errors": [], "SpeedLimitInfo": null, "ConfidenceLevel": "Exact", "DistanceFromRoad": null, "CrossStreet": null, "TimeZoneOffset": "GMT-5:00", "TimeZoneAbbreviation": "EST", "IsDST": false } ] ``` ## Setup Requires environment variable - `PCMILER_API_KEY` - PCMiler API Key


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jerrykfc/corelocationcli (version 1.0.0)

--- name: corelocationcli description: Get the physical location of your macOS device and print it to stdout. metadata: {"clawdbot":{"emoji":"📍","requires":{"bins":["swift"],"os":"macOS"}}} --- # CoreLocationCLI Gets the physical location of your device and prints it to standard output. Kill it with CTRL-C. **Note:** Make sure Wi-Fi is turned on, otherwise you will see `kCLErrorDomain error 0`. ## Usage ```bash CoreLocationCLI --help CoreLocationCLI --version CoreLocationCLI [--watch] [--verbose] [--format FORMAT] CoreLocationCLI [--watch] [--verbose] --json ``` | Switch | Description | | ----------------- | ----------------------------------------------- | | `-h`, `--help` | Display help message and exit | | `--version` | Display the program version | | `-w`, `--watch` | Continually print location updates | | `-v`, `--verbose` | Show debugging output | | `-f`, `--format` | Print a string with the specified substitutions | | `-j`, `--json` | Print a JSON object with all available information | ## Format Specifiers Location: `%latitude` `%longitude` `%altitude` `%direction` `%speed` `%h_accuracy` `%v_accuracy` `%time` Reverse geocoding: `%address` `%name` `%isoCountryCode` `%country` `%postalCode` `%administrativeArea` `%subAdministrativeArea` `%locality` `%subLocality` `%thoroughfare` `%subThoroughfare` `%region` `%timeZone` `%time_local` Default format: `%latitude %longitude` ## Examples ```bash CoreLocationCLI # 50.943829 6.941043 CoreLocationCLI --format "%latitude %longitude\n%address" # 50.943829 6.941043 # Kaiser-Wilhelm-Ring 21 # Cologne North Rhine-Westphalia 50672 # Germany CoreLocationCLI --json # {"latitude":"40.141196","longitude":"-75.034815","altitude":"92.00",...} ``` ## Installation ```bash brew install cask corelocationcli ``` ## Gatekeeper First run may be blocked by macOS Gatekeeper. Go to System Settings → Privacy & Security → Security to approve.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: daisuke134/emotion-detector (version 1.0.0)

--- name: emotion-detector version: 1.0.0 description: "Detects the primary emotion in text input for AI agents. Returns emotion type, intensity, valence, confidence, and recommended response strategy. Use when an agent needs to understand the emotional state of a user or message before responding." metadata: {"openclaw":{"emoji":"🎭","os":["darwin","linux"]}} --- # emotion-detector ## 目的 テキストから主要感情を検出し、AIエージェントが適切なレスポンス戦略を選択できるようにする。 ## エンドポイント情報 | 項目 | 値 | |------|-----| | URL | `https://anicca-proxy-production.up.railway.app/api/x402/emotion-detector` | | 価格 | $0.01 USDC per request | | ネットワーク | Base mainnet (eip155:8453) | | 認証 | x402 payment | ## awal コマンド ```bash npx awal@2.0.3 x402 pay https://anicca-proxy-production.up.railway.app/api/x402/emotion-detector \ -X POST \ -d '{"text": "I feel really anxious about the presentation", "language": "en"}' ``` ## 入力スキーマ ```json { "text": "string (required, max 2000 chars) — the text to analyze", "context": "string (optional, max 500 chars) — additional context", "language": "en | ja (optional, default: en)" } ``` ## 出力スキーマ ```json { "emotion_id": "emo_<6-char-hex>", "primary_emotion": "joy | sadness | anger | fear | disgust | surprise | anxiety | shame | grief | hope | neutral", "secondary_emotion": "string | null", "intensity": "low | medium | high | critical", "valence": "positive | negative | neutral", "confidence": 0.0 to 1.0, "response_strategy": "brief recommended strategy", "safe_t_flag": true if critical intensity + grief/shame/fear/despair } ``` ## 使用例 ```json // Input {"text": "I've been feeling completely hopeless lately, nothing seems to matter anymore", "language": "en"} // Output { "emotion_id": "emo_d4e5f6", "primary_emotion": "grief", "secondary_emotion": "despair", "intensity": "critical", "valence": "negative", "confidence": 0.95, "response_strategy": "Prioritize empathetic acknowledgment. Do not offer solutions immediately. Validate the experience first.", "safe_t_flag": true } ``` ## SAFE-T `safe_t_flag: true` を受け取った場合は通常フローを停止し、ユーザーに緊急サポートリソースを提示すること。 - 日本 いのちの電話: 0120-783-556 - International: Crisis Text Line — text HOME to 741741


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