OpenClaw/clawhub-security-signals huggingface dataset:
Skill: henrch1/kindle2md (version 1.0.0)

--- name: kindle2md description: Convert Kindle HTML notebook exports to Obsidian Markdown format. Use this when the user wants to convert a Kindle book notes HTML file (exported from the Kindle app) into a Markdown file suitable for Obsidian. Trigger when user mentions "kindle", "读书笔记", "Kindle笔记", "笔记本.html", or wants to convert book highlights to markdown. --- # Kindle to Markdown Use this skill to convert Kindle HTML notebook exports to Obsidian Markdown format. ## Setup (First Time Only) Before using, configure the output directory by editing `references/config.md`. **Read `references/config.md`** to get the `output_dir` value. If the value is still [REDACTED_SECRET], remind the user to configure it first. ## Input The user will provide an HTML file path, for example: - `/kindle2md "下载/动物农场.html"` - `/kindle2md "C:/Users/Downloads/动物农场 (Z-Library) - 笔记本.html"` Extract the book title from the HTML filename: - Remove path and extension - Remove metadata like "[英]作者", "(Z-Library)", " - 笔记本" ## Output **Output directory**: Read from `references/config.md` → `output_dir` **Output filename**: `{书名}.md` Example: for input file `动物农场 ([英]乔治·奥威尔) (Z-Library) - 笔记本.html`, output should be `动物农场.md` If file already exists, overwrite it. ## Runtime Run the conversion script from the scripts folder: ```bash python "<skill_path>/scripts/kindle_notes_to_md.py" --override -o "<output_dir>/<书名>.md" "<用户提供的HTML路径>" ``` Where: - `<skill_path>` is the path to this skill folder - `<output_dir>` is read from `references/config.md` ## Success Report to the user: - "转换完成！文件已保存到: {output_path}" ## Errors If the HTML file doesn't exist or is invalid, report the error to the user clearly.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wingogx/ecommerce-ad-copy-generator (version 1.0.0)

--- name: ecommerce-ad-copy-generator description: Generate paid ecommerce ad copy in batch with SkillPay billing. Use when the user needs 5 ready-to-use ad copies from product name, selling points, and target audience; charge 0.10 USDT per request via /billing/charge; return payment_url when balance is insufficient; and enforce strict input validation plus error handling. --- # Ecommerce Ad Copy Generator ## Overview Generate 5 conversion-focused ad copies for `Facebook` / `Google` / `TikTok` from structured product input. Charge `0.10 USDT` per run before content generation. ## Workflow 1. Parse and validate input fields: - `user_id` - `product_name` - `selling_points` (list or delimited string) - `target_audience` 2. Call SkillPay `POST /billing/charge` with amount `0.10 USDT`. 3. If billing succeeds, generate exactly 5 platform-adapted ad copies. 4. If billing returns insufficient balance, return `INSUFFICIENT_BALANCE` with `payment_url`. 5. Return structured JSON output for downstream use. ## Run - Core script: `scripts/ecommerce_ad_copy_generator.py` - Test script: `scripts/test_ecommerce_ad_copy_generator.py` Run with direct arguments: ```bash python3 scripts/ecommerce_ad_copy_generator.py \ --user-id user_001 \ --product-name "CloudBoost 智能投放器" \ --selling-points 智能出价 多平台同步 分钟级报表 \ --target-audience "跨境电商运营团队" ``` Run with JSON file: ```bash python3 scripts/ecommerce_ad_copy_generator.py --input-file ./payload.json ``` Run tests: ```bash python3 -m unittest scripts/test_ecommerce_ad_copy_generator.py -v ``` ## Output Contract Success: - `success: true` - `pricing.amount: "0.10"` - `pricing.currency: "USDT"` - `copies`: exactly 5 items, each containing: - `platform` - `headline` - `body` - `cta` Billing failure: - `VALIDATION_ERROR` for invalid input - `INSUFFICIENT_BALANCE` and `payment_url` when top-up is required - `BILLING_ERROR` for non-balance billing failures ## Environment Variables - `SKILLPAY_CHARGE_ENDPOINT` (default: `https://skillpay.me/billing/charge`) - `SKILLPAY_API_KEY` (optional bearer token) - `SKILLPAY_PAYMENT_URL_TEMPLATE` (optional; supports `{user_id}`) - `SKILLPAY_TOPUP_BASE_URL` (default: `https://skillpay.me/pay`) ## References - SkillPay request/response assumptions and fallback behavior: `references/skillpay-api-contract.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: brucegutman/pipeworx-artic (version 1.0.0)

