OpenClaw/clawhub-security-signals huggingface dataset:
Skill: make453/openclaw-tavily-search-bak (version 1.0.0)

--- name: tavily-search description: "Web search via Tavily API (alternative to Brave). Use when the user asks to search the web / look up sources / find links and Brave web_search is unavailable or undesired. Returns a small set of relevant results (title, url, snippet) and can optionally include short answer summaries." --- # Tavily Search Use the bundled script to search the web with Tavily. ## Requirements - Provide API key via either: - environment variable: `TAVILY_API_KEY`, or - `~/.openclaw/.env` line: `TAVILY_API_KEY=...` ## Commands Run from the OpenClaw workspace: ```bash # raw JSON (default) python3 {baseDir}/scripts/tavily_search.py --query "..." --max-results 5 # include short answer (if available) python3 {baseDir}/scripts/tavily_search.py --query "..." --max-results 5 --include-answer # stable schema (closer to web_search): {query, results:[{title,url,snippet}], answer?} python3 {baseDir}/scripts/tavily_search.py --query "..." --max-results 5 --format brave # human-readable Markdown list python3 {baseDir}/scripts/tavily_search.py --query "..." --max-results 5 --format md ``` ## Output ### raw (default) - JSON: `query`, optional `answer`, `results: [{title,url,content}]` ### brave - JSON: `query`, optional `answer`, `results: [{title,url,snippet}]` ### md - A compact Markdown list with title/url/snippet. ## Notes - Keep `max-results` small by default (3–5) to reduce token/reading load. - Prefer returning URLs + snippets; fetch full pages only when needed.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: dereklu515/tech-radar-daily (version 1.0.9)

--- name: tech-radar-daily version: 1.0.9 description: "每日技术情报雷达 - 自动发现有趣工具、技术趋势、赚钱项目。扫描 GitHub Trending、Product Hunt、Hacker News、Awesome Lists，智能评分筛选高价值项目，每日推送 7-9 条精选情报到飞书。" metadata: { "openclaw": { "emoji": "📡", "requires": { "env": ["FEISHU_WEBHOOK_URL"], "bins": ["node"] }, "install": [ { "id": "npm", "kind": "node", "label": "Install dependencies (npm)", }, { "id": "manual", "kind": "manual", "label": "配置环境变量", "steps": ["在 ~/.zshrc 中添加：export FEISHU_WEBHOOK_URL=\"你的飞书 Webhook URL\""] } ], "actions": { "run": { "command": "node scripts/run-cycle.js", "description": "运行每日技术情报扫描" }, "test": { "command": "node scripts/run-cycle.js --test", "description": "测试模式运行（不推送飞书）" } } } } --- # Tech Radar Daily 每日技术情报雷达 - 自动发现有趣工具、技术趋势、赚钱项目 ## 功能 - 🔍 扫描 GitHub Trending、Product Hunt、Hacker News、Awesome Lists - 📊 智能评分筛选高价值项目（趋势热度 + 历史影响 + AI 属性 + 大厂加分） - 🚀 每日推送 7-9 条精选情报到飞书 - 🔄 自动去重，7 天内不重复推荐 - ⏰ 自动运行，每天 09:00 Cron 定时任务 ## 使用方法 ### 手动运行 ```bash cd /Users/mini/.openclaw/workspace/skills/tech-radar-daily node scripts/run-cycle.js ``` ### 测试模式（不推送飞书） ```bash node scripts/run-cycle.js --test ``` ### 定时任务 ```bash # 已配置：每天 09:00 自动运行 ``` ## ⚠️ Gotchas（常见陷阱） ### 🔴 高风险 - ❌ **不要忘记设置 Cron timeout** ✅ 正确做法：`openclaw cron add --timeout 650` - ❌ **不要重复推荐同一项目（7 天内）** ✅ 正确做法：维护 seen_repos 数据库 ### 🟡 中风险 - ❌ **不要一次性抓取太多数据** ✅ 正确做法：每个情报源限制 20 个候选 - ❌ **不要忘记置信度标注** ✅ 正确做法：每条情报标注 🟢🟡🟠 ## 配置 环境变量： - `FEISHU_WEBHOOK_URL`: 飞书机器人 webhook 地址（必需） - `https_proxy` 或 `HTTP_PROXY`: 代理地址（推荐配置，解决 GitHub 访问问题） - `GITHUB_TOKEN`: GitHub API Token（可选，提高限额） 代理说明： - 代码使用 `proxy-agent` 自动读取 `https_proxy` / `HTTP_PROXY` 环境变量 - 如果已配置本地 Clash（系统代理），设置 `export https_proxy=http://127.0.0.1:7897` - 代理配置建议写入 `~/.zshrc`，让所有子进程自动继承 ## 变更历史 ### v1.0.9 (2026-03-29) - ✅ 添加 `proxy-agent` 支持，解决 GitHub Trending 超时问题 - ✅ 修复 `SKILL.md` 的 `install` 配置，支持自动 `npm install` - ✅ 添加 `requires.bins: ["node"]` 依赖检查 ### v1.0.8 (2026-03-29) - 初始发布版本


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: terrycarter1985/demo-asset-store (version 0.1.0)

--- name: demo-asset-store description: 演示素材入库技能——用于配合 TaskFlow 完成素材上传与入库的端到端流程 metadata: { "openclaw": { "emoji": "📦" } } --- # Demo Asset Store 本技能用于演示素材入库操作。 ## 用途 - 将本地文件（图片、文档等）登记到技能目录下 - 生成素材索引清单（assets-index.json） - 配合 TaskFlow 编排批量入库流程 ## 操作 1. 将素材文件放入 `assets/` 子目录 2. 运行索引生成脚本（见 scripts/index.sh） 3. 索引文件 `assets-index.json` 即为入库结果


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

--- name: zhangyue description: 注册“掌阅”技能；用于阅读产品公开页面、书库入口、会员说明与帮助信息整理。 homepage: `https://www.ireader.com/` metadata: {"clawdbot":{"emoji":"📖"}} --- # 掌阅 用途与边界 - 面向公开官网、书城页、会员页、帮助中心与活动页的信息整理 - 不提供盗版资源、版权绕过、会员代充、账号共享或接口调用能力 - 仅处理公开可见的书库入口、会员说明、阅读功能与帮助信息 关键入口 - 主页：https://www.ireader.com/ - 书库与内容：书城、分类、榜单、专题、作者或出版方入口 - 会员与帮助：会员页、订阅说明、帮助中心、活动页入口 常见任务 - 书库分类、榜单、书单与内容入口整理 - 会员权益、订阅规则、下载说明与设备支持汇总 - 帮助中心、常见问题、活动页与版权说明提取 数据字段 - 内容分类、榜单入口、会员权益、链接 - 设备支持、离线规则、帮助页、活动页链接 - 版权说明、FAQ、下载限制、公告入口 自动化要点 - 内容授权和会员权益存在地区与时间差异，输出时注明上下文 - 不输出盗版下载、会员共享、抓包或接口绕过建议 - 不处理个人书架、阅读记录、购买记录或私有账户数据 示例流程 - 书库整理：访问 Zhangyue 书城与分类页 → 输出内容入口清单 - 权益整理：进入会员页 → 提取权益与限制 → 输出表格 - 帮助汇总：访问帮助中心 → 提取下载、设备、FAQ → 输出摘要 合规提示 - 遵守平台规则、版权要求与账号安全要求 - 只整理公开信息，不输出敏感数据或非公开内容


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: guyoung/pandoc-rs (version 1.0.0)

--- name: pandoc-rs description: A powerful document conversion tool supporting Html, Markdown, Docx, PDF, and LaTeX formats. Provides bidirectional conversion between these formats using a WebAssembly-based engine similar to Pandoc. --- # Pandoc Rs A WebAssembly-based document conversion tool that converts between Html, Markdown, Docx, PDF, and LaTeX formats. ## Trigger when The user asks to convert documents between Html, Markdown, Docx, PDF, or LaTeX formats. Examples: "convert this markdown to PDF", "export as Word document", "transform HTML to LaTeX", "change docx to markdown". 中文触发条件：请求在 Html、Markdown、Docx、PDF、LaTeX 格式之间转换文档时触发。示例：「把 Markdown 转 PDF」、「导出为 Word 文档」、「HTML 转 LaTeX」、「docx 转 markdown」。 ## Quick Start 1. Download the WASM file using `wasm-sandbox-download` or let it cache automatically 2. Use `wasm-sandbox-run` with `--work-dir` parameter to specify the directory containing input files (or current working directory) 3. Execute conversion, stats, or validation commands **⚠️ Important:** Always use `--work-dir <directory>` with `wasm-sandbox-run` to grant filesystem access. ## Supported Conversions - Markdown ↔ Html - Markdown ↔ Docx - Markdown ↔ LaTeX - Html ↔ LaTeX - Docx → Html - Docx → Markdown ## Resources For detailed usage instructions and examples, see [USAGE.md](references/USAGE.md).


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ssidharhubble/elliott-wave-counts (version 1.0.1)

--- name: elliott-wave-counts description: Automated wave counting and market cycle prediction. compatibility: OpenClaw, Zo Computer metadata: author: ssidharHubble --- # Elliott Wave Expert Automated wave counting and market cycle prediction. ## Usage This skill connects to the Money Machine x402 API. Calls are free for basic health, but premium signals require a 402 payment proof. ```javascript import { execute } from "elliott-wave-counts"; const signal = await execute({ ticker: "BTC" }); ```

path: index.js
content: 
export async function run({ ticker = "BTC" }) {
  const url = `https://money-machine-x402-ssyopros.zocomputer.io/api/wave/${ticker.toUpperCase()}`;
  const response = await fetch(url);
  if (response.status === 402) {
    return {
      error: "402 Payment Required",
      message: "Premium signal. Send 0.005 SOL to AKz1pZ8yxtFQLwTpDKJGZjLeBUX4rnobX7HdMF3uvK6W",
      payment_url: "https://ssyopros.zo.space/pricing"
    };
  }
  return await response.json();
}

/**
 * @tool
 * @description Automated wave counting and market cycle prediction.
 * @param {string} ticker - Asset ticker (e.g. SPY, BTC, TSLA)
 */
export async function execute(args) {
  return await run(args);
}


path: package.json
content: name: elliott-wave-counts
version: 1.0.1
description: Automated wave counting and market cycle prediction.
author: ssidharHubble
license: MIT
main: index.js
type: module

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: lj-hao/web-auto-analyzer (version 1.1.1)

--- name: Chrome DevTools Auto Analyzer slug: chrome-devtools-auto-analyzer version: 1.1.1 homepage: https://github.com/user/chrome-devtools-auto-analyzer description: Automatically analyze websites for performance metrics and audit issues using Lighthouse. metadata: {"clawic":{"emoji":"🤖","requires":{"bins":["node","npm"],"npm":["lighthouse","chrome-launcher"]},"os":["linux","darwin","win32"]}} --- ## When to Use User wants to automatically analyze a website URL for performance metrics, accessibility, SEO, or best practices without manual Chrome DevTools interaction. ## Core Rules 1. **Verify prerequisites** — Check Node.js (v18+) and packages installed: `node --version && npm list lighthouse chrome-launcher` 2. **Run Lighthouse audit** — Execute `node automation-script.js <URL> [--mobile] [--output=DIR]` to collect all metrics. 3. **Extract and present metrics** — Use tables for scores (0-100) and metrics with status indicators (⚪ Good, 🟡 Warning, 🔴 Critical). 4. **Identify critical issues** — Flag metrics outside thresholds: LCP>2.5s, CLS>0.1, INP>200ms, TBT>200ms, Performance<50. 5. **Provide actionable fixes** — For each issue, include specific code fixes from `audit-checklist.md` and `metrics-reference.md`. 6. **Save results** — Store JSON and HTML reports in `./results/`. Ask user before saving to memory for tracking. 7. **Handle errors gracefully** — If audit fails, check `troubleshooting.md` for common solutions (Chrome not found, ES module errors, memory issues). ## Quick Reference | Topic | File | |-------|------| | Automation script | `automation-script.js` | | Metrics & thresholds | `metrics-reference.md` | | Fix checklists | `audit-checklist.md` | | Setup guide | `setup.md` | | Quick start | `quick-start.md` | | Troubleshooting | `troubleshooting.md` | | Memory tracking | `memory-template.md` | ## Data Storage After analysis, offer to save: URL, timestamp, scores, critical issues, report path. Always ask before saving to memory. ## Security & Privacy - Runs locally in headless Chrome — no external data transmission - Warn before analyzing authenticated URLs - JSON reports contain URL structure — handle sensitive paths carefully ## Common Commands ```bash # Quick audit (desktop) node automation-script.js https://example.com # Mobile emulation node automation-script.js https://example.com --mobile # Custom output directory node automation-script.js https://example.com --output=./reports # Lighthouse CLI directly lighthouse https://example.com --output=json --output-path=report.json ``` ## Troubleshooting Quick Reference | Error | Solution | |-------|----------| | "lighthouse is not a function" | Add `"type": "module"` to package.json | | "Chrome not found" | Install Chrome or use `npm install puppeteer` | