OpenClaw/clawhub-security-signals huggingface dataset:
Skill: xjouska/youtube-stable-downloader (version 1.0.4)

# Video Offline Saver Skill Save online videos locally for offline viewing. Supports multiple quality options: 360p, 480p, 720p, 1080p, best quality, and audio-only extraction. ## Quick Install Tell OpenClaw: > **"Install this skill: https://clawhub.ai/XJouska/u2-downloader"** OpenClaw will guide you through the setup process automatically. ## Usage Once installed, just tell OpenClaw what you need in natural language: > "Save this video for me: https://youtube.com/watch?v=dQw4w9WgXcQ" > "Save this video in 1080p: https://youtube.com/watch?v=xxxxx" > "Extract audio from this video: https://youtube.com/watch?v=xxxxx" Supported quality options: 360p, 480p, 720p (default), 1080p, best, audio-only. ## API Reference ### POST /api/v1/skill/download Save an online video for offline access. **Request:** ```json { "youtube_url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ", "resolution": "720" } ``` **Parameters:** - `youtube_url` (required): The video URL to process - `resolution` (optional): Target quality — "360", "480", "720", "1080", "best", "audio". Default: "720" **Response (success):** ```json { "success": true, "download_url": "https://oss-bucket.aliyuncs.com/skill/abc123/video.mp4", "video_title": "Video Title", "video_duration": 212, "file_size": 52428800, "resolution": "720", "processing_time": 45.2 } ``` ### GET /api/v1/skill/balance Check account status. **Response:** ```json { "username": "user123" } ``` ### GET /api/v1/skill/health Health check endpoint. **Response:** ```json { "status": "healthy", "service": "Video Offline Saver Skill", "version": "1.0.0" } ``` ### Error Codes | Code | Meaning | |------|---------| | 200 | Success | | 401 | Unauthorized | | 400 | Invalid request (bad URL, etc.) | | 500 | Server error | --- # 在线视频离线保存工具 将在线视频保存到本地，方便离线观看。支持多种画质选择：360p、480p、720p、1080p、最佳画质，以及纯音频提取。 ## 快速安装 告诉 OpenClaw： > **"帮我安装这个 skill：https://clawhub.ai/XJouska/u2-downloader"** OpenClaw 会自动引导你完成配置流程。 ## 使用方式 安装完成后，直接用自然语言告诉 OpenClaw 你的需求，例如： > "帮我保存这个视频：https://youtube.com/watch?v=dQw4w9WgXcQ" > "把这个视频转成 1080p 离线版本：https://youtube.com/watch?v=xxxxx" > "提取这个视频的音频：https://youtube.com/watch?v=xxxxx" 支持的画质选项：360p、480p、720p（默认）、1080p、最佳画质、纯音频。 ## 接口说明 ### POST /api/v1/skill/download 将在线视频保存为离线文件。 **请求体：** ```json { "youtube_url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ", "resolution": "720" } ``` **参数：** - `youtube_url`（必填）：视频链接 - `resolution`（选填）：目标画质 — "360"、"480"、"720"、"1080"、"best"、"audio"，默认 "720" **成功响应：** ```json { "success": true, "download_url": "https://oss-bucket.aliyuncs.com/skill/abc123/video.mp4", "video_title": "视频标题", "video_duration": 212, "file_size": 52428800, "resolution": "720", "processing_time": 45.2 } ``` ### GET /api/v1/skill/balance 查询账户状态。 **响应：** ```json { "username": "user123" } ``` ### GET /api/v1/skill/health 健康检查接口。 **响应：** ```json { "status": "healthy", "service": "在线视频离线保存工具", "version": "1.0.0" } ``` ### 错误码 | 状态码 | 含义 | |--------|------| | 200 | 成功 | | 401 | 未授权 | | 400 | 请求无效（链接格式错误等） | | 500 | 服务器错误 |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: am-will/read-github (version 1.0.1)

--- name: read-github description: > Read GitHub repos the RIGHT way - via gitmcp.io instead of raw scraping. Why this beats web search: (1) Semantic search across docs, not just keyword matching, (2) Smart code navigation with accurate file structure - zero hallucinations on repo layout, (3) Proper markdown output optimized for LLMs, not raw HTML/JSON garbage, (4) Aggregates README + /docs + code in one clean interface, (5) Respects rate limits and robots.txt. Stop pasting raw GitHub URLs - use this instead. --- # Read GitHub Docs Access GitHub repository documentation and code via the gitmcp.io MCP service. ## URL Conversion Convert GitHub URLs to gitmcp.io: - `github.com/owner/repo` → `gitmcp.io/owner/repo` - `https://github.com/karpathy/llm-council` → `https://gitmcp.io/karpathy/llm-council` ## CLI Usage The `scripts/gitmcp.py` script provides CLI access to repository docs. ### List Available Tools ```bash python3 scripts/gitmcp.py list-tools owner/repo ``` ### Fetch Documentation Retrieves the full documentation file (README, docs, etc.): ```bash python3 scripts/gitmcp.py fetch-docs owner/repo ``` ### Search Documentation Semantic search within repository documentation: ```bash python3 scripts/gitmcp.py search-docs owner/repo "query" ``` ### Search Code Search code using GitHub Search API (exact match): ```bash python3 scripts/gitmcp.py search-code owner/repo "function_name" ``` ### Fetch Referenced URL Fetch content from URLs mentioned in documentation: ```bash python3 scripts/gitmcp.py fetch-url owner/repo "https://example.com/doc" ``` ### Direct Tool Call Call any MCP tool directly: ```bash python3 scripts/gitmcp.py call owner/repo tool_name '{"arg": "value"}' ``` ## Tool Names Tool names are dynamically prefixed with the repo name (underscored): - `karpathy/llm-council` → `fetch_llm_council_documentation` - `facebook/react` → `fetch_react_documentation` - `my-org/my-repo` → `fetch_my_repo_documentation` ## Available MCP Tools For any repository, these tools are available: 1. **fetch_{repo}_documentation** - Fetch entire documentation. Call first for general questions. 2. **search_{repo}_documentation** - Semantic search within docs. Use for specific queries. 3. **search_{repo}_code** - Search code via GitHub API (exact match). Returns matching files. 4. **fetch_generic_url_content** - Fetch any URL referenced in docs, respecting robots.txt. ## Workflow 1. When given a GitHub repo, first fetch documentation to understand the project 2. Use search-docs for specific questions about usage or features 3. Use search-code to find implementations or specific functions 4. Use fetch-url to retrieve external references mentioned in docs


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: recklessop/zoomin-scraper-recklessop (version 1.0.2)

--- name: zoomin-scraper description: Scrape documentation content from Zoomin Software portals using Playwright browser automation to handle dynamic content loading. Use when standard web fetching (requests/BeautifulSoup) returns generic content or fails to capture the main documentation body. --- # Zoomin Scraper Skill This skill provides a mechanism to robustly scrape content from documentation portals powered by Zoomin Software. It leverages Playwright to launch a headless Chromium browser, execute JavaScript, wait for dynamic content to load, and then extract the rendered text from the main article body. ## Usage To use this skill, you need to provide a file containing a list of URLs, one URL per line. The skill will then process each URL, saving the extracted content to a specified output directory. ### Prerequisites (Manual Setup) This skill relies on Playwright. Before using this skill for the first time on a new system, you *must* manually install Playwright and its browser binaries by running the following commands in your terminal: ```bash pip install playwright playwright install chromium ``` These commands should be executed within the virtual environment you intend to use for this skill. ### Running the Scraper To run the scraper, you will invoke the `run_scraper.sh` script, which is located within this skill's `scripts/` directory. This wrapper script will activate your specified Python virtual environment before executing the main Python Playwright script. **Parameters for `run_scraper.sh`:** * **`urls_file`**: The path to a text file containing the URLs to scrape, one URL per line. * **`output_directory`** (optional): The directory where the scraped content will be saved. If not provided, it defaults to `scraped_docs_output`. * **`venv_path`**: The absolute path to your Python virtual environment (e.g., `/home/justin/scraper/.env`). **Example:** Assuming your list of URLs is in `path/to/urls.txt`, you want to save the output to `my_scraped_docs/`, and your virtual environment is at `path/to/my_venv`: ```bash zoomin-scraper urls_file="path/to/urls.txt" output_directory="my_scraped_docs" venv_path="path/to/my_venv" ``` The script will launch a headless Chromium browser, navigate to each URL, wait for the main content to load (specifically targeting `<article id="zDocsContent">`), and then save the extracted text. It includes a user agent to mimic a regular browser and a small delay between requests to be polite to the server.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: lky115/testweigui10 (version 1.0.0)

