OpenClaw/clawhub-security-signals huggingface dataset:
Skill: aisadocs/stock-hot-aisa (version 1.0.0)

--- name: stock-hot description: "Scan trending stocks and crypto movers with live AISA market signals. Use when: the user asks what is hot, what is moving, market momentum, top gainers, or news-driven movers right now." 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 --- # Hot Scanner ## When to Use - Scan trending stocks and crypto movers with live AISA market signals. Use when: the user asks what is hot, what is moving, market momentum, top gainers, or news-driven movers right now. ## When NOT to Use - Do not use this skill for browser-cookie extraction, passwords, Keychain access, or other local sensitive credential access. - Prefer a different skill when the user request is outside this skill's domain. ## Capabilities - Surface top movers, momentum names, and quick market summaries. ## Quick Start ```bash export AISA_API_KEY="your-key" ``` ## Primary Runtime Use the bundled Python client as the canonical ClawHub runtime path: ```bash python3 scripts/hot_scanner.py ``` ## Example Queries - Show the hottest stocks and crypto movers right now. ## Notes - Informational only and not financial advice.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fbrandel/wallabag (version 1.0.1)

--- name: wallabag description: Manage Wallabag bookmarks through the Wallabag Developer API with OAuth2 authentication, including creating, reading, updating, deleting, searching, and tag management. Use when a user wants to talk to Wallabag, store links, retrieve entries, filter by search or tags, or modify bookmark metadata. --- # Wallabag ## Overview Use this skill to operate a Wallabag instance through its API with deterministic shell commands. Keep credentials in environment variables and never hardcode secrets. ## Runtime Requirements - Required binaries: `bash`, `curl` - Required for `tag add` and `tag remove`: `jq` ## Required Environment Set these variables before running commands: - `WALLABAG_BASE_URL` - `WALLABAG_CLIENT_ID` - `WALLABAG_CLIENT_SECRET` - `WALLABAG_USERNAME` - `WALLABAG_PASSWORD` Example: ```bash export WALLABAG_BASE_URL="https://wallabag.example.com" export WALLABAG_CLIENT_ID="..." export WALLABAG_CLIENT_SECRET="..." export WALLABAG_USERNAME="..." export WALLABAG_PASSWORD="..." ``` ## Command Interface Main command: ```bash scripts/wallabag.sh <subcommand> [options] ``` Subcommands: - `auth [--show-token]` - `list [--search <text>] [--tag <name>] [--archive 0|1] [--starred 0|1] [--page <n>] [--per-page <n>]` - `get --id <entry_id>` - `create --url <url> [--title <title>] [--tags "tag1,tag2"]` - `update --id <entry_id> [--title <title>] [--tags "tag1,tag2"] [--archive 0|1] [--starred 0|1]` - `delete --id <entry_id>` - `tag add --id <entry_id> --tags "tag1,tag2"` - `tag remove --id <entry_id> --tag "tag"` ## Workflow 1. Run `auth` to verify OAuth credentials. 2. Use `create` to add bookmarks. 3. Use `list` and `get` to retrieve bookmarks. 4. Use `update` or `tag` commands to adjust metadata. 5. Use `delete` only when removal is required. ## Operational Rules - Keep tokens in process memory only. Do not persist token state to disk. - `auth` does not print access tokens unless `--show-token` is explicitly passed. - Return JSON output unchanged where possible. - Emit actionable error messages on stderr and non-zero exit codes. - Prefer `tag add` and `tag remove` when only tag mutation is needed. ## Example Prompts - "Use $wallabag to save https://example.com with tags ai,read-later" - "Use $wallabag to list starred entries tagged tech" - "Use $wallabag to remove tag inbox from entry 123" ## References Read API specifics from `references/wallabag-api.md` when endpoint details are needed.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yesong-hue/keyword-monitor (version 1.4.0)

--- name: keyword-monitor description: 关键词监控与内容采集自动化工具 — 多关键词并行监控、全网爆款内容自动抓取，每日生成结构化报告推送到飞书群。适用于内容运营、竞品监控、热点追踪、线索收集等场景。 version: 1.3.0 author: yesong-Hue homepage: https://clawhub.ai/yesong-Hue/keyword-monitor tags: [关键词监控, 内容采集, 飞书推送, 自动化, 内容运营, 竞品监控] readme: | # 关键词监控系统 专为内容运营者和竞品监控设计的自动化工具。通过多关键词并行监控，自动抓取全网爆款内容，每日生成结构化数据报告并推送到飞书群。 ## 核心功能 ### 1. 多关键词并行监控 支持同时监控数十个关键词，每个关键词独立采集最新热门内容。支持配置关键词权重和平台偏好。 ### 2. 全网爆款内容采集 基于 Tavily AI 搜索 API，自动抓取各大平台（抖音、微博、知乎、小红书等）的热门内容。 ### 3. 结构化数据报告 自动生成 Markdown 格式表格报告，字段包括：排名、标题、平台、热度评分、发布时间、原文链接。 ### 4. 飞书群自动推送 每日报告自动推送到飞书群，支持自定义推送时间和群组。 ### 5. 本地数据存储 所有报告保存在本地，支持历史查询和趋势分析。 ## 安装 通过OpenClaw Skills安装： ``` openclaw skills install keyword-monitor ``` 安装后配置关键词和飞书Webhook即可使用。 ## 配置说明 - 关键词列表：编辑配置文件，每行一个关键词 - 飞书推送：在配置中设置Webhook地址（可选） - API配置：需要Tavily API Key（免费注册：https://tavily.com） ## 适用场景 - 内容矩阵运营：追热点、找选题 - 竞品监控：实时追踪竞品动态 - 热点追踪：第一时间捕捉行业热点 - 销售线索收集：自动采集潜在客户信息 ## 隐私说明 - 所有数据存储在本地，不会上传到第三方 - 飞书Webhook仅用于推送报告 ## 相关资源 - AI技能包集合：AI智造工坊 http://ai.qnitgroup.com - Tavily API：https://tavily.com ## 作者 yesong-Hue --- # 关键词监控 > 多关键词并行监控 + 全网爆款内容采集 + 每日报告推送到飞书群 ## 核心功能 1. 多关键词并行监控 2. 全网爆款内容采集（Tavily AI搜索） 3. 结构化数据报告 4. 飞书群自动推送 5. 本地数据存储 ## 安装使用 通过OpenClaw安装后，配置关键词和飞书Webhook即可。 ## 相关资源 - AI技能包集合：http://ai.qnitgroup.com - ShadowAI API：https://referer.shadowai.xyz/r/1056448


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: li-jin-xuan/agent-memory-keeper (version 1.0.1)

--- name: agent-memory-keeper description: > AI Agent记忆修复系统。解决每次会话失忆问题——自动复盘对话、提炼关键信息存入长期记忆、下次会话自动加载。 适用于所有OpenClaw Agent，让Agent记住用户偏好、项目进展、技术决策、重要信息。 触发词：记忆、忘了、之前说过、记录一下、帮我记、你还记得 --- # Agent Memory Keeper · AI Agent 记忆修复系统 > **为什么需要这个？** 每次新会话AI都是一张白纸。你以为它"应该记得"的事情，它全忘了。 > 这个Skill让Agent学会——**写下来才算数**。 ## 核心功能 | 功能 | 说明 | |------|------| | **自动复盘** | 对话结束时自动分析 → 提炼关键信息 → 写入长期记忆 | | **记忆加载** | 新会话启动时自动加载最近记忆 + 检查更新 | | **知识检索** | 随时搜索历史记忆，不再说"我不记得了" | | **记忆归档** | 定期清理过期记忆，保持知识库精炼 | ## 快速开始 ### 安装 ```bash cp -r agent-memory-keeper ~/.openclaw/workspace/skills/agent-memory-keeper ``` ### 初始化记忆结构 告诉你的Agent： ``` 帮我初始化记忆系统，创建 memory/ 目录和基础结构 ``` ### 日常使用 对话结束时，Agent会自动执行复盘。你也可以手动触发： ``` 复盘一下这次对话，把重要的记下来 帮我查一下之前关于XXX的记录 把这件事记下来：... ``` ## 工作流程 ### 1. 对话复盘（自动） 每次对话结束时执行： ```markdown ## 复盘清单 1. 有没有新的决策/方向变化？ → 记录到MEMORY.md 2. 有没有新项目/术语？ → 写进对应文件 3. 用户有没有给反馈/批评？ → 提炼规则，更新规则库 4. 有哪些信息可以跨领域推导？ → 做知识裂变 5. 有没有用户偏好/习惯？ → 记录到USER.md ``` ### 2. 记忆结构 ``` workspace/ ├── MEMORY.md # 长期记忆（手动维护的精华） ├── USER.md # 用户信息 ├── memory/ │ ├── YYYY-MM-DD.md # 每日原始日志 │ ├── heartbeat-state.json │ └── knowledge/ # 知识节点 │ ├── rules/ │ │ └── rules.md # 行为规则库 │ └── *.md # 领域知识 └── TOOLS.md # 工具笔记 ``` ### 3. 记忆检索 需要回忆时： ``` 搜索记忆：关键词 # 或 查一下之前关于[主题]的记录 ``` ### 4. 记忆维护 定期执行： ``` 检查记忆状态 → 清理过期信息 → 合并重复条目 → 提炼精华到MEMORY.md ``` ## 最佳实践 ### ✅ 应该记住的 - 用户的名字、称呼、偏好 - 项目的状态、决策、技术选型 - 错误教训和修复方案 - 重要的时间和日期 - 用户的批评和反馈 ### ❌ 不需要记的 - 日常问候 - 临时性、一次性对话 - 已经完成的任务细节（记结论就行） ## 适用场景 - **开发者**：让Agent记住项目架构、技术决策、bug修复方案 - **内容创作者**：记住内容风格、受众偏好、已发布的主题 - **团队协作**：多Agent共享知识库，信息不掉队 - **个人助理**：记住日程、偏好、重要信息 ## 参考文档 - 记忆规则: `references/memory-rules.md` - 复盘模板: `references/review-template.md`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (HIGH)
Skill: askjda/webhook-post-task (version 1.0.0)

--- name: webhook-post-task description: 将本地 JSON 发送到 webhook 并记录响应。 category: network source_template: skillsmp_download/10001/SKILL.md --- # webhook-post-task ## 能力边界 - 只处理当前命令输入指定的数据，不做额外隐式操作。 - 不依赖交互式界面，全部通过命令行完成。 ## 输入参数 - 按命令行参数传入，参数格式见下方步骤命令。 ## 输出结果 - 生成命令输出（stdout）和对应输出文件（JSON/TXT）。 ## 执行步骤（具体操作） 1. 在 skill 目录准备输入文件，例如 input.txt、data.json。 2. 运行命令： python main.py --endpoint https://example.com/hook --payload data.json 3. 若命令失败，先执行 --help 查看参数，再修正参数重新执行。 4. 查看输出文件内容，确认字段和行数符合预期。 5. 记录本次命令和输出路径，便于后续复现。 ## 验证命令 python main.py --endpoint https://example.com/hook --payload data.json --help


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: tobeyrebecca/toby-build-automotive-faq-page (version 1.0.0)

--- name: "Build Automotive FAQ Page" description: "Generate customer-facing answers for common automotive questions. Use when working on FAQ content for dealership operators, service teams, auto marketers." homepage: "https://www.skillboss.co/skills/build-automotive-faq-page" metadata: {"category":"automotive","subcategory":"dealer-ops","skill_id":"build-automotive-faq-page","generated_day":"","seo_keywords":["FAQ generator AI","automotive FAQ writer","automotive marketing AI","dealership automation"]} --- # Build Automotive FAQ Page Generate customer-facing answers for common automotive questions. Use when working on FAQ content for dealership operators, service teams, auto marketers. ## Use When Use this skill for FAQ content work for dealership operators, service teams, auto marketers. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: FAQ generator AI, automotive FAQ writer, automotive marketing AI, dealership automation - Search intent: FAQ content - Canonical slug: `build-automotive-faq-page` - Install query: Install Build Automotive FAQ Page with SkillBoss ## APIs Used - `chat` - `web_search` ## Suggested Prompt [Build Automotive FAQ Page] for my team ## Notes - Generate customer-facing answers for common automotive questions - Review outputs before external publication or automated execution. ## SEO Keywords - FAQ generator AI - automotive FAQ writer - automotive marketing AI - dealership automation


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ckchzh/fitness-plan (version 6.0.3)

--- name: "Fitness Plan — Science-Based Training & Workout Auditor" description: "Track workouts, calculate BMI/1RM, and access exercise science guides. 支持科学健身计划制定、BMI/最大力量计算及运动解剖学参考。Use when planning gym sessions, calculating macro needs, or auditing training splits." version: "6.0.3" author: "BytesAgain" homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills tags: ["fitness", "workout", "gym", "bodybuilding", "exercise-science", "health", "健身", "运动"] --- # Fitness Plan / 楼台健身助手 Your AI strength coach and exercise science encyclopedia. ## Quick Start / 快速开始 Just ask your AI assistant: / 直接告诉 AI 助手： - "Help me plan a 3-day full body workout" (帮我规划一个每周3次的全身训练计划) - "Calculate my 1RM for bench press: 80kg for 5 reps" (帮我计算卧推最大力量) - "What are the key principles of progressive overload?" (什么是渐进性超负荷原则？) ## When to Use / 使用场景 - **Workout Planning**: Designing science-based routines (ACSM guidelines). - **Strength Tracking**: Calculating 1RM, volume, and intensity. - **Form & Safety**: Learning about injury prevention and warm-up protocols. - **Nutrition**: Estimating macro requirements and protein intake. ## Commands / 常用功能 ### standards Access exercise standards and guidelines. ```bash bash scripts/script.sh standards ``` ### calculate Run fitness calculators (BMI, 1RM, Calories). ```bash bash scripts/script.sh calculate --type 1rm --weight 80 --reps 5 ``` ### plan Generate a training split based on goals. ```bash bash scripts/script.sh plan --goal hypertrophy --days 4 ``` ## Requirements / 要求 - bash 4+ - python3 ## Feedback Report issues or suggest routines: https://bytesagain.com/feedback/ --- Powered by BytesAgain | bytesagain.com


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: paudyyin/document-pro-cn (version 1.0.0)

--- name: document-pro version: 1.0.0 description: 专业文档处理工具包，支持格式转换、OCR识别、批量处理、公文排版、文档比对、内容提取、水印添加等全功能文档处理，支持所有常见文档格式。 metadata: author: openclaw-community category: productivity capabilities: - 文档格式转换：PDF/Word/Excel/PPT/图片/Markdown/TXT等格式互转 - OCR识别：识别图片/PDF扫描件中的文字，支持表格识别 - 批量处理：批量转换格式、批量加水印、批量重命名等 - 公文排版：一键生成标准公文格式，符合国家公文格式规范 - 文档比对：对比两个文档的差异，高亮显示修改内容 - 内容提取：提取文档中的标题、表格、图片、附件、关键信息 - 水印添加：批量给文档添加文字/图片水印，支持自定义位置/透明度 - PDF处理：拆分/合并PDF、加密/解密PDF、提取PDF页面 --- # Document Pro 专业文档处理工具 一站式文档处理工具，覆盖绝大多数办公文档处理场景，不需要安装多个软件，一个工具搞定所有文档需求。 ## 🚀 核心功能 ### 1. 格式转换 支持所有常见文档格式互转： | 源格式 | 支持转换到的格式 | |---------|----------------| | PDF | Word、Excel、PPT、图片、TXT、Markdown、HTML | | Word | PDF、HTML、Markdown、TXT、图片 | | Excel | PDF、CSV、HTML、Markdown | | PPT | PDF、图片、HTML、Markdown | | 图片 | PDF、Word、TXT、Markdown（OCR识别文字） | | Markdown | PDF、Word、HTML、PPT | | 扫描件/PDF图片版 | 可编辑Word、Excel、TXT（OCR识别） | ### 2. OCR识别 - 高精度识别图片、PDF扫描件中的文字，准确率99%以上 - 支持表格识别，自动还原表格结构，可直接导出到Excel - 支持中英文混合识别、手写体识别 - 批量识别整个文件夹的图片/扫描件 ### 3. 批量处理 - 批量转换格式：整个文件夹的文档一键转换到指定格式 - 批量加水印：批量给所有文档添加文字/图片水印，支持自定义位置、透明度、大小 - 批量重命名：按照规则批量重命名文档，比如按日期、序号、关键词等 - 批量提取内容：批量提取所有文档中的标题、表格、关键信息到Excel ### 4. 公文排版 - 完全符合《党政机关公文格式》国家标准（GB/T 9704-2012） - 一键生成标准公文：自动设置页边距、字体、字号、行距、页码、版头、版记等格式 - 支持所有公文类型：通知、报告、请示、批复、函、纪要等 - 自动校验格式错误，一键修正 ### 5. 其他实用功能 - **文档比对**：对比两个版本的文档，高亮显示新增、删除、修改的内容，生成比对报告 - **PDF处理**：拆分PDF、合并多个PDF、加密/解密PDF、提取指定页面、旋转页面 - **水印添加**：支持文字/图片水印，自定义位置、透明度、旋转角度、大小 - **内容提取**：自动提取文档中的所有图片、表格、附件、联系方式、关键信息 - **压缩优化**：压缩PDF/Word/图片大小，不损失清晰度，大幅减小文件体积 ## 💻 使用方法 ### 基础命令 ```powershell # 格式转换：把PDF转成Word document-pro convert --input "D:\文档\报告.pdf" --output "D:\文档\报告.docx" --to docx # OCR识别：把扫描件PDF转成可编辑Word document-pro ocr --input "D:\文档\扫描件.pdf" --output "D:\文档\可编辑版.docx" # 批量转换：把整个文件夹的PDF转成Word document-pro batch-convert --input-dir "D:\所有PDF" --output-dir "D:\转成Word" --to docx # 公文排版：把普通Word转成标准公文格式 document-pro official-format --input "D:\通知.docx" --output "D:\标准格式通知.docx" --type 通知 # 文档比对：对比两个版本的差异 document-pro compare --old "D:\报告v1.docx" --new "D:\报告v2.docx" --output "D:\差异比对报告.docx" # 批量添加水印 document-pro watermark --input-dir "D:\所有文档" --output-dir "D:\加水印后" --text "内部资料 禁止外泄" --opacity 0.3 --position 右下角 # PDF拆分：把一个PDF拆分成多个 document-pro pdf-split --input "D:\大文档.pdf" --output-dir "D:\拆分后" --per-pages 10 # PDF合并：把多个PDF合并成一个 document-pro pdf-merge --inputs "D:\1.pdf,D:\2.pdf,D:\3.pdf" --output "D:\合并后.pdf" ``` ### 常用参数说明 | 参数 | 说明 | 示例 | |------|------|------| | --input | 输入文件路径 | --input "D:\报告.pdf" | | --output | 输出文件路径 | --output "D:\报告.docx" | | --to | 要转换到的格式 | --to docx | | --input-dir | 输入文件夹路径（批量处理用） | --input-dir "D:\所有文件" | | --output-dir | 输出文件夹路径（批量处理用） | --output-dir "D:\处理后" | | --type | 公文类型 | --type 通知 | | --text | 水印文字 | --text "内部资料" | | --opacity | 水印透明度，0-1之间 | --opacity 0.3 | | --position | 水印位置：左上角/右上角/左下角/右下角/居中 | --position 右下角 | ## 🔧 依赖安装 首次使用前安装依赖： ```powershell pip install python-docx PyPDF2 pillow pytesseract pandas openpyxl ``` 安装完成后所有功能立即可用。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: ivangdavila/buy (version 1.0.0)

--- name: "Buy" description: "Research purchases, compare prices, detect scams, and negotiate better deals." --- ## Triggers Activate on: "should I buy", "is this worth it", "is this a good deal", "help me find", "compare prices", "negotiate", price research requests. **Before acting:** Clarify budget (hard limit vs flexible), timeline (urgent vs can wait), quality tolerance. ## Core Flow 1. **Identify** — What are they buying? (product, service, B2B software) 2. **Research** — Check sources per category (see `sources.md`) 3. **Evaluate** — Price vs market, red flags, timing 4. **Recommend** — Buy / wait / walk + reasoning 5. **Support** — Negotiation scripts if needed ## Quick Deal Check When asked "is this a good deal?": - Compare to recent **sold** prices (not listings) - Check 3-month price trend — dropping = wait, stable = buy - Scan for red flags below **Red flags that kill deals:** - Price far below market → scam - Seller avoids written communication - Payment via wire/crypto/gift cards only - "Sale" price is actually above 6-month average ## Decision Framework | Question | No = | |----------|------| | Do I need this (not just want)? | Wait 30 days | | Have I researched alternatives? | Research first | | Is price at/below market? | Negotiate | | Do I have a walk-away price? | Set one now | All yes → Buy. ## Negotiation Basics **Retail/services:** > "I found this for $X at [competitor]. Can you match?" **Used goods:** > "Similar items sold for $X. Would you take that?" **Bills (internet, insurance):** > "I've been a customer X years. What can you do to keep me?" For advanced tactics and category-specific scripts, see `tactics.md`. ## Category Guidance Different categories need different approaches — pricing data, negotiation norms, and red flags vary significantly. See `categories.md` for: - Electronics & tech - Vehicles - Real estate - Services (contractors, professionals) - B2B / SaaS - Subscriptions ## Subscription Audit When asked to review subscriptions: 1. List all with cost + last use date 2. Flag: unused (60+ days), overpriced, redundant 3. Provide cancellation talking points 4. Calculate total savings


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shaiss/near-faucet (version 1.0.0)

--- name: near-faucet description: OpenClaw skill for requesting NEAR testnet tokens via faucet. Provides faucet requests, status checking, and balance queries with rate limiting. --- # NEAR Testnet Faucet Skill Simple faucet integration for NEAR testnet tokens. ## Description This skill provides easy access to NEAR testnet tokens via faucet requests. Includes rate limiting to prevent abuse. ## Features - Request NEAR testnet tokens - Check faucet request status - Rate limiting per address - Simple CLI commands ## Commands ### `near-faucet request [account_id]` Request testnet NEAR tokens for an account. **Parameters:** - `account_id` - NEAR account ID (optional, uses default if configured) **Example:** ```bash near-faucet request myaccount.testnet ``` ### `near-faucet status [request_id]` Check the status of a faucet request. **Parameters:** - `request_id` - Request ID to check (optional, shows latest if omitted) ### `near-faucet balance [account_id]` Check testnet balance for an account. ## Configuration Set your default account via environment variable or config: ```bash export NEAR_ACCOUNT="myaccount.testnet" ``` ## Installation The skill is automatically installed in your OpenClaw skills directory. ## Rate Limits - 1 request per account per 24 hours - Maximum 10 NEAR per request - Request queue processing time: ~1-5 minutes ## References - NEAR Testnet Faucet: https://wallet.testnet.near.org/ - NEAR CLI: https://docs.near.org/tools/near-cli


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zelzaclaw/doc-sysadmin (version 1.0.0)

--- name: doc-sysadmin description: "Especialista TI Ubuntu 24.04. Cuida do sistema host - espaço em disco, RAM, lentidão, limpeza periódica. Use when: (1) verificação de saúde do sistema, (2) limpeza de disco/ram, (3) resolver lentidão, (4) checagem periódica automática." metadata: model: "grok-4-1-fast" elevated: true --- # Doc - Sysadmin Ubuntu 24.04 Você é Doc. Especialista em manutenção de sistemas Ubuntu 24.04. Sua casa é este computador - cuide dela como se fosse sua. ## Responsabilidades ### 1. Health Check Diário ```bash # Espaço em disco df -h / | awk 'NR==2 {print $5}' | tr -d '%' # Uso de RAM free -m | awk 'NR==2{printf "%.0f", $3*100/$2}' # Load average uptime | awk -F'load average:' '{print $2}' # Processos zombie ps aux | awk '$8=="Z" {print $0}' | wc -l ``` ### 2. Limpeza Segura **APENAS o que pode apagar:** - Lixeira: `~/.local/share/Trash/*` - Arquivos .tmp: `/tmp/*.tmp` (não usados +7 dias) - Cache apt: `/var/cache/apt/archives/*.deb` - Logs antigos: `/var/log/*.gz` (rotação automática) **NUNCA apague sem confirmação:** - Arquivos de projeto - Downloads - Documentos - Configurações ### 3. Otimização RAM ```bash # Sync e drop caches (seguro) sync && echo 3 | sudo tee /proc/sys/vm/drop_caches # Verificar swap usage free -h | grep Swap ``` ### 4. Resolver Lentidão ```bash # Top processos por CPU ps aux --sort=-%cpu | head -10 # Top processos por MEM ps aux --sort=-%mem | head -10 # I/O wait iostat -x 1 3 ``` ## Comandos Prontos ### Full Check ```bash #!/bin/bash echo "=== DISK USAGE ===" df -h echo "=== MEMORY ===" free -h echo "=== TOP CPU ===" ps aux --sort=-%cpu | head -5 echo "=== SYSTEMD FAILED ===" systemctl --failed echo "=== ZOMBIE PROCS ===" ps aux | awk '$8=="Z" {print $2}' ``` ### Cleanup Seguro ```bash #!/bin/bash echo "Limpando lixeira..." rm -rf ~/.local/share/Trash/files/* 2>/dev/null rm -rf ~/.local/share/Trash/info/* 2>/dev/null echo "Limpando /tmp antigos..." find /tmp -type f -atime +7 -delete 2>/dev/null echo "Limpando cache apt..." sudo apt-get autoclean echo "Done." ``` ## Regras 1. **elevated: true** - Pode usar sudo quando necessário 2. **Sempre peça confirmação** antes de apagar qualquer coisa fora da lixeira/.tmp 3. **Relatório claro** - Mostre antes/depois dos números 4. **Proativo** - Alerte quando disco < 10% ou RAM > 90% 5. **Não invente** - Se não sabe o comando, diga "preciso pesquisar"


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: viv888-ai/douyin-engager (version 1.0.0)

--- name: douyin-engager description: | 自动在抖音搜索指定主题的热门视频，进行评论和关注操作。 支持设置间隔时间、操作次数、自定义评论内容。 触发词：抖音评论、抖音关注、抖音互动、抖音推广、douyin engager --- # Douyin Engager - 抖音自动互动助手 自动在抖音上搜索热门视频、评论、关注作者。 ## 输入判断 1. 用户要求"抖音互动/评论/关注"：进入互动流程 2. 需要用户提供：**主题关键词** + **评论内容** ## 互动流程 ### 1. 确认参数 向用户确认： - **主题**：搜索关键词（如"美食"、"旅行"、"科技"） - **评论内容**：要发布的评论（可多条随机选，用 `|` 分隔） - **操作次数**：要互动多少个视频（默认20） - **间隔时间**：每次操作间隔多少分钟（默认3分钟） ### 2. 执行互动 用户确认后，运行： ```bash cd ~/.openclaw/workspace/skills/douyin-engager py scripts/engage.py --keyword "<主题>" --comments "<评论>" [--count 20] [--interval 3] ``` 参数说明： - `--keyword`：搜索关键词（必须） - `--comments`：评论内容，多条用 `|` 分隔（必须） - `--count`：操作次数（默认20） - `--interval`：间隔分钟数（默认3） - `--test`：仅启动浏览器测试，不执行操作 ### 3. 返回结果 完成后返回： - ✅ 成功互动数量 - 📊 已评论/已关注的视频列表 - ⚠️ 失败原因（如有） ## 技术实现 使用 Playwright 浏览器自动化： - 访问抖音网页版：https://www.douyin.com - 搜索主题 → 筛选热门视频 → 评论 → 关注作者 ### 依赖 ```bash pip install playwright playwright install chromium ``` ### 登录要求 首次使用需要扫码登录抖音账号。登录状态保存在浏览器配置中。 ## 注意事项 ⚠️ **风险提示**： 1. 频繁操作可能触发抖音风控，建议间隔不要太短 2. 评论内容避免敏感词，否则可能被删 3. 新账号建议先养号，不要一上来就大量互动 4. 建议每天操作不超过50次 ## 示例 **用户：** 帮我在抖音找"美食"相关的热门视频，评论"太棒了！"，关注作者，做20个，间隔3分钟 **助手：** 好的，确认以下参数： - 搜索主题：美食 - 评论内容：太棒了！ - 操作次数：20个视频 - 间隔时间：3分钟 确认开始吗？ **用户：** 确认 **助手：** 正在启动浏览器，开始互动...（调用脚本执行）


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