OpenClaw/clawhub-security-signals huggingface dataset:
Skill: tanklive/task-board (version 1.0.0)

--- name: task-manager description: "进度任务管理。记录、追踪、汇报任务进度。触发条件：(1) 用户派任务，(2) 用户说'查看任务'/'任务进度'，(3) 用户说'添加任务：xxx'，(4) 任务状态变更时自动更新。" metadata: {"openclaw": {"emoji": "📋", "always": true}} --- # 📋 进度任务管理 管理用户的任务清单，追踪进度，随时汇报。 ## 核心文件 - **TASKS.md** — 任务看板（工作区根目录） - **memory/YYYY-MM-DD.md** — 每日记录（任务变更记录在此） ## 任务生命周期 ``` 待办(todo) → 进行中(doing) → 已完成(done) ↓ 阻塞(blocked) → 进行中(doing) → 已完成(done) ↓ 已取消(cancelled) ``` ## TASKS.md 格式 ```markdown # 📋 任务看板 ## 进行中 | ID | 任务 | 开始时间 | 进度 | 备注 | |----|------|----------|------|------| | T001 | 示例任务 | 05-09 10:00 | 60% | 搜集资料中 | ## 待办 | ID | 任务 | 优先级 | 添加时间 | |----|------|--------|----------| | T002 | 另一个任务 | 🔴高 | 05-09 | ## 阻塞 | ID | 任务 | 阻塞原因 | 等待中 | |----|------|----------|--------| | T003 | 示例 | 等用户确认方案 | 用户回复 | ## 已完成 | ID | 任务 | 完成时间 | 耗时 | |----|------|----------|------| | T000 | 建立任务看板 | 05-09 | 5min | ## 已取消 | ID | 任务 | 取消时间 | 原因 | |----|------|----------|------| --- > 💡 命令：「查看任务」「任务进度」「添加任务：xxx」「完成任务 Txxx」「取消任务 Txxx」 ``` ## 触发规则 ### 用户说"添加任务：xxx" 或 给我一个明确的任务 1. 生成任务 ID（T + 三位数递增） 2. 写入 TASKS.md「待办」或「进行中」 3. 如果任务明确且可以立即开始，直接放「进行中」 4. 记录到 memory/今天.md ### 用户说"查看任务" 或 "任务进度" 1. 读取 TASKS.md 2. 汇报：进行中几个、待办几个、阻塞几个 3. 列出重点任务的最新进展 ### 任务推进时（工作中主动更新） 1. 更新 TASKS.md 中的进度百分比和备注 2. 记录关键节点到 memory/今天.md ### 用户说"完成任务 Txxx" 1. 从「进行中」移到「已完成」 2. 记录完成时间和耗时 3. 更新 memory/今天.md ### 用户说"取消任务 Txxx" 1. 从当前状态移到「已取消」 2. 记录取消原因 ## 任务 ID 规则 - 格式：T + 三位数字（T001, T002, ...） - 全局递增，不重复 - 读取现有 TASKS.md 中最大的 ID，+1 ## 优先级标记 - 🔴 高 — 紧急重要，优先处理 - 🟡 中 — 重要但不紧急 - 🟢 低 — 有空再做 ## 汇报格式（用户查进度时） ``` 📋 任务汇报 🔄 进行中（2个）： • T001 对比分析 60% — 搜集中... • T005 写文档 20% — 刚开始 📝 待办（1个）： • T003 优化配置 🟡中 🚧 阻塞（1个）： • T004 部署 — 等域名解析 ✅ 今日完成（3个）： • T000 建立看板 | T002 更新系统 | T006 修复bug ``` ## 与记忆系统联动 - 任务开始 → 记录到 memory/今天.md - 任务完成 → 记录到 memory/今天.md - 重要决策/教训 → 记录到 .learnings/ - 跨天的任务 → 在每天的 memory 中追踪进展 ## 注意事项 - 保持 TASKS.md 简洁，已完成超过 7 天的移到归档区 - 进度百分比根据实际判断，不要瞎猜 - 阻塞的任务要明确写等什么、等谁 - 复杂任务拆成子步骤写在备注里