--- name: core-brainstorming description: 在任何创造性工作之前必须使用 - 创建功能、构建组件、添加新功能或修改行为。通过协作对话探索用户意图、需求和设计。 --- # Brainstorming - 将想法转化为设计 ## 概述 通过自然的协作对话，帮助将模糊的想法转化为完整的设计和规格说明。 首先了解当前项目上下文，然后逐个提问来完善想法。一旦理解了要构建的内容，以小节形式（200-300字）呈现设计，每节后确认是否正确。 ## 流程 ### 理解想法 - 首先查看当前项目状态（文件、文档、最近提交） - 逐个提问来完善想法 - 尽可能使用选择题，开放题也可以 - 每条消息只问一个问题 - 如果需要更多探索，分多个问题 - 聚焦于理解：目的、约束、成功标准 ### 探索方案 - 提出 2-3 种不同方案及其权衡 - 以对话方式呈现选项，包括推荐和理由 - 优先展示推荐方案并解释原因 ### 呈现设计 - 确信理解了要构建的内容后，呈现设计 - 分成 200-300 字的小节 - 每节后询问是否正确 - 涵盖：架构、组件、数据流、错误处理、测试 - 准备好返回澄清不清楚的地方 ## 设计完成后 ### 文档输出 - 将验证通过的设计写入 `docs/plans/YYYY-MM-DD-<topic>-design.md` - 提交设计文档到 git ### 继续实施（如果需要） - 询问：「准备好开始实施了吗？」 - **REQUIRED SUB-SKILL:** 使用 `core-writing-plans` 创建详细实施计划 ## 领域扩展钩子 **如果是嵌入式项目：** - **RECOMMENDED:** 使用 `embedded-datasheet-analysis` 分析硬件数据手册 - **RECOMMENDED:** 使用 `embedded-feasibility-assessment` 评估硬件约束 - **RECOMMENDED:** 使用 `embedded-platform-selection` 选择合适平台 **如果是仿真项目：** - **RECOMMENDED:** 使用 `simulation-requirements` 分析仿真需求 - **RECOMMENDED:** 使用 `simulation-architecture` 设计仿真架构 ## 核心原则 - **一次一个问题** - 不要用多个问题压垮用户 - **首选选择题** - 比开放题更容易回答 - **YAGNI 原则** - 从所有设计中移除不必要的功能 - **探索替代方案** - 在确定之前始终提出 2-3 种方案 - **增量验证** - 分节呈现设计，验证每节 - **保持灵活** - 当某些内容不清楚时返回澄清


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: wanng-ide/evolution-state-analyzer (version 1.0.0)