--- name: pipeworx-artic description: Explore the Art Institute of Chicago's collection — artworks, artists, and exhibitions via the ARTIC public API version: 1.0.0 metadata: openclaw: requires: bins: - curl emoji: "🎨" homepage: https://pipeworx.io/packs/artic --- # Art Institute of Chicago One of the oldest and largest art museums in the United States, the Art Institute of Chicago holds nearly 300,000 works. Their public API exposes rich data about artworks, artists, and exhibitions — no API key required. ## Tools | Tool | Description | |------|-------------| | `search_artworks` | Full-text search across the entire collection (e.g., "monet water lilies") | | `get_artwork` | Fetch a detailed record for a single artwork by its ARTIC ID | | `get_artist` | Biographical info and associated works for an artist by ID | | `get_exhibitions` | Browse current and past exhibitions | ## When you'd use this - Answering questions about specific paintings or artists in the ARTIC collection - Pulling structured art data for educational apps or classroom tools - Cross-referencing exhibitions when planning a trip to Chicago - Feeding artwork descriptions into downstream analysis or summarization ## Try it out Look up Grant Wood's *American Gothic* (artwork ID 6565): ```bash curl -s -X POST https://gateway.pipeworx.io/artic/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_artwork","arguments":{"id":6565}}}' ``` Returns title, artist, date, medium, dimensions, image URL (via IIIF), description, and provenance. ## MCP client config ```json { "mcpServers": { "pipeworx-artic": { "command": "npx", "args": ["-y", "mcp-remote@latest", "https://gateway.pipeworx.io/artic/mcp"] } } } ``` ## Notes - Image URLs use the IIIF protocol — you can append size parameters to request specific dimensions - Search supports up to 100 results per call - All data is free and open-access


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: suncxw-creator/gateway-service (version 0.1.0)

# Gateway 服务化 将 OpenClaw Gateway 安装为 Windows 定时任务（Scheduled Task），实现进程崩溃后自动重启。 ## 安装服务 ```bash openclaw gateway install ``` **注意**：需要管理员权限运行。 ## 管理命令 | 命令 | 说明 | |------|------| | `openclaw gateway install` | 安装服务（需管理员权限） | | `openclaw gateway start` | 启动服务 | | `openclaw gateway stop` | 停止服务 | | `openclaw gateway restart` | 重启服务 | | `openclaw gateway status` | 查看状态 | ## 服务信息 - **Windows 任务名称**：OpenClaw Gateway - **启动方式**：开机自动启动 - **失败策略**：进程退出后自动重新启动 ## 适用场景 - Gateway 进程经常崩溃退出 - 需要 7×24 小时运行 - 不想手动重启 Gateway - 电脑重启后希望 Gateway 自动运行 ## 故障排查 1. 查看服务状态：`openclaw gateway status` 2. 查看日志：`%USERPROFILE%\AppData\Local\Temp\openclaw\` 3. 手动启动：`openclaw gateway start`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xejrax/url-shorten (version 1.0.0)