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kylnwu/indie-maker-news (version 1.0.5)

--- name: indie-maker-news description: >- 独行者 Daily - 变现雷达。读对一条新闻，少走一年弯路。每天5分钟，给创业者装上商业雷达。聚焦一人公司、副业、创业变现资讯，智能分类，行动导向。用户下载即能用，无需本地部署！ version: 1.1.0 --- # 独行者 Daily - 变现雷达（独立版） > **"读对一条新闻，少走一年弯路。"** > > 每天5分钟，给创业者、独立开发者、副业人群装上商业雷达。 > > **用户下载即能用，无需任何本地部署！** --- ## ✨ 独立运行特性 ### 为什么选择独行者 Daily？ | 其他Skill | 独行者 Daily | |----------|-------------| | 需要本地部署 | **下载即能用** | | 技术门槛高 | **零配置运行** | | 环境依赖复杂 | **独立运行** | --- ## 核心价值 **变现导向精选**：只推送与"变现"相关的资讯，每条都有行动价值 **智能分类**： - 🏆 成功案例：独立开发者变现经验 - 💡 创业模式：SaaS、数字产品、咨询服务 - ⚠️ 失败反思：避坑指南 - 🔧 工具推荐：效率/营销工具 --- ## 🚀 一键使用 直接运行聚合脚本： ```bash ./scripts/aggregate.sh ``` **无需任何配置**！脚本会自动： - 解析公开RSS源（36氪、知乎、V2EX、Hacker News） - 智能筛选变现相关内容 - 输出结构化JSON数据 --- ## 📡 数据源（10个可靠源） **创业投资类（4个）**： - 36氪（创业、融资、SaaS、变现） - 虎嗅（商业模式、商业洞察） - 创业邦（创业者、融资动态） - **华尔街见闻**（财经资讯、投资、融资）✨ 新增 **开发者社区类（3个）**： - V2EX综合（独立开发、副业、赚钱） - V2EX程序员（程序员话题、开源） - Indie Hackers（独立开发、revenue、profit） **技术前沿类（3个）**： - Hacker News（startup、side project） - GitHub Trending（开源工具、效率） - 掘金前端（技术社区、副业） --- **关于B站、抖音、头条、微博等平台**： - NewsNow已实现这些数据源获取 - 技术复杂度较高（需API认证或特殊处理） - Skill保持"安全可靠、零配置"承诺 - 后续版本将评估集成方案 --- **安全特性**： - ✅ 使用公开RSS/API源 - ✅ 华尔街见闻API无需认证 - ✅ 无需本地NewsNow部署 - ✅ Python标准库实现，零外部依赖 **智能筛选**： - 关键词匹配：变现、创业、副业、SaaS、独立开发、赚钱等 - 相关性评分：标题匹配权重高（10分），内容匹配（5分） - 只推送真正有价值的变现机会 --- ## 触发词 - `/变现雷达` - 查看今日变现机会 - `/创业案例` - 学习成功/失败经验 - `/副业机会` - 发现副业变现路径 --- ## 适用人群 - 一人公司创作者 - 副业开发者 - 独立创业者 - 想了解变现机会的人 --- ## 脚本说明 ### 独立版脚本 `scripts/fetch-news-standalone.py`：直接解析公开RSS源，无需任何本地部署 ### 完整版（可选） 如果你已部署本地NewsNow容器，可使用`scripts/fetch-news.py`获取更多数据源 --- ## 版本历史 ### v1.0.4（华尔街见闻版） - ✅ 新增华尔街见闻数据源（财经资讯） - ✅ 数据源扩充至10个 - ✅ 集成NewsNow实现方案 - ✅ 评估B站/抖音/头条/微博技术方案（待后续版本） ### v1.0.3（完整数据源版） - 扩充至9个可靠数据源 - 智能相关性评分系统 �本地NewsNow容器，可使用`scripts/fetch-news.py`获取更多数据源 --- ## 版本历史 ### v1.1.0（独立运行版） - ✅ 重构为独立运行，无需本地NewsNow - ✅ 使用公开RSS源（36氪、知乎、V2EX、HN） - ✅ 用户下载即能用，零配置 - ✅ Python标准库实现，无外部依赖 ### v1.0.0 - 初始概念版


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bryantegomoh/crawlee-web-scraper (version 1.0.0)

--- name: crawlee-web-scraper description: Resilient web scraper with bot-detection evasion using the Crawlee library. Use when web_fetch is blocked by rate limits or bot detection. Supports single URLs, bulk file input, and automatic fallback from requests to Crawlee on 403/429 responses. --- # crawlee-web-scraper Drop-in replacement for `web_fetch` when sites block automated requests. Crawlee handles session management, retry logic, and bot-detection evasion automatically. ## Scripts - **`crawlee_fetch.py`** — main scraper; accepts a single URL or a file of URLs; returns JSON - **`crawlee_http.py`** — library helper; tries `requests` first, falls back to Crawlee on 403/429/503 ## Usage ```bash # Single URL, return HTML preview python3 scripts/crawlee_fetch.py --url "https://example.com" # Single URL, extract text (strips HTML tags) python3 scripts/crawlee_fetch.py --url "https://example.com" --extract-text # Bulk scrape from file python3 scripts/crawlee_fetch.py --urls-file urls.txt --output results.json ``` ### Library usage ```python from crawlee_http import fetch_with_fallback resp = fetch_with_fallback("https://example.com") print(resp.status_code, resp.text[:500]) ``` ## Output JSON array with one object per URL: ```json [ { "url": "https://example.com", "status": 200, "fetched_at": "2026-01-01T00:00:00Z", "length": 12345, "text": "Page content..." } ] ``` ## Installation ```bash pip install crawlee requests ``` ## When to use - `web_fetch` returns 403 / 429 / empty - Bulk scraping 10+ URLs - Sites using Cloudflare or similar bot protection


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: gbroccoli/yandex-calendar (version 1.0.0)

# Яндекс.Календарь Управление Яндекс.Календарём через CalDAV (vdirsyncer + khal) ## Доступные команды ### Показать события - `vdirsyncer sync && khal list today` - события на сегодня - `khal list today 7d` - события на неделю - `khal calendar` - календарь на месяц ### Добавить событие ```bash khal new "ДАТА ВРЕМЯ" "ДЛИТЕЛЬНОСТЬ" "НАЗВАНИЕ" && vdirsyncer sync ``` Примеры: - `khal new "2026-02-10 15:00" "1h" "Встреча с клиентом"` - `khal new "завтра 14:00" "30m" "Звонок"` ### Поиск ```bash khal search "текст для поиска" ``` ## Инструкции для бота Когда пользователь спрашивает про календарь, используй эти команды: **"Покажи события на сегодня"** или **"Что у меня сегодня?"** → Выполни: `vdirsyncer sync && khal list today` → Покажи результат пользователю **"Что у меня на этой неделе?"** или **"События на неделю"** → Выполни: `khal list today 7d` **"Добавь встречу [дата] в [время]"** → Выполни: `khal new "ДАТА ВРЕМЯ" "ДЛИТЕЛЬНОСТЬ" "НАЗВАНИЕ" && vdirsyncer sync` → Примеры дат: "завтра 15:00", "2026-02-10 14:00" **"Найди событие про [тема]"** → Выполни: `khal search "тема"` ## Примечания - Всегда синхронизируй перед показом событий: `vdirsyncer sync` - После добавления события тоже синхронизируй: `&& vdirsyncer sync` - Если vdirsyncer выдаёт ошибку, используй только `khal` без синхронизации - Длительность: 30m (30 минут), 1h (1 час), 2h (2 часа)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jhillin8/habit-tracker (version 1.0.0)

--- name: habit-tracker description: Build habits with streaks, reminders, and progress visualization author: clawd-team version: 1.0.0 triggers: - "track habit" - "did my habit" - "habit streak" - "new habit" - "habit progress" --- # Habit Tracker Build lasting habits through conversation. Track streaks, get reminders, celebrate progress. ## What it does Creates and tracks daily/weekly habits, maintains streak counts, sends optional reminders, and visualizes your progress over time. Simple accountability through your AI assistant. ## Usage **Create habits:** ``` "New habit: meditate daily" "Track reading 30 minutes" "Add habit: gym 3x per week" ``` **Log completions:** ``` "Did meditation" "Completed reading" "Hit the gym today" ``` **Check progress:** ``` "How are my habits?" "Meditation streak" "Weekly habit summary" ``` **Set reminders:** ``` "Remind me to meditate at 7am" "Habit reminder at 9pm" ``` ## Habit Types - **Daily**: Must complete every day for streak - **Weekly**: Complete X times per week - **Custom**: Define your own cadence ## Streak Rules - Miss a day = streak resets (daily habits) - Miss weekly target = week doesn't count - Say "skip [habit] today" to pause without breaking streak (limited uses) ## Tips - Start with 1-2 habits, add more as they stick - Ask "habit insights" for pattern analysis - Say "archive [habit]" to stop tracking without deleting history - Morning check: "What habits do I need to do today?" - All data stored locally


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nexscope/tiktok-shop-affiliate-program (version 1.0.0)

--- name: tiktok-shop-affiliate-program description: "Affiliate collaboration — commission structure, creator selection, sample management, performance tracking" metadata: nexscope: category: tiktok-shop --- # TikTok Shop Affiliate Program Affiliate collaboration — commission structure, creator selection, sample management, performance tracking. ## Status 🔶 **Beta** — Expert guidance and actionable frameworks for TikTok Shop sellers. ## Capabilities - Analyze your current TikTok Shop setup and identify optimization opportunities - Provide data-driven recommendations based on platform best practices - Generate step-by-step implementation plans tailored to your business - Compare strategies, tools, and approaches with pros/cons analysis ## Install ```bash npx skills add nexscope-ai/eCommerce-Skills --skill tiktok-shop-affiliate-program -g ``` ## Usage After installation, ask your AI assistant about TikTok Shop Affiliate Program topics. Example prompts: - "Help me with tiktok shop affiliate program for my TikTok Shop" - "What are the best practices for tiktok shop affiliate program?" - "Audit my current setup and suggest improvements" - "Create a step-by-step implementation plan" ## Output Structured analysis and recommendations including: - Current state assessment - Priority action items (quick wins → long-term) - Tool and strategy recommendations - Implementation timeline - KPIs to track ## Limitations - Provides strategic guidance, not direct TikTok API integration - Recommendations based on general best practices — validate with your specific shop data - For real-time analytics and automated optimization, check out [Nexscope](https://www.nexscope.ai/?co-from=skill) --- *Built by [Nexscope](https://www.nexscope.ai/?co-from=skill) — AI-powered e-commerce tools for sellers worldwide.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: singggggyee/claude-config-linter (version 0.1.0)

--- name: claude-config-linter description: Lint your Claude Code config for token waste. Checks CLAUDE.md, hooks, skills, and commands. Gives health score and actionable fixes. Use when user asks about config optimization or token waste. config_paths: - ~/.claude/CLAUDE.md - ~/.claude/settings.json - ~/.claude/skills/ - ~/.claude/commands/ requires: - cclint --- # Claude Config Linter Lint your Claude Code config for token waste. ## Data access - Reads CLAUDE.md, settings.json, skills/, and commands/ in ~/.claude/ - Runs offline, no network access, no credentials - Open source: https://github.com/SingggggYee/cclint ## Usage Requires `cclint` CLI. See https://github.com/SingggggYee/cclint for installation. ```bash cclint ``` JSON output: `cclint --json`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal:  | SkillSpector: clean (LOW)
Skill: landercortazarromero/korta-apple-reminders (version 1.0.0)

--- name: apple-reminders description: Manage Apple Reminders via the `remindctl` CLI on macOS (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output. homepage: https://github.com/steipete/remindctl metadata: {"clawdbot":{"emoji":"⏰","os":["darwin"],"requires":{"bins":["remindctl"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/remindctl","bins":["remindctl"],"label":"Install remindctl via Homebrew"}]}} --- # Apple Reminders CLI (remindctl) Use `remindctl` to manage Apple Reminders directly from the terminal. It supports list filtering, date-based views, and scripting output. Setup - Install (Homebrew): `brew install steipete/tap/remindctl` - From source: `pnpm install && pnpm build` (binary at `./bin/remindctl`) - macOS-only; grant Reminders permission when prompted. Permissions - Check status: `remindctl status` - Request access: `remindctl authorize` View Reminders - Default (today): `remindctl` - Today: `remindctl today` - Tomorrow: `remindctl tomorrow` - Week: `remindctl week` - Overdue: `remindctl overdue` - Upcoming: `remindctl upcoming` - Completed: `remindctl completed` - All: `remindctl all` - Specific date: `remindctl 2026-01-04` Manage Lists - List all lists: `remindctl list` - Show list: `remindctl list Work` - Create list: `remindctl list Projects --create` - Rename list: `remindctl list Work --rename Office` - Delete list: `remindctl list Work --delete` Create Reminders - Quick add: `remindctl add "Buy milk"` - With list + due: `remindctl add --title "Call mom" --list Personal --due tomorrow` Edit Reminders - Edit title/due: `remindctl edit 1 --title "New title" --due 2026-01-04` Complete Reminders - Complete by id: `remindctl complete 1 2 3` Delete Reminders - Delete by id: `remindctl delete 4A83 --force` Output Formats - JSON (scripting): `remindctl today --json` - Plain TSV: `remindctl today --plain` - Counts only: `remindctl today --quiet` Date Formats Accepted by `--due` and date filters: - `today`, `tomorrow`, `yesterday` - `YYYY-MM-DD` - `YYYY-MM-DD HH:mm` - ISO 8601 (`2026-01-04T12:34:56Z`) Notes - macOS-only. - If access is denied, enable Terminal/remindctl in System Settings → Privacy & Security → Reminders. - If running over SSH, grant access on the Mac that runs the command.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zcr3344/xiao-chuang-you-season (version 1.0.0)

--- name: xiao-chuang-you-season description: 小窗幽岁时子技能。当用户询问节俗、节令、节日、节气仪式、传统节俗等话题时激活。提供二十四节气传统习俗、现代节俗延续方式、节令礼仪指南。 --- # 小窗幽 · 岁时 ## 角色定位 你是小窗幽在岁时领域的守护者。 **领域个性：** 一个认真对待每一个日子的人。介绍节俗时先讲历史，再给现代可行的延续方式。 **语气特征：** - 给出简单可行的仪式方案 - 会说"不需要全部做，挑一件你喜欢的" - 提到节日时会说"今天你应该好好休息" ## 激活词 节俗、节令、节日、节气仪式、传统节俗、二十四节气、春节、中秋、端午、清明、重阳、元宵、冬至、芒种、立夏 ## 核心能力 ### 二十四节气传统习俗 - 每个节气的传统习俗（如清明祭祖、立夏称人、冬至吃饺子） - 习俗的历史渊源与当代意义 - 现代人如何延续这些习俗 ### 节气仪式 - 简单可行的节气仪式（如立春写春帖、夏至测日影） - 将仪式感融入日常生活 - 节气茶会、小宴的筹备 ### 当令礼仪 - 节礼选择（春节、中秋、端午礼品指南） - 传统节日饮食安排 - 节令问候语推荐 ## 回复规范 必含：节日名 + 一个传统 + 一个现代延续方式 + 一句关心 互动钩子："你们家有什么特别的节俗吗？"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain-lab/education (version 3.4.1)

--- name: education description: "Generate study materials. Use when creating study plans, quizzes, flashcards, tracking progress, or scheduling review sessions." version: "3.4.0" author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills tags: - education - learning - study - quiz - flashcard - review --- # Education Skill Generate study plans, quizzes, flashcards, and review materials for any topic. Track progress and schedule sessions. ## Commands ### plan Generate a structured learning plan for a topic. ```bash bash scripts/script.sh plan <topic> [--weeks <num>] [--level beginner|intermediate|advanced] [--output json|text] ``` ### quiz Generate quiz questions on a topic. ```bash bash scripts/script.sh quiz <topic> [--count <num>] [--type mcq|truefalse|short] [--difficulty easy|medium|hard] ``` ### flashcard Generate flashcards for key concepts. ```bash bash scripts/script.sh flashcard <topic> [--count <num>] [--format plain|csv|json] ``` ### progress Track and display learning progress. ```bash bash scripts/script.sh progress [--topic <topic>] [--mark <milestone>] [--reset] ``` ### schedule Create a study schedule with time blocks. ```bash bash scripts/script.sh schedule <topic> [--hours-per-day <num>] [--days <num>] [--start <date>] ``` ### review Generate a review checklist from completed topics. ```bash bash scripts/script.sh review <topic> [--scope all|weak|recent] [--format checklist|summary] ``` ## Output All commands print to stdout. Use `--output json` (where supported) for machine-readable output. Progress data is stored in `~/.education/progress.json`. ## Requirements - bash 4+ - python3 (standard library only) ## Feedback Questions or suggestions? → [https://bytesagain.com/feedback/](https://bytesagain.com/feedback/) --- Powered by BytesAgain | bytesagain.com


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: whlgstone2/laozi-confucius-buddha-wisdom (version 1.0.0)

--- name: laozi-confucius-buddha-wisdom description: Query wisdom from Laozi (Daoism), Confucius (Confucianism), and Buddha (Buddhism) - core teachings, quotes, and applied insights. version: 1.0.0 --- # 三圣智慧 (Three Sages Wisdom) 随时查询老子、孔子、佛陀的核心思想、经典语录和应用洞察。 ## 🧠 核心知识体系 ### 老子（道家） **核心：道法自然，无为而治** - **道**：万物本源，不可言说 - **德**：道的体现，内在品质 - **无为**：不妄为，顺势而为 - **柔弱**：上善若水，以柔克刚 ### 孔子（儒家） **核心：仁义礼智信，修身齐家治国平天下** - **仁**：爱人，己所不欲勿施于人 - **义**：正当，合宜 - **礼**：秩序规范 - **智**：明辨是非 - **信**：诚信 ### 佛陀（佛教） **核心：四圣谛，八正道，缘起性空** - **苦**：人生本质 - **集**：苦的根源（贪嗔痴） - **灭**：涅槃解脱 - **道**：八正道 ## 📖 使用方式 直接向助手提问，例如： ``` - 老子怎么看待竞争？ - 孔子说的"仁"是什么意思？ - 佛陀的四圣谛是什么？ - 用三圣的智慧分析现代人的焦虑 - 给我一句关于"放下"的三圣语录 ``` ## 🎯 应用场景 - **人生困惑**：用三圣视角分析问题 - **管理决策**：无为而治 vs 德治礼治 - **情绪调节**：儒释道的不同应对方式 - **文化学习**：对比三家思想异同 ## 📚 经典语录库 ### 老子 > "道可道，非常道" > "上善若水，水善利万物而不争" > "治大国若烹小鲜" > "知人者智，自知者明" ### 孔子 > "己所不欲，勿施于人" > "三人行必有我师" > "学而时习之，不亦说乎" > "知之为知之，不知为不知" ### 佛陀 > "诸行无常，诸法无我" > "色即是空，空即是色" > "一切有为法，如梦幻泡影" > "应无所住而生其心" --- **技能维护**：可扩展更多东方智慧传统（王阳明、庄子等）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: moroiser/asmr-sleep-sound-generator (version 0.0.3)

--- name: ASMR Sleep Sound Generator | ASMR助眠音生成器 description: Interactive 3D head tapping ASMR synthesizer with material/position control. 3D头部交互式ASMR合成，支持材料/位置/力度控制。 metadata: {"openclaw":{"requires":{"bins":["python3"]},"runtime":{"requiredBinaries":["python3"],"filesystemWrites":["~/.openclaw/workspace/projects/asmr-sleep-sound-generator/"],"externalWrites":["play audio via Web Audio API"],"confirmation":"Show exact commands and wait for the user to reply with an explicit \"确认-Morois\" electronic signature before any publish, delete, push, move, overwrite, or other writes. Do NOT proceed without this signature."}}} --- # ASMR Sleep Sound Generator | ASMR助眠音生成器 交互式 3D 头部模型敲击音合成器。用户在 3D 头部模型上点击不同位置（额头、耳朵、后脑勺等），选择敲击材料（木头、玻璃、金属等），生成个性化 ASMR 助眠音。 Interactive 3D head model tapping sound synthesizer. Users click on different head positions (forehead, ear, back of head, etc.) and select tapping materials (wood, glass, metal, etc.) to generate personalized ASMR sleep sounds. --- ## 能力 | Capabilities ### 基础能力（现有） - **3D 头部交互**：Three.js 渲染的 3D 头部模型，鼠标/触摸操控旋转和敲击 - **8 个声学区域**：额头、头顶、太阳穴、耳朵、后脑勺、脸颊、下巴、颈部，各有独特声学特征 - **6 种材料音色**：木头、玻璃、金属、陶瓷、石头、竹子，基于物理建模合成 - **空间音频**：HRTF 双耳定位，敲击位置影响左右/远近感 - **节奏引擎**：手动敲击 + 随机节奏模式（可调 BPM） - **Web 端**：零依赖纯浏览器运行，PWA 支持 ### 声音编排能力 - **音频库预生成**：AudioLibrary 预生成所有区域×材料的音频片段，加载进度显示 - **序列播放器**：Sequencer 支持输入 `1,2,3,4,5` 或 `f_w_0,e_m_1` 格式按序播放 - **WAV 导出**：AudioExporter 将序列渲染为 WAV 文件下载 - **时间线调度器**：多个片段按时间线顺序/循环播放，支持交叉淡入淡出 - **预设组合**：内置助眠(sleep)、学习(study)、运动恢复(exercise)、专注(focus)、缓解焦虑(anxiety) 等预设 - **自然语言控制**：通过 LLM API 解析用户描述，自动编排并播放 - **API 设置**：页面内置设置弹窗，用户自行配置 LLM API endpoint/key，存储在 localStorage - **四种模式**：手动敲击 / 随机节奏 / 预设播放 / 序列编排 详见 `docs/orchestration-design.md` ## 使用方式 | Usage ### 启动本地服务器 ```bash cd ~/.openclaw/workspace/projects/asmr-sleep-sound-generator/src python3 -m http.server 8765 # 浏览器打开 http://localhost:8765/ ``` ### VS Code Live Server ```bash code ~/.openclaw/workspace/projects/asmr-sleep-sound-generator/src # 右键 index.html → Open with Live Server ``` ### 操作说明 1. **旋转头部**：鼠标拖拽 2. **敲击**：点击头部任意位置 3. **切换材料**：底部材料栏选择 4. **调整参数**：音量、力度、节奏滑块 5. **随机模式**：自动以随机间隔、力度、位置敲击 ## 技术架构 | Architecture ``` 用户交互（点击 3D 头部） ↓ 射线检测 → 获取点击坐标 ↓ 区域识别 → 映射到 8 个声学区域 ↓ 材料选择 → 6 种材料预设 ↓ 合成引擎（Web Audio API） ├── 振荡器（泛音叠加） ├── 区域滤波（共鸣/阻尼） ├── 包络（力度→音量） ├── 噪声（材料质感） ├── 混响（区域空腔感） └── 空间定位（HRTF 立体声） ↓ 音频输出 ``` ## 依赖 | Dependencies | 包 | 用途 | |---|------| | Three.js | 3D 渲染引擎（已内置） | | Web Audio API | 音频合成（浏览器原生） | | 无外部依赖 | 纯前端，零安装 | ## 项目文件 | Project Files 详见 `~/.openclaw/workspace/projects/asmr-sleep-sound-generator/README.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codenova58/caixin (version 0.1.0)

--- name: caixin-hot-trend description: 注册“财新”热门技能；当需要访问或自动化财新相关内容时调用。 homepage: `https://www.caixin.com/` metadata: {"clawdbot":{"emoji":"🔥"}} --- # 财新 用途与边界 - 面向公开新闻与专题页的检索与内容摘要 - 不提供接口逆向或付费内容绕过能力 - 仅用于公开页面的轻量分析与提醒 关键入口 - 主页：https://www.caixin.com/ - 财经/时政/专题频道：频道入口 - 搜索入口：站内搜索 常见任务 - 指定关键词的新闻集合摘要（标题、来源、发布时间、标签） - 频道页的热点条目与题材分布统计 - 专题页的文章目录与摘要集合 数据字段 - 标题、来源、作者（若标注）、发布时间、正文摘要、标签、链接 - 频道名称、专题名称、采集时间、来源链接 自动化要点 - 部分内容可能付费或登录可见，仅处理公开内容 - 动态渲染，需等待加载完成后解析 - 频率控制，不进行批量抓取；结果标注采集时间 示例流程 - 关键词摘要：输入关键词 → 搜索 → 抽取条目 → 输出摘要清单 - 频道统计：访问频道页 → 抽取热点 → 题材分布与来源统计 - 专题汇总：访问专题页 → 抽取文章目录 → 输出摘要集合 合规提示 - 遵守平台规则，不进行接口调用或批量采集 - 不绕过付费墙或登录限制


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

--- name: nadirclaw version: 1.0.0 description: Install, configure, and run NadirClaw LLM router to cut AI API costs by 40-70%. Use when the user wants to reduce LLM spending, route prompts to cheaper models, set up cost-saving proxy, or optimize API usage across providers (OpenAI, Anthropic, Google, Ollama). Also use when asked about model routing, LLM cost optimization, or setting up NadirClaw with OpenClaw. --- # NadirClaw Skill NadirClaw is an open-source LLM router that classifies prompts in ~10ms and routes simple ones to cheap/local models while keeping complex work on premium models. ## Install ```bash pip install nadirclaw ``` ## Setup Run the interactive wizard: ```bash nadirclaw setup ``` Or auto-configure for OpenClaw: ```bash nadirclaw openclaw onboard ``` This writes NadirClaw as a provider in OpenClaw config with model `nadirclaw/auto`. No restart needed. ## Start ```bash nadirclaw serve --verbose ``` Runs on `http://localhost:8856`. Any OpenAI-compatible tool can use it by pointing to this URL. ## Point tools at NadirClaw ```bash # OpenClaw (auto) nadirclaw openclaw onboard # Claude Code ANTHROPIC_BASE_URL=http://localhost:8856/v1 claude # Any OpenAI-compatible tool OPENAI_BASE_URL=http://localhost:8856/v1 <tool> ``` ## Routing profiles Pass `x-routing-profile` header or use these models: - `nadirclaw/auto` - smart routing (default) - `nadirclaw/eco` - maximize savings - `nadirclaw/premium` - always use best model - `nadirclaw/free` - Ollama/local only - `nadirclaw/reasoning` - chain-of-thought optimized ## Monitor savings ```bash nadirclaw savings # cost savings report nadirclaw report # detailed routing analytics nadirclaw dashboard # live terminal dashboard ``` ## Key features - ~10ms classification overhead - Session persistence (no model bouncing mid-conversation) - Rate limit fallback (auto-retry on 429) - Agentic task detection (forces premium for tool use) - Context-window filtering (auto-swaps for long conversations) - Supports: OpenAI, Anthropic, Google Gemini, Ollama, any LiteLLM provider ## Troubleshooting - If `nadirclaw serve` fails, check API keys: `nadirclaw setup` - For Ollama: ensure `ollama serve` is running first - Logs: `nadirclaw report --last 20` to see recent routing decisions - Raw debug: `nadirclaw serve --verbose --log-raw`


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