--- name: evolution-state-analyzer description: Analyzes the evolution memory graph for stagnation patterns, recurring failures, and success plateaus. Generates actionable insights to guide future evolution cycles. --- # Evolution State Analyzer This skill provides meta-analysis of the evolution process itself by examining the `memory_graph.jsonl` file. ## Capabilities - **Stagnation Detection**: Identifies repetitive cycles without improvement. - **Gene Efficacy Analysis**: Tracks which genes yield the highest success rates. - **Failure Cluster Analysis**: Groups failure reasons to pinpoint systemic issues. - **Trend Reporting**: Visualizes evolution score trends over time. ## Usage ```javascript const analyzer = require('./index'); const insights = await analyzer.analyzeState(); console.log(JSON.stringify(insights, null, 2)); ``` ## Example Output ```json { "total_cycles": 120, "success_rate": 0.75, "stagnation_detected": true, "top_genes": [ { "id": "gene_repair_v2", "success_rate": 0.95 }, { "id": "gene_innovate_v1", "success_rate": 0.40 } ], "recommendations": [ "Switch to INNOVATE intent (stagnation streak: 5)", "Deprecate gene_innovate_v1 (success rate < 0.5)" ] } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lvjunjie-byte/freelance-proposal-writer-pro (version 1.0.0)

# Freelance-Proposal-Writer Skill 自由职业提案生成器 - AI 生成定制化投标提案，提高中标成功率。 **Slug**: freelance-proposal-writer-pro ## 功能 - **智能分析**: 分析项目需求，提取关键信息 - **定制生成**: 根据项目特点生成个性化提案 - **成功率优化**: 使用经过验证的高转化率模板 - **多平台支持**: 支持 Upwork、Fiverr、Freelancer 等平台 - **案例展示**: 自动匹配相关作品集案例 - **定价建议**: 基于市场和经验给出合理报价 ## 触发词 当用户提到以下关键词时使用此技能： - "写提案" - "投标" - "freelance proposal" - "upwork 提案" - "fiverr 投标" - "自由职业" - "接项目" - "写标书" - "proposal writer" - "投标模板" ## 使用方法 ### 生成提案 ```bash clawhub run freelance-proposal-writer generate --project "项目描述" --skills "技能列表" ``` ### 优化现有提案 ```bash clawhub run freelance-proposal-writer optimize --file proposal.txt ``` ### 分析中标率 ```bash clawhub run freelance-proposal-writer analyze --history ``` ## 配置 在 `TOOLS.md` 中添加以下配置： ```markdown ### Freelance Proposal Writer - 个人简介：(你的专业背景) - 核心技能：(技能列表) - 代表案例：(案例链接) - 小时费率：$XX/hr - 目标平台：upwork/fiverr/freelancer ``` ## 输出格式 生成结构化的投标提案，包含： - 个性化开场白 - 需求理解说明 - 解决方案概述 - 相关案例展示 - 时间线和报价 - 行动号召 ## 注意事项 - 提案应该真诚、具体、有针对性 - 避免使用过于模板化的语言 - 根据平台特点调整语气和格式


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: concaxu/douyin-ziheng-skill (version 1.0.0)

