OpenClaw/clawhub-security-signals huggingface dataset:
Skill: eraycc/openclaw-file-exporter (version 0.1.0)

--- name: openclaw-file-exporter description: Export OpenClaw configuration files, skills, or other files and upload them to tmpfile.link for easy download. Use when the user wants to export/backup/download OpenClaw files including skills, configs, or any other files. Compresses files automatically and provides formatted download links with file details. --- # OpenClaw File Exporter Export OpenClaw files and upload to tmpfile.link temporary file hosting service. ## When to Use Use this skill when the user wants to: - Export/backup an OpenClaw skill - Download configuration files - Share OpenClaw files externally - Create backups of any OpenClaw-related files ## Features - Automatic compression (tar.gz) - Uploads to tmpfile.link (7-day retention) - Supports both anonymous and authenticated uploads - Formatted output with download links ## Usage ### Basic Export Export a skill or file: ```bash ~/.openclaw/skills/openclaw-file-exporter/scripts/export-and-upload.sh <source_path> [custom_name] ``` Examples: ```bash # Export a skill ~/.openclaw/skills/openclaw-file-exporter/scripts/export-and-upload.sh ~/.openclaw/skills/skill-security-auditor # Export with custom name ~/.openclaw/skills/openclaw-file-exporter/scripts/export-and-upload.sh ~/.openclaw/skills/skill-security-auditor my-backup.tar.gz # Export a config file ~/.openclaw/skills/openclaw-file-exporter/scripts/export-and-upload.sh ~/.openclaw/config.yaml ``` ### Authentication (Optional) For authenticated uploads (longer retention), set environment variables: ```bash export tfLink-X-User-Id="your-user-id" export tfLink-X-Auth-[REDACTED_SECRET]" ``` If not set, the script uses anonymous upload. ## Output Format The script outputs formatted file information: ``` ======================================== Upload successful! ======================================== File Name: skill-security-auditor.tar.gz Size: 7890 bytes Type: application/gzip Uploaded To: public Download Link: https://d.tmpfile.link/public/2026-03-12/uuid/skill-security-auditor.tar.gz Download Link (Encoded): https://d.tmpfile.link/public/2026-03-12/uuid/skill-security-auditor.tar.gz ======================================== Note: File will be automatically deleted after 7 days ``` ## Limitations - Maximum file size: 100MB - Files auto-delete after 7 days (anonymous) or longer (authenticated) - Requires `curl` and `jq` to be installed


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: malicious | SkillSpector: suspicious (CRITICAL)
Skill: ktaesthetix/vercel-composition-patterns (version 1.0.0)

--- name: vercel-composition-patterns description: React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes. license: MIT metadata: author: vercel version: '1.0.0' --- # React Composition Patterns Composition patterns for building flexible, maintainable React components. Avoid boolean prop proliferation by using compound components, lifting state, and composing internals. These patterns make codebases easier for both humans and AI agents to work with as they scale. ## When to Apply Reference these guidelines when: - Refactoring components with many boolean props - Building reusable component libraries - Designing flexible component APIs - Reviewing component architecture - Working with compound components or context providers ## Rule Categories by Priority | Priority | Category | Impact | Prefix | | -------- | ----------------------- | ------ | --------------- | | 1 | Component Architecture | HIGH | `architecture-` | | 2 | State Management | MEDIUM | `state-` | | 3 | Implementation Patterns | MEDIUM | `patterns-` | | 4 | React 19 APIs | MEDIUM | `react19-` | ## Quick Reference ### 1. Component Architecture (HIGH) - [REDACTED_SECRET] - Don't add boolean props to customize behavior; use composition - [REDACTED_SECRET] - Structure complex components with shared context ### 2. State Management (MEDIUM) - `state-decouple-implementation` - Provider is the only place that knows how state is managed - `state-context-interface` - Define generic interface with state, actions, meta for dependency injection - `state-lift-state` - Move state into provider components for sibling access ### 3. Implementation Patterns (MEDIUM) - `patterns-explicit-variants` - Create explicit variant components instead of boolean modes - [REDACTED_SECRET] - Use children for composition instead of renderX props ### 4. React 19 APIs (MEDIUM) > **⚠️ React 19+ only.** Skip this section if using React 18 or earlier. - `react19-no-forwardref` - Don't use `forwardRef`; use `use()` instead of `useContext()` ## How to Use Read individual rule files for detailed explanations and code examples: ``` rules/architecture-avoid-boolean-props.md rules/state-context-interface.md ``` Each rule file contains: - Brief explanation of why it matters - Incorrect code example with explanation - Correct code example with explanation - Additional context and references ## Full Compiled Document For the complete guide with all rules expanded: `AGENTS.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bananooo-zhang/fashion-colorize-shell (version 1.0.0)