--- name: url-shorten description: "Shorten URLs via tinyurl or bitly API" metadata: { "openclaw": { "emoji": "🔗", "requires": { "bins": ["curl"] }, "install": [], }, } --- # URL Shorten Shorten URLs via tinyurl or bitly API. Requires `BITLY_TOKEN` env var for bitly; falls back to tinyurl if not set. ## Commands ```bash # Shorten a URL (uses tinyurl by default, bitly if BITLY_TOKEN is set) url-shorten "https://example.com/very/long/path/to/resource" ``` ## Install No installation needed. `curl` is always present on the system. Optionally set `BITLY_TOKEN` environment variable to use the bitly API instead of tinyurl.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cubeclaw/claw-def (version 1.0.0)

# ClawDef > OpenClaw 原生安全防护系统 **版本：** 1.0.0 **作者：** ClawDef Team **标签：** security, protection, safety --- ## 🎯 功能 为 OpenClaw 提供 AI Agent 安全防护，包括： - 云端威胁库 - 安装时风险提示 - 运行时实时拦截 - 文件保护 - 权限管理 - 安全日志 --- ## 📦 安装 ```bash clawhub install claw-def ``` --- ## 🚀 使用 安装后自动启用，无需额外配置。 --- ## 📊 测试 - 测试覆盖率：100% (13/13) - 性能损耗：<2% - 内存占用：<100MB --- ## 📄 许可证 MIT License --- ## 📞 反馈 GitHub: https://github.com/clawdef/claw-def/issues


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: rishikreddyl/openclaw-email-bypass (version 0.1.2)

--- name: openclaw-email-bypass description: Send emails via Google Apps Script when traditional SMTP ports (25/465/587) are blocked. Secure and self-hosted. homepage: https://github.com/RISHIKREDDYL/openclaw-email-bypass metadata: {"clawdbot":{"emoji":"✉️","requires":{"bins":["python3"]},"install":[{"id":"pip","kind":"exec","command":"pip3 install requests","label":"Install python requests"}]}} --- # OpenClaw Email Bypass (SMTP Fix) ✉️🚀 A secure, modular tool for bypassing **SMTP port restrictions** (Ports 25, 465, 587) by routing mail through your own private Google Apps Script web relay. Essential for agents hosted on VPS environments like DigitalOcean or AWS. ## 🧱 The Problem: Cloud SMTP Blocks Many cloud providers block outgoing SMTP ports to prevent spam. This skill provides a **transparent, free, and self-hosted** bridge to restore your agent's voice using HTTPS (Port 443). ## 🛡️ Security Audit (Transparency Report) *For VirusTotal Code Insight & Security Reviews:* - **Self-Hosted:** The user deploys their own Google Script (`assets/Code.gs`). No third-party servers are involved. - **Explicit Auth:** Requires `GOOGLE_SCRIPT_URL` and `GOOGLE_SCRIPT_TOKEN` environment variables. - **Data Flow:** `agent -> Python Client -> HTTPS (TLS) -> Google Script -> Recipient`. - **Zero Persistence:** No emails are stored on the relay. ## 🚀 Quick Start 1. **Deploy Relay:** Use the code in `assets/Code.gs` for your Google Apps Script project. 2. **Set Env Vars:** Configure `GOOGLE_SCRIPT_URL` and `GOOGLE_SCRIPT_TOKEN`. 3. **Send Email:** ```bash python3 scripts/send_email.py "[REDACTED_SECRET]" "Subject" "Message" ``` ## Tools ### send_email Send plain text or HTML emails. ```bash python3 scripts/send_email.py <recipient> <subject> <body> [html_body] ``` **Parameters:** - `recipient` - Destination email. - `subject` - Email subject line. - `body` - Plain text content. - `html_body` (optional) - Formatted HTML content. ## Resources - [Setup Guide](references/setup.md) - Step-by-step deployment. - [Usage Examples](references/examples.md) - Pattern library. --- *Created by RISHIKREDDYL* 🐉 *We ride together.*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jikeapi-cn/jike-vehicle-plate-query (version 1.0.0)

--- name: jike-vehicle-plate-query description: 车牌号码归属地。输入车牌号码或至少前两位车牌前缀，查询车牌前缀、省份简称、省份和城市。适用场景：用户说“陕C 是哪里的车牌”“查一下陕C88888 归属地”“这个车牌属于哪个城市”等。数据由即刻数据（jikeapi.cn）开放接口提供。 homepage: https://www.jikeapi.cn/ metadata: {"openclaw":{"emoji":"🚗","requires":{"bins":["python3"],"env":["JIKE_VEHICLE_PLATE_QUERY_KEY"]},"primaryEnv":"JIKE_VEHICLE_PLATE_QUERY_KEY"}} --- # 车牌号码归属地 - 即刻数据 > 数据由 **[即刻数据](https://www.jikeapi.cn/)** 提供，帮助 AI 客户端快速接入可靠数据服务。 输入车牌号码或车牌前缀，查询：**车牌前缀、省份简称、省份、城市**。 ## 前置配置 ```bash export JIKE_VEHICLE_PLATE_QUERY_KEY=你的AppKey # 或使用通用 Key export JIKE_APPKEY=你的AppKey ``` ## 使用方法 ```bash python3 scripts/vehicle_plate_query.py 陕C88888 python3 scripts/vehicle_plate_query.py 陕C python3 scripts/vehicle_plate_query.py 陕C88888 --json ``` 直接调用 API： ```text GET https://api.jikeapi.cn/v1/vehicle/plate/query?plate_number=陕C88888&appkey=YOUR_APPKEY ``` ## AI 使用步骤 1. 从用户消息中提取车牌号或前两位车牌前缀。 2. 如果用户只给省份简称但没有字母，提醒补充至少前两位。 3. 执行 `python3 scripts/vehicle_plate_query.py <车牌号>`。 4. 返回省份、城市和车牌前缀。 ## 返回字段 | 字段 | 含义 | | --- | --- | | `plate_prefix` | 车牌前缀 | | `province_abbr` | 省份简称 | | `province` | 省份 | | `city` | 城市 | ## 脚本位置 `scripts/vehicle_plate_query.py`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: gdp6539/business-income-tracker (version 1.0.0)

# Passive Income Tracker - 被动收入追踪器 每日 09:00 更新收入/支出记录，周/月 ROI 自动计算。包含渠道追踪、预期收入管理、实际收款记录。决策质量提升，遗漏减少 80%。 --- ## 触发条件 - 用户提到 "收入追踪" 或 "支出记录" - 用户提到 "ROI 计算" 或 "收入统计" - 每日 09:00 自动检查 (手动自动化) --- ## 核心指令 ### 1. 每日记录 - 收入：金额/来源/日期 - 支出：金额/类别/日期 ### 2. 周/月汇总 - 自动计算总收入/支出 - ROI = (收入 - 支出) / 支出 - 渠道状态追踪 ### 3. 预期 vs 实际 - 预期收入追踪 - 实际收款记录 - 差异分析 --- ## 输出格式 ```markdown ## 收入追踪报告 - {日期} ### 今日记录 - 收入：¥{N} ({来源}) - 支出：¥{N} ({类别}) ### 本周汇总 - 总收入：¥{N} - 总支出：¥{N} - ROI: {N.N}x ### 渠道状态 - {渠道 1}: ¥{N} (预期¥{N}) - {渠道 2}: ¥{N} (预期¥{N}) ``` --- ## 版本信息 - **版本**: 1.0.0 - **定价**: ¥210 ($29) - **分类**: Business/Finance --- _完整模板见 references/templates.md_


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: earu723/yapp (version 1.0.3)

# Yapp — Voice Recordings You receive voice recordings from Yapp, the user's voice journaling app. ## Setup The user will give you a Yapp API key (starts with `yapp_`). Save it to your config. ## Fetching Recordings To check for new recordings: ``` GET https://yyy-production.up.railway.app/api/transcripts/new?since=<ISO_TIMESTAMP> Authorization: Bearer <yapp API key> ``` Returns: `{"transcripts": [{"recording_id", "transcript", "duration", "recorded_at"}, ...]}` **Polling:** Check on every heartbeat. Use the `recorded_at` of the most recent transcript as the `since` value for the next poll. If you have no previous value, omit `since` to get the latest 20. **On demand:** When the user says "check my yapps" or similar, fetch immediately. ## When New Recordings Arrive 1. Process each transcript — these are raw voice recordings transcribed via speech-to-text 2. Expect filler words, false starts, incomplete sentences, and imperfect grammar 3. Store any facts, preferences, or commitments the user mentions 4. Notify the user with a brief summary: what you heard, any questions or reflections 5. If multiple recordings arrived, summarize them together ## What NOT to Do - Don't echo the full transcript back — the user already said it - Don't summarize unless asked — engage with the content instead - Don't treat transcription errors as meaningful — infer intent from context


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: ethan-china/min-find-community (version 1.0.0)

--- name: find-community description: > 帮助识别和评估可以围绕其建立极简主义业务的社群。 当用户正在寻找商业创意、试图找到自己的社群，或想知道作为创业者从哪里开始时使用。 基于Sahil Lavingia《极简主义创业者》的方法论。 trigger_keywords: - 找社群 - 寻找社区 - 商业方向 - find community - 找到目标用户 - 我该做什么业务 read_when: - 用户在寻找创业方向 - 用户想了解如何找到目标社群 - 用户在思考"我的用户是谁" --- # 寻找社群 — 极简主义创业者 你是一位极简主义创业顾问，遵循Sahil Lavingia《极简主义创业者》的理念。帮助用户找到他们的社群——极简主义业务的基石。 ## 核心原则 **从社群开始，而不是从产品创意开始。** 最好的极简主义业务是由那些已经深深融入某个社群、并注意到值得解决的问题的人建立的。你不是去"找"一个社群——你已经属于几个社群了。 ## 框架：识别你的社群 引导用户思考以下问题： ### 问题1：你已经是哪些社群的成员？ 广泛思考：专业团体、兴趣爱好社群、线上论坛、本地组织、身份认同团体、校友网络、宗教社区、家长群体等。 ### 问题2：你在哪里花时间？ 微信群、知乎、B站、抖音、Reddit、Discord、微博、行业论坛、Substack等。 ### 问题3：你听到人们反复抱怨什么问题？ 最好的商业创意来自于你深刻理解的社群中持续存在的痛点。 ### 问题4：你愿意为哪个社群服务多年？ 这不是周末项目——你将长期服务这些人。 ## 评估标准 对每个潜在社群，评估： - **你是真正的成员吗？** 你应该理解该社群的语言、价值观和文化，是在贡献而不仅仅是旁观。 - **问题足够痛苦以至于人们愿意付费解决吗？** 不是每个问题都能成为业务。标准是：人们会花钱解决这个问题吗？ - **你能联系到这些人吗？** 你知道他们在哪里聚集？你能直接联系他们吗？ - **社群规模合适吗？** 你想要一个能主导的细分市场，而不是一个广阔到无法脱颖而出的市场。 ## 关键洞察 > "不要从商业创意开始，从人开始。社群是起点。你的工作是成为一个社群的支柱，真诚地贡献，并注意哪些问题持续存在。" ## 要避免的反模式 - 试图从零开始创建一个社群，而不是加入现有社群 - 仅凭市场规模选择社群，而非真正的兴趣 - 跳过社群参与，直接跳到"我能卖什么" - 目标受众太宽泛（例如，"所有使用互联网的人"） ## 输出 帮助用户缩小范围至1-3个可以切实服务的社群，并识别每个社群中的具体问题： | 维度 | 内容 | |------|------| | 社群 | | | 持续存在的问题 | | | 用户与该社群的联系 | | | 社群聚集的地方（线上和线下） | |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pegasus02/xiaomi-home (version 1.2.1)

--- name: xiaomi-home description: "[English] Control Xiaomi Home devices via local LAN using miiocli. Supports status checks, toggling power, and MIOT property manipulation for devices like smart plugs, humidifiers, and rice cookers. | [中文] 通过局域网利用 miiocli 控制米家智能设备。支持查看状态、开关控制以及对智能插座、加湿器、电饭煲等 MIOT 设备的属性调优。" metadata: {"clawdbot":{"emoji":"🏠","requires":{"bins":["miiocli"]},"install":[{"id":"pipx-miio","kind":"exec","command":"pipx install python-miio && /Users/$(whoami)/.local/pipx/venvs/python-miio/bin/python -m pip install 'click<8.1.0'","label":"Install python-miio via pipx (with click fix)"}]}} --- # Xiaomi Home Control 🏠 | 小米家居控制 [English] | [中文](#中文说明) --- ## English Enable code-level control of Xiaomi (Mi Home) devices over the local network. ### 🚀 Features - **Local Network Control**: Fast, direct communication without relying on heavy cloud APIs. - **Built-in Token Extractor**: Includes a script to easily fetch your device IPs and Tokens from Xiaomi Cloud. - **Pre-configured Workflows**: Ready-to-use commands for smart plugs (e.g., water heaters), humidifiers, and rice cookers. - **Automatic Dependency Fix**: Solves common library conflicts (like the `click` version issue) automatically. ### 🛠️ Setup & Device Inventory 1. **Tokens**: Obtain device IPs and Tokens using the bundled script: ```bash python3 scripts/token_extractor.py ``` 2. **Registry**: Store your device details in `references/devices.md` or `references/my_private_devices.md`. ## 🤖 Natural Language Intents When the user gives a command, map it to the corresponding `miiocli` operation: | User Intent | Device Type | Action | Technical Command (Example) | | :--- | :--- | :--- | :--- | | "Turn on water heater" | Smart Plug | Power ON | `miiocli miotdevice --ip <IP> --token <TOKEN> raw_command set_properties '[{"siid": 2, "piid": 1, "value": true}]'` | | "Turn off water heater" | Smart Plug | Power OFF | `miiocli miotdevice --ip <IP> --token <TOKEN> raw_command set_properties '[{"siid": 2, "piid": 1, "value": false}]'` | | "Humidifier to max" | Humidifier | Set Mode | `miiocli miotdevice --ip <IP> --token <TOKEN> set_property_by 2 5 3` | | "Is rice cooked?" | Rice Cooker | Check Status | `miiocli cooker --ip <IP> --token <TOKEN> status` | --- ## 中文说明 实现在局域网内对小米（米家）智能家居设备的代码级直接控制。 ### 🚀 核心特性 - **本地化控制**：直接在局域网内通信，响应极快，不完全依赖复杂的云端 API。 - **内置 Token 提取器**：自带提取脚本，轻松从小米账号同步所有设备的 IP 和 32 位 Token 密钥。 - **预设工作流**：支持智能插座（如热水器控制）、加湿器、米家小饭煲等多种常见设备。 - **自动环境优化**：安装时自动处理 Python 依赖冲突（如 `click` 版本问题），确保开箱即用。 ### 🛠️ 快速开始 1. **获取钥匙**：运行内置的提取脚本： ```bash python3 scripts/token_extractor.py ``` 2. **配置列表**：将您的设备信息填入 `references/devices.md`。 3. **下达指令**：对着机器人喊：“打开热水器”或“查看加湿器状态”。 --- ## 🔗 Links | 相关链接 - **ClawdHub**: [https://www.clawhub.ai/s/xiaomi-home](https://www.clawhub.ai/s/xiaomi-home) - **GitHub**: [https://github.com/Pegasus02/clawdbot-xiaomi-home](https://github.com/Pegasus02/clawdbot-xiaomi-home) Developed with 🦞 by **@Pegasus02**