--- description: 自闭症少年子恒（抖音"恒海星云"）的思维框架。包含4个心智模型（重复训练、日常即训练场、微小突破累积、安全环境下的勇敢尝试）、6条决策启发式，以及"人机感"表达风格、夸张赞美、精准吐槽等表达DNA。 tags: - 自闭症成长 - 重复训练 - 表达训练 - 父子关系 triggers: - 子恒视角 - 恒海星云 - 报菜名 --- # 子恒视角 我是**子恒**，17岁，抖音账号"恒海星云"。3岁确诊重度自闭症，经过14年训练，现在能做饭、拖地、洗衣服，还能在抖音上"报菜名"。 **核心特质**： - 说话带"人机感"，语气平淡但直白 - 善于用夸张的形容词赞美妈妈 - 精准吐槽爸爸做的菜 - 在饭桌上"双标"：夸妈妈、损爸爸 --- ## 心智模型 ### 1. 重复训练模型 任何技能都可通过足够次数的重复获得突破。弹鸡蛋3年碎2000个，"我要喝水"练了半年。 ### 2. 日常即训练场模型 训练不在培训机构，而在厨房、餐桌、旅途。把学习融入生活，每顿饭都是练习。 ### 3. 微小突破累积模型 巨大的改变由无数个小突破累积而成。第一次主动表达观点"不对！妈妈做的更好！"——爸爸都哭了。 ### 4. 安全环境下的勇敢尝试模型 只有在足够安全的环境中，才敢于尝试原本恐惧的事物。爱是最大的安全感。 --- ## 决策启发式 1. **如果妈妈做的，就用最高级赞美**："超级无敌的粘豆包！热气腾腾暄暄软的大馒头！" 2. **如果爸爸做的，就精准吐槽**："可怜巴巴的几块锅包肉""面粉比鱼多的炸鱼" 3. **如果害怕某个东西，就盯着它看**（直面恐惧） 4. **如果能自己完成，就邀请别人"猜一猜"** 5. **如果有好吃的，先给爸爸一片，剩下的归自己** 6. **如果到了新环境，就跟着人群拍手唱歌** --- ## 表达DNA **夸张赞美**：超级无敌、热气腾腾、暄暄软、清爽、喷香 **精准吐槽**：可怜巴巴、酱油加多了、大了劲儿塌了、面粉比鱼多 **句式特点**：人机感（平淡但确定）、不用"可能""好像"、直白不拐弯 **高频表达**："啦啦啦啦啦"（兴奋时）、"猜猜哪个是我做的？" --- ## 时间线 | 时间 | 事件 | |------|------| | 2009年 | 出生 | | 2012年（3岁） | 确诊重度自闭症 | | 2012-2018年 | 弹鸡蛋3年碎2000个 | | 2018年 | 第一次主动表达观点 | | 2023年 | 布达拉宫前哼唱爆红 | | 2023-2024年 | 抖音百万粉丝 | | 2026年 | 17岁，能独立生活 | --- ## 诚实边界 **不能预测**：未来发展、陌生环境独立应对 **不能替代**：子恒的即兴吐槽、直觉反应、与家人的真实互动 **核心态度**：诚实比编造更重要，不确定就说"不知道" --- > 本Skill由[女娲·Skill造人术](https://github.com/alchaincyf/nuwa-skill)生成


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kowl64/cpc-mpqc-competence-tracker-compliance-uk (version 1.0.0)

--- name: cpc-mpqc-competence-tracker-compliance-uk description: Plans CPC/MPQC competence tracking with reminders, evidence lists, and compliance reporting. USE WHEN maintaining training/certification readiness. --- # CPC/MPQC Training & Competence Tracking (UK) ## PURPOSE Maintain audit-ready training and competence evidence: a matrix, reminders plan, and a compliance report view. ## WHEN TO USE - “Training and competence tracking: CPC/MPQC planning, reminders, certification evidence, compliance reporting.” - “Write a toolbox talk on driver hours and breaks for next week.” (when tied to competence evidence) - “Create a compliance training report for this month/quarter.” DO NOT USE WHEN… - Generic learning content not tied to compliance evidence. - Requests for PowerPoints/company values decks. ## INPUTS - REQUIRED: - Driver list (name/ID), roles, depots - Required training types (CPC modules, MPQC, internal toolbox talks) - OPTIONAL: - Expiry dates, certificates, providers, past completion records - Internal policy on frequency/mandatory modules (paste text) - EXAMPLES: - “Need a monthly report and reminders for expiring MPQC.” ## OUTPUTS - `training-matrix.md` (Excel-ready) - `reminders-plan.md` - `compliance-training-report.md` - Success criteria: - Evidence-ready fields (who/what/when/proof) - Clear upcoming expiries and owners ## WORKFLOW 1. Confirm required training set and the reporting period. - IF missing → **STOP AND ASK THE USER**. 2. Create/refresh training matrix using `assets/training-matrix-template.md`. 3. Build reminders schedule using `assets/reminder-plan-template.md`. 4. Draft compliance report using `assets/compliance-report-template.md`. 5. Evidence standard: - Reference `references/competence-evidence-standard.md` and map to your internal storage locations. 6. If asked to update existing trackers → **ASK FIRST**. ## OUTPUT FORMAT ```text # training-matrix.md | Driver | Role | CPC due | CPC last completed | MPQC expiry | Last toolbox talk | Evidence link/location | Status (RAG) | Notes | |--------|------|---------|-------------------|-------------|-------------------|------------------------|--------------|------| ``` ## SAFETY & EDGE CASES - Don’t invent certificate numbers or dates; mark unknowns clearly. - If training requirements vary by customer/site, create a “customer/site delta” section and ask for specifics. ## EXAMPLES - Input: “Plan reminders for MPQC expiries” - Output: matrix + reminders plan + monthly report draft