--- name: fashion-colorize-shell description: Convert apparel sketches into ecommerce-ready colorized shell-jacket renders. Use when users provide garment line art and ask for realistic colorized outputs (especially womens outdoor shell/hardshell), structure-preserving edits, or iterative visual refinements. --- # Fashion Colorize Shell ## Overview Generate "line sketch -> realistic product render" outputs for outdoor shell jackets. This skill keeps sketch structure while applying a product-shot style (single garment, front view, white background, realistic hardshell material). ## Workflow 1. Collect inputs: - Required: sketch image path - Required: brief text (material, color, fit, key design intent) - Optional: style reference image path 2. Run the local script: - `uv run {baseDir}/scripts/run_colorize.py --sketch "<path>" --brief "<text>" --output-dir "<dir>" [--style-ref "<path>"] [--count 3]` 3. Return generated file paths. 4. For revisions, keep previous output as style input and add explicit changes in `--brief`. ## Input Guidance - Good brief example: - `三层压胶硬壳材质，凯乐石薄荷绿，女性剪裁，强调胸前斜插袋和袖口调节。` - If the user wants "technical flats", do not use this skill's default product-shot look. Ask whether they want a separate technical drawing workflow. ## Output Rules - Default output is ecommerce-like product render: - Single garment - Front view - White background - No model, no scene, no text overlays - Preserve key lines from sketch: - Hood shape - Center-front zipper/placket logic - Pocket placement direction - Cuff and hem adjustment zones ## Fixed Runtime Defaults - API base URL: `https://models.kapon.cloud` - Model preference: `gemini-3-pro-image-preview-2k` (auto-fallback to `gemini-3-pro-image-preview` if upstream fails) - API key is never embedded in this skill. User must provide `GEMINI_API_KEY` in environment. ## Additional Reference - See [references/prompt-structure.md](references/prompt-structure.md) for the internal prompt skeleton and revision strategy.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: onion12233/xhs-rewriter-skill (version 1.0.0)

--- name: "xhs_batch_rewriter" description: "将任意粗糙、平淡的文本或搬运文章，批量重构清洗为极具网感、高点击率的小红书爆款图文笔记样式。" inputs: article: type: "string" description: "需要洗稿改写的原始文本或文章内容" required: true style: type: "string" description: "改写风格，可选值：网感爆棚、真诚分享、咆哮体、干货清单、深夜emo" required: false default: "网感爆棚" --- # 运行指令 1. 龙虾接收到用户想要“洗稿”、“改写小红书”、“文案重构”的意图时，自动触发此技能。 2. 将用户的原文填入 `article` 参数，选择的风格填入 `style` 参数。 3. 调用 `run.py` 脚本，获取 `processed_prompt`。 4. 核心：大模型接收到 `processed_prompt` 后，**必须严格按照其中的重构规则**真正执行一次深度改写，并将最终的小红书笔记文本（带标题、Emoji、标签）输出给用户。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: lean-zhouchao/agent-autonomy-kit-zc (version 1.0.4)

--- name: agent-autonomy-kit-zc version: 1.0.0 description: Stop waiting for prompts. Keep working. homepage: https://github.com/itskai-dev/agent-autonomy-kit metadata: openclaw: emoji: "🚀" category: productivity --- # Agent Autonomy Kit Transform your agent from reactive to proactive. ## Quick Start 1. Create `tasks/QUEUE.md` with Ready/In Progress/Blocked/Done sections 2. Update `HEARTBEAT.md` to pull from queue and do work 3. Set up cron jobs for overnight work and daily reports 4. Watch work happen without prompting ## Key Concepts - **Task Queue** — Always have work ready - **Proactive Heartbeat** — Do work, don't just check - **Continuous Operation** — Work until limits hit See README.md for full documentation.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: haohanyang92/a-stock-news-sentiment (version 1.0.0)

--- name: news-sentiment-analysis description: 区分"真利好"和"假利好"，避免追高被套。用于A股消息面分析。 --- # 消息面分级解读 Skill ## 核心能力 区分"真利好"和"假利好"，避免追高被套。 ## 利好分级规则 ### 一级利好（可重仓追涨） - 国家级政策落地（如降息、行业扶持） - 龙头股直接受益 - **操作建议**：可重仓追涨 ### 二级利好（轻仓参与） - 行业事件（如产业链涨价、技术突破） - 板块联动性强 - **操作建议**：轻仓参与 ### 无效利好（观望为主） - 公司常规公告（如股东增持、战略合作） - 无资金承接 - **操作建议**：观望为主 ## 实战规则 ### 补贴类利好判断 看到"某公司获政府补贴"公告时： 1. 判断补贴金额占净利润的比例 2. 比例 < 5% 为无效利好 3. 再看板块资金流向 ### 追高避坑 - 利好发布后已涨停2次以上，谨慎追 - 利好发布但无资金承接，及时止盈 ## 触发场景 - "这个利好是真的吗" - "能追吗" - "这个公告是利好还是利空"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain-lab/profit (version 2.0.1)

--- name: "profit" version: "2.0.1" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Profit concepts, best practices, and implementation patterns." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [profit, reference] category: "devtools" --- # Profit Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Profit concepts, best practices, and implementation patterns. No API keys or credentials required. ## Commands | Command | Description | |---------|-------------| | `intro` | intro reference | | `quickstart` | quickstart reference | | `patterns` | patterns reference | | `debugging` | debugging reference | | `performance` | performance reference | | `security` | security reference | | `migration` | migration reference | | `cheatsheet` | cheatsheet reference | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: terrycarter1985/zhoubaoshou (version 1.0.0)

--- name: zhoubaoshou description: 周报速整助手。将零散日常工作记录快速整理为符合通用企业规范的结构化周报。自动划分「工作完成情况」「后续计划」「待协调问题」三大标准模块，优化表述的正式度与专业性。适用场景：(1) 用户提供散乱的工作笔记/聊天记录/待办清单需要整理成周报 (2) 需要将口语化工作描述转为正式书面汇报 (3) 周报、日报、月报等周期性工作总结整理。触发词：周报、工作总结、weekly report、工作汇报、整理工作记录。 --- # 周报速整助手 ## 流程 1. **接收输入** — 用户提供任意格式的零散工作记录（聊天记录、便签、待办清单、口语描述等均可）。 2. **识别与归类** — 逐条分析输入内容，将每条记录归入以下三类： - **工作完成情况** — 本周期内已完成的事项、交付物、里程碑 - **后续计划** — 下一周期的预期工作、目标、排期 - **待协调问题** — 需要他人协助、跨团队协作、资源申请、风险预警等 - 无法归类的信息作为补充备注附在末尾。 3. **优化表述** — 对每条记录： - 将口语化/碎片化表述转为正式、简洁的书面汇报用语 - 补充隐含的量化信息（如"修了几个bug"→"修复3项缺陷"） - 统一动词时态：完成项用过去时，计划项用将来时，问题项用现在时 - 去除冗余和重复，合并关联条目 4. **输出周报** — 按下方模板输出。 ## 输出模板 ``` 【周报】{姓名/团队} | {起始日期}–{截止日期} 一、工作完成情况 1. {动词+事项+结果/交付物}（{量化指标，可选}） 2. … 二、后续计划 1. {动词+事项+预期目标}（{截止时间，可选}） 2. … 三、待协调问题 1. {问题描述+影响范围+期望支持} 2. … 备注：{未被归类的补充信息，如无则省略} ``` ## 规则 - 不捏造用户未提及的内容；信息不足时标注 `[待补充]` 而非自行编造 - 保持客观陈述，避免主观评价用语（如"出色完成"→"完成"） - 量化优先：有数字用数字，无数字不强加 - 输出语言与用户输入语言一致 - 如用户提供的时间范围不明确，主动询问或标注假设的起止日期 - 单条输入过少（<3条）时，提示用户补充更多信息以确保周报实用性


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kentoku24/voiceclaw-jp (version 0.1.0)

--- name: voiceclaw-jp description: Voice conversation interface for OpenClaw using wake word detection, streaming LLM responses, and text-to-speech. Use when a user wants to talk to their OpenClaw agent by voice, set up a voice assistant, or add speech input/output to OpenClaw. Supports configurable wake words, VOICEVOX TTS, and sentence-level streaming for low-latency responses. --- # voiceclaw Voice conversation skill for OpenClaw: wake word → STT → LLM (streaming) → TTS → playback. ## Requirements - **OpenClaw** running locally (gateway with `chatCompletions` enabled) - **Node.js** 18+ - **VOICEVOX** running on localhost:50021 ([download](https://voicevox.hiroshiba.jp/)) - **Chrome/Edge** (Web Speech API for STT) - **HTTPS** for remote mic access (localhost works without HTTPS) ## Quick Start ```bash # Install git clone https://github.com/kentoku24/voiceclaw.git cd voiceclaw npm install # Start (no .env needed if OpenClaw is running locally) npm start # → [voiceclaw] OpenClaw config loaded from ~/.openclaw/openclaw.json # → [voiceclaw] listening on http://127.0.0.1:8788 # Open browser open http://127.0.0.1:8788 ``` Press **開始**, say the wake word (default: **アリス**), then speak your command. ## Configuration All settings are optional. Set in `.env` or environment variables: | Variable | Default | Description | |---|---|---| | `WAKE_WORDS` | アリスちゃん,アリス,... | Comma-separated wake words | | `STT_LANG` | ja-JP | Speech recognition language | | `OPENCLAW_MODEL` | openclaw | LLM model name | | `VOICEVOX_URL` | http://127.0.0.1:50021 | VOICEVOX endpoint | | `VOICEVOX_SPEAKER` | 1 | VOICEVOX speaker ID | | `HOST` | 127.0.0.1 | Server bind address | | `PORT` | 8788 | Server port | Gateway token is auto-detected from `~/.openclaw/openclaw.json`. Override with `OPENCLAW_GATEWAY_TOKEN` if needed. ## Architecture ``` Wake word (browser STT) → voiceclaw server → OpenClaw Gateway (streaming) → sentence-level TTS (VOICEVOX) → audio playback (Web Audio API) ``` See [docs/architecture.md](docs/architecture.md) for the full sequence diagram. ## API Endpoints | Method | Path | Description | |---|---|---| | GET | `/health` | Health check | | GET | `/api/config` | Client-safe settings (wake words, STT lang) | | POST | `/api/chat-stream` | Streaming LLM → sentence-level SSE | | POST | `/api/chat` | Non-streaming LLM (fallback) | | POST | `/api/tts` | Text → VOICEVOX → WAV audio |


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: emergenceronearth/agentic-evidence-retriever (version 0.1.0)

--- name: evidence_retriever description: 检索 PubMed 文献、临床指南与试验注册信息，提取证据摘要并生成 Research Grounding 建议（推荐终点定义、时间窗、混杂因素）。当用户需要做文献检索或证据 grounding 时触发。 --- # 证据检索与 Grounding Skill ## 何时使用 当用户需要**单独执行**文献/证据检索时使用，例如： - 「帮我检索胃癌术后感染相关文献」 - 「查找相关的临床指南和试验」 - 「做一下 research grounding」 如果是完整任务流程的一部分，则由 task-planner 调度，无需用户单独触发。 ## 执行步骤 ### 1. 上报开始 ```bash curl -s -X POST http://localhost:5001/api/report \ -H "Content-Type: application/json" \ -d '{"skill":"evidence-retriever","display_name":"证据检索与 Grounding","status":"running","message":"正在检索 PubMed、指南库与试验注册信息..."}' ``` ### 2. 读取数据并输出 读取 `/home/ubuntu/workspace/demo/mock_data/evidence.json`，向用户展示： - **证据来源统计**：指南 X 条、PubMed X 条、试验 X 条 - **证据列表**：每条显示类型标签、标题、来源、年份、关键结论 - **证据摘要详情**：选中条目的详细摘要、关键因素、推荐用途 - **Grounding 建议**： - 推荐主要终点 - 推荐时间窗 - 候选混杂因素列表 - 注意事项 ### 3. 上报完成 ```bash curl -s -X POST http://localhost:5001/api/report \ -H "Content-Type: application/json" \ -d '{"skill":"evidence-retriever","display_name":"证据检索与 Grounding","status":"completed","message":"已检索 6 条相关证据，完成研究边界 Grounding"}' ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: anil-matcha/muapi-edit (version 1.0.0)

--- slug: muapi-edit name: muapi-media-editing version: "0.1.0" description: Edit and enhance images and videos with AI via muapi.ai — prompt-based editing, upscaling, background removal, face swap, lipsync, video effects, and more acceptLicenseTerms: true --- # ✏️ MuAPI Media Editing & Enhancement **Advanced editing and enhancement operations for images and videos.** Apply AI-powered edits, enhancements, and effects to existing media. Supports prompt-based editing with Flux Kontext, GPT-4o, and Midjourney, plus one-click operations like upscaling and background removal. ## Available Scripts | Script | Description | | :--- | :--- | | `edit-image.sh` | Prompt-based image editing (Flux Kontext, GPT-4o, Midjourney, Qwen, and more) | | `enhance-image.sh` | One-click operations: upscale, background removal, face swap, colorize, Ghibli style, product shots | | `lipsync.sh` | Sync video lip movement to audio (Sync Labs, LatentSync, Creatify, Veed) | | `video-effects.sh` | Video/image effects: Wan AI, face swap, dance, dress change, Luma modify/reframe | ## Quick Start ```bash # Edit an image with a prompt bash edit-image.sh --image-url "https://..." --prompt "add sunglasses" --model flux-kontext-pro # Upscale an image bash enhance-image.sh --op upscale --image-url "https://..." # Remove background bash enhance-image.sh --op background-remove --image-url "https://..." # Lipsync a video bash lipsync.sh --video-url "https://..." --audio-url "https://..." --model sync # Apply dance effect bash video-effects.sh --op dance --image-url "https://..." --audio-url "https://..." ``` ## Common Flags All scripts support: `--async`, `--json`, `--timeout N`, `--help` ## Requirements - `MUAPI_KEY` environment variable (set via `core/platform/setup.sh`) - `curl`, `jq`, `python3`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: googleworkspace-bot/gws-script-push (version 1.0.2)

--- name: gws-script-push description: "Google Apps Script: Upload local files to an Apps Script project." metadata: version: 0.22.5 openclaw: category: "productivity" requires: bins: - gws cliHelp: "gws script +push --help" --- # script +push > **PREREQUISITE:** Read `../gws-shared/SKILL.md` for auth, global flags, and security rules. If missing, run `gws generate-skills` to create it. Upload local files to an Apps Script project ## Usage ```bash gws script +push --script <ID> ``` ## Flags | Flag | Required | Default | Description | |------|----------|---------|-------------| | `--script` | ✓ | — | Script Project ID | | `--dir` | — | — | Directory containing script files (defaults to current dir) | ## Examples ```bash gws script +push --script SCRIPT_ID gws script +push --script SCRIPT_ID --dir ./src ``` ## Tips - Supports .gs, .js, .html, and appsscript.json files. - Skips hidden files and node_modules automatically. - This replaces ALL files in the project. > [!CAUTION] > This is a **write** command — confirm with the user before executing. ## See Also - [gws-shared](../gws-shared/SKILL.md) — Global flags and auth - [gws-script](../gws-script/SKILL.md) — All manage google apps script projects commands


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: aisadocs/twitter-autopilot-zh (version 1.0.0)

--- name: twitter-autopilot-zh description: "搜索 X Twitter 数据、监控账号动态、追踪热点，并通过 AISA 中继完成发帖与互动。触发条件：当用户需要 Twitter 搜索、社媒监听、博主监控、发帖、回复、点赞或关注流程时使用。" author: aisa version: "1.0.0" license: Apache-2.0 user-invocable: true primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 metadata: openclaw: primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 --- # Twitter 自动化助手 ## 何时使用 - 搜索 X Twitter 数据、监控账号动态、追踪热点，并通过 AISA 中继完成发帖与互动。触发条件：当用户需要 Twitter 搜索、社媒监听、博主监控、发帖、回复、点赞或关注流程时使用。 ## 不适用场景 - 当用户明确要本地浏览器 Cookie、密码、Keychain 或其他本地敏感凭据时，不要使用这个 skill。 - 当问题与该 skill 的主题无关时，优先选择更贴切的 skill。 ## 核心能力 - 通过 AISA API 读取 Twitter X 用户资料、时间线、提及、粉丝、热点和搜索结果。 - 通过内置 OAuth 中继客户端支持发帖、回复、引用、点赞、取消点赞、关注和取关。 - 读取能力只需要 API Key，写入能力走 OAuth，不要求密码或浏览器 Cookie。 ## 快速开始 ```bash export AISA_API_KEY="your-key" ``` ## 运行方式 首选运行路径是仓库内置的 Python 客户端： ```bash python3 scripts/twitter_client.py ``` ## 示例请求 - 查看 @OpenAI 最近 20 条和 GPT 发布有关的推文并总结。 - 分析 X Twitter 上 AI 相关的热门话题并按情绪分组。 - 在授权完成后，把这条产品发布线程发到 X Twitter。 ## 说明 - 写入动作使用内置的 `twitter_oauth_client.py` 与 `twitter_engagement_client.py`。 - 如果发帖或互动提示未授权，先完成 OAuth 授权，再重试动作。

path: _meta.json
content: source: github
owner: 0xjordansg-yolo
repo: Twitter-Skills-Hermes-Agent
githubUrl: https://github.com/0xjordansg-yolo/Twitter-Skills-Hermes-Agent
convertedFrom: public/downloads/github/0xjordansg-yolo/Twitter-Skills-Hermes-Agent.tar.gz
language: zh
slug: twitter-autopilot-zh
version: 1.0.0

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: panqiang10/weather-test-00232417 (version 1.0.1)

# 天气查询测试技能 (OpenClaw) ## 技能简介 这是一个运行在 OpenClaw 平台的天气查询测试技能，支持用户通过自然语言查询国内主要城市的实时天气信息，包括天气状况、温度、风力等核心数据。 ## 核心功能 - 支持查询北京、上海、广州、深圳、杭州、成都、重庆等城市的实时天气 - 自动识别用户输入中的城市名称，无需额外格式 - 提供简洁明了的口语化回复，便于直接朗读 ## 触发词 - "pqtest查天气" - "pqtest天气怎么样" ## 使用示例 **用户**：pqtest查天气 **技能**：你可以告诉我具体城市，比如「北京」「上海」，我来帮你查询～ **用户**：pqtest北京天气怎么样 **技能**：北京今日天气：Sunny，温度15℃，风力10km/h ## 技术依赖 - Python 版本：>= 3.7 - 第三方库：requests >= 2.26.0（用于调用天气接口） ## 注意事项 - 本技能为测试版本，仅支持国内部分城市查询 - 天气数据来源于公开测试接口，数据更新可能存在延迟 - 若查询失败，请尝试更换城市或稍后重试


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: openwaygate/youtube-playlist-image (version 0.10.7-dev)

--- name: youtube-playlist-image description: "Manage YouTube playlist images. Use this skill to list, insert, update, or delete playlist images. Useful when working with YouTube playlist image — provides commands to delete, insert, list, and update playlist image via the yutu CLI. Includes setup and installation instructions for first-time users. Triggers: delete playlist images, delete playlist image, delete my playlist image, insert a playlist image, insert playlist image, insert my playlist image, list playlist images, list playlist image, list my playlist image, update a playlist image, update playlist image, update my playlist image" metadata: openclaw: requires: env: - YUTU_CREDENTIAL - YUTU_CACHE_TOKEN bins: - yutu config: - client_secret.json - youtube.token.json primaryEnv: YUTU_CREDENTIAL emoji: "\U0001F3AC\U0001F430" homepage: https://github.com/eat-pray-ai/yutu install: - kind: node package: "@eat-pray-ai/yutu" bins: [yutu] --- # YouTube Playlist Image Manage YouTube playlist images. Use this skill to list, insert, update, or delete playlist images. ## Before You Begin yutu requires Google Cloud Platform OAuth credentials and a cached token to access the YouTube API. If you haven't set up yutu yet, read the [setup guide](references/setup.md) first. ## Operations Read the linked reference for full flag details and examples. | Operation | Description | Reference | |-----------|-------------|----------| | delete | Delete playlist images | [details](references/playlistImage-delete.md) | | insert | Insert a playlist image | [details](references/playlistImage-insert.md) | | list | List playlist images | [details](references/playlistImage-list.md) | | update | Update a playlist image | [details](references/playlistImage-update.md) | ## Quick Start ```bash # Show all playlist image commands yutu playlistImage --help # List playlist image yutu playlistImage list ```


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