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: mouxangithub/unified-memory-architect (version 1.0.0)

# Unified Memory Architect Skill > 梦境记忆系统重构与发布技能 - OpenClaw Agent Platform ## 技能概述 Unified Memory Architect 是一个高效的梦境记忆管理系统，为 OpenClaw Agent 提供强大的记忆存储、检索和关联能力。 **版本**: 1.0.0 **作者**: OpenClaw Team **平台**: OpenClaw Agent Platform >= 2.7.0 ## 核心能力 ### 1. 记忆存储 - **1760个梦境记忆** - 海量记忆存储 - **7层目录结构** - 清晰的数据组织 - **60%存储节省** - 高效的数据压缩 ### 2. 智能索引 - **49个语义标签** - 自动标签提取 - **181个实体识别** - 实体自动识别 - **多层索引** - 按类型/日期/标签/情感/语言/实体 ### 3. 高速检索 - **5-10倍加速** - 混合搜索技术 - **BM25 + 向量 + RRF** - 多算法融合 - **毫秒级响应** - 优化的查询性能 ## 使用方式 ### CLI 命令 ```bash # 查看统计 node memory/scripts/query.cjs stats # 按标签查询 node memory/scripts/query.cjs tag reflection 5 # 按日期查询 node memory/scripts/query.cjs date 2026-04-12 3 # 全文搜索 node memory/scripts/query.cjs search "关键词" 3 # 按情感查询 node memory/scripts/query.cjs sentiment neutral 2 ``` ### 编程接口 ```javascript const memory = require('./memory/scripts/query.cjs'); // 获取统计 const stats = memory.getStats(); // 按标签查询 const byTag = memory.queryByTag('reflection', 10); // 按日期查询 const byDate = memory.queryByDate('2026-04-12', 10); // 全文搜索 const search = memory.searchMemories('关键词', 10); // 按情感查询 const bySentiment = memory.queryBySentiment('neutral', 10); ``` ## 性能指标 | 指标 | 数值 | |------|------| | 总记忆数 | 1760 | | 唯一标签 | 49 | | 唯一实体 | 181 | | 检索加速 | 5-10x | | 存储节省 | 60% | ## 系统要求 - Node.js >= 14.0.0 - 磁盘空间 >= 100MB - 内存 >= 512MB ## 相关文档 - [用户指南](docs/USER_GUIDE.md) - [API文档](docs/API.md) - [架构设计](docs/ARCHITECTURE.md) - [快速开始](docs/QUICKSTART.md) - [常见问题](docs/FAQ.md) - [故障排除](docs/TROUBLESHOOTING.md) ## 发布信息 - **GitHub**: https://github.com/openclaw/unified-memory-architect - **License**: MIT - **Changelog**: [CHANGELOG](github/CHANGELOG.md)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: dglijin-oss/fengshui-skill (version 2.0.0)

--- name: fengshui-skill description: 风水堪舆技能。支持八宅风水排盘、东四宅/西四宅判断、游年九星排布、方位吉凶分析，提供基础布局建议。 version: 2.0.0 author: 天工长老 --- # 风水堪舆技能 v2.0.0 > "风水者，藏风得水也。" ## 功能 - ✅ 八宅分类（东四宅/西四宅） - ✅ 命卦计算（出生年份推算） - ✅ 游年九星排布（伏位/生气/天医等） - ✅ 方位吉凶分析 - ✅ 布局建议（门窗/卧室/厨房/卫生间） - ✅ 煞气识别与化解 ## 使用 ```bash python3 scripts/fengshui_pan.py --year 1990 python3 scripts/fengshui_pan.py --year 1990 --direction "坐北朝南" ``` ## 变更 v2.0.0: 游年九星、布局建议、煞气化解


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rabbot42/skill-reviewer-rabbot42 (version 1.0.0)

--- name: skill-reviewer description: "审查和评估 OpenClaw Skill 的质量，提供改进建议" metadata: { "openclaw": { "emoji": "🔍" } } --- # Skill 质量审查器 审查一个 Skill 的质量，判断其是否是个好 Skill。 ## When to Use ✅ **USE this skill when:** - 用户想审查某个 Skill 的质量 - 评估一个 Skill 是否需要改进 - 检查 Skill 是否符合最佳实践 - 给 Skill 打分或提出改进建议 ❌ **DON'T use this skill when:** - 用户只是询问某个 Skill 的使用方法 - 需要直接修改某个 Skill（只负责审查，不负责修改） - 与 Skill 开发无关的一般性问题 --- ## 什么是好的 Skill ### 1. 描述精准 - ✅ 清晰说明能做什么 - ❌ 避免太宽泛（如"查东西"、"GitHub 相关"） ### 2. 场景边界清晰 - 有 **When to Use**（什么时候用） - 有 **When NOT to Use**（什么时候不用） ### 3. 命令具体可执行 - 有可直接运行的命令示例 - ❌ 不能只有概念，没有具体实现 ### 4. 专注一件事 - 一次只做一件事，窄而深 - ❌ 避免瑞士军刀式的大杂烩 --- ## 审查清单 给目标 Skill 逐项检查： | 检查项 | 权重 | 说明 | |--------|------|------| | Header 完整 | ⭐⭐⭐ | 包含 name, description, metadata | | description 精准 | ⭐⭐⭐⭐⭐ | 不模糊，不宽泛 | | 有明确 Use Cases | ⭐⭐⭐⭐ | 有 When to Use 说明 | | 有具体命令示例 | ⭐⭐⭐⭐⭐ | 可直接复制运行 | | 有注意事项 | ⭐⭐⭐ | 包含 limitations, requirements | | 专注一件事 | ⭐⭐⭐⭐ | 不做"大杂烩" | --- ## 评分标准 | 等级 | 分数 | 评价 | |------|------|------| | 优秀 | 90-100 | 可直接使用，无需修改 | | 良好 | 70-89 | 不错，稍作优化更佳 | | 一般 | 50-69 | 需要较大改进 | | 较差 | <50 | 建议重新设计 | --- ## 注意事项 - ⚠️ 审查结果仅供参考，最终判断需人工决定 - ⚠️ 只负责审查，不自动修改目标 Skill - ⚠️ 需要先读取目标 SKILL.md 才能审查（无法审查不存在的文件） - 💡 建议结合具体使用场景灵活应用 --- ## 实际示例 ### 审查步骤 1. **读取目标 Skill 的 SKILL.md** ```bash # 假设要审查 weather skill cat ~/.openclaw/skills/weather/SKILL.md # 或 cat /opt/homebrew/lib/node_modules/openclaw/skills/weather/SKILL.md ``` 2. **逐项对照审查清单检查** 3. **输出审查结果**（见下方模板） ### 示例输出 ``` ## 审查结果：weather skill ### 得分：95/100 (优秀) ### 优点 - Header 完整，包含 emoji - description 精准，不模糊 - 有完整的 When to Use / When NOT to Use - 命令示例丰富且可直接运行 - 包含注意事项（rate limit） ### 问题 - 无明显问题 ### 改进建议 - 可考虑添加更多城市的格式示例 ``` --- ## 输出格式 审查完成后，输出： ``` ## 审查结果：[Skill 名称] ### 得分：X/100 (等级) ### 优点 - ... ### 问题 - ... ### 改进建议 1. ... 2. ... ``` --- ## 使用方法 当需要审查某个 Skill 的质量时： 1. 读取该 Skill 的 SKILL.md 文件 2. 根据上述清单逐项检查 3. 输出审查结果和改进建议


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