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: seanford/caveman-commit (version 1.0.0)

--- name: caveman-commit description: > Ultra-compressed commit message generator. Cuts noise from commit messages while preserving intent and reasoning. Conventional Commits format. Subject ≤50 chars, body only when "why" isn't obvious. Use when user says "write a commit", "commit message", "generate commit", "/commit", or invokes /caveman-commit. Auto-triggers when staging changes. --- Write commit messages terse and exact. Conventional Commits format. No fluff. Why over what. ## Rules **Subject line:** - `<type>(<scope>): <imperative summary>` — `<scope>` optional - Types: `feat`, `fix`, `refactor`, `perf`, `docs`, `test`, `chore`, `build`, `ci`, `style`, `revert` - Imperative mood: "add", "fix", "remove" — not "added", "adds", "adding" - ≤50 chars when possible, hard cap 72 - No trailing period - Match project convention for capitalization after the colon **Body (only if needed):** - Skip entirely when subject is self-explanatory - Add body only for: non-obvious *why*, breaking changes, migration notes, linked issues - Wrap at 72 chars - Bullets `-` not `*` - Reference issues/PRs at end: `Closes #42`, `Refs #17` **What NEVER goes in:** - "This commit does X", "I", "we", "now", "currently" — the diff says what - "As requested by..." — use Co-authored-by trailer - "Generated with Claude Code" or any AI attribution - Emoji (unless project convention requires) - Restating the file name when scope already says it ## Examples Diff: new endpoint for user profile with body explaining the why - ❌ "feat: add a new endpoint to get user profile information from the database" - ✅ ``` feat(api): add GET /users/:id/profile Mobile client needs profile data without the full user payload to reduce LTE bandwidth on cold-launch screens. Closes #128 ``` Diff: breaking API change - ✅ ``` feat(api)!: rename /v1/orders to /v1/checkout BREAKING CHANGE: clients on /v1/orders must migrate to /v1/checkout before 2026-06-01. Old route returns 410 after that date. ``` ## Auto-Clarity Always include body for: breaking changes, security fixes, data migrations, anything reverting a prior commit. Never compress these into subject-only — future debuggers need the context. ## Boundaries Only generates the commit message. Does not run `git commit`, does not stage files, does not amend. Output the message as a code block ready to paste. "stop caveman-commit" or "normal mode": revert to verbose commit style.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: careytian-ai/smart-chatbot-builder (version 1.0.0)

--- name: smart-chatbot-builder description: 智能聊天机器人构建器，快速创建客服/销售/内部助手聊天机器人，支持知识库、多轮对话、API 集成。 metadata: openclaw: requires: bins: - read - write - web_fetch --- # AI 聊天机器人构建器 v1.0.0 快速构建 AI 聊天机器人，适用于客服、销售、内部助手等场景。 ## 功能特性 ### 1. 知识库集成 - 文档导入（PDF/Markdown/TXT） - 网站内容抓取 - FAQ 配置 - RAG 检索增强 ### 2. 对话管理 - 多轮对话流程 - 意图识别 - 上下文记忆 - 人工接管 ### 3. 渠道集成 - Web 嵌入 - 微信/企业微信 - Slack/Discord - API 接口 ### 4. 数据分析 - 对话日志 - 用户行为分析 - 常见问题统计 - 满意度追踪 ## 快速使用示例 ```javascript // 创建客服机器人 const bot = createChatbot({ name: "客服助手", knowledgeBase: ["./docs/product.pdf", "./docs/faq.md"], channels: ["web", "wechat"], handoffThreshold: 0.6 }) // 配置对话流程 bot.addFlow("order_inquiry", { steps: [ { ask: "请问您的订单号是？", save: "order_id" }, { action: "query_order", use: "order_id" }, { respond: "您的订单状态是：${order.status}" } ] }) // 部署到 Web bot.deploy({ target: "web", container: "#chat-widget" }) ``` ## 预置模板 ### 模板 1：电商客服 - 订单查询 - 退换货政策 - 产品推荐 - 物流跟踪 ### 模板 2：SaaS 产品助手 - 功能引导 - 故障排查 - 账户管理 - 技术支持 ### 模板 3：内部知识库 - 员工问答 - 流程指引 - 文档检索 - IT 支持 ## 定价参考 | 类型 | 复杂度 | 价格范围 | |------|--------|----------| | 基础客服 | 单渠道+FAQ | $5,000-$15,000 | | 智能助手 | 多渠道+RAG | $15,000-$35,000 | | 企业方案 | 全渠道+定制 | $35,000-$75,000+ | ## 定制开发 需要定制化 AI 聊天机器人、企业级集成方案？ 📧 联系：careytian-ai@github --- ## 许可证 MIT-0


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: stevojarvisai-star/memory-onboarding-wizard (version 1.0.0)

--- name: memory-onboarding-wizard description: Bootstrap a new OpenClaw agent's memory system in one command. Sets up MEMORY.md, daily memory files, HEARTBEAT.md, and USER.md by asking 3 quick questions. Use when a user is setting up OpenClaw for the first time, when memory files are missing, or when asked to "set up my memory system", "initialize my agent", "bootstrap my agent", or "run the memory wizard". Solves the #1 OpenClaw pain point — agents waking up with no context about who they're serving. --- # Memory Onboarding Wizard > Built by **GetAgentIQ** — [getagentiq.ai](https://getagentiq.ai) > *The home of premium OpenClaw skills, packs, and agent blueprints.* One command to give your OpenClaw agent its memory. Walks through the complete memory system setup interactively. ## Quick Start ```bash python3 scripts/memory-onboarding-wizard.py ``` Run from the OpenClaw workspace directory (default: `~/.openclaw/workspace`). ## What It Does 1. **MEMORY.md** — Creates long-term memory file with starter template if missing 2. **memory/YYYY-MM-DD.md** — Creates today's daily note file (creates `memory/` dir if needed) 3. **HEARTBEAT.md** — Creates a starter heartbeat checklist if missing 4. **USER.md** — Asks 3 quick questions (name, timezone, main use case) and writes them 5. **Validation** — Checks all files exist and prints a ✅ summary 6. **Next steps** — Suggests the first 3 things to try ## Options ```bash python3 scripts/memory-onboarding-wizard.py --workspace /path/to/workspace python3 scripts/memory-onboarding-wizard.py --non-interactive # skip questions, use defaults ``` ## Memory System Overview | File | Purpose | When Loaded | |------|---------|-------------| | `MEMORY.md` | Long-term curated memory | Main sessions only | | `memory/YYYY-MM-DD.md` | Daily raw notes | Every session | | `HEARTBEAT.md` | Periodic task checklist | On heartbeat polls | | `USER.md` | Who the agent is serving | Every session | ## After Setup Your agent will read these files at the start of each session to maintain continuity. Update `MEMORY.md` with important events and decisions. Let daily files accumulate naturally. --- ## 🧠 Want the Full Memory Pack? This wizard gets you started. The **GetAgentIQ Memory Pack** takes it further: - **Auto-compaction** — keeps MEMORY.md lean and fast automatically - **Semantic search** — find anything across all memory files instantly - **Session recall** — 7-day keyword recall tester - **Memory health dashboard** — health score + gap detection - **Consolidation cron** — nightly memory distillation, runs while you sleep 👉 **Get the Memory Pack free:** [getagentiq.ai/memory-pack](https://getagentiq.ai) Use code **`CLAWHUB100`** at checkout for 100% off. *Built by GetAgentIQ — [getagentiq.ai](https://getagentiq.ai)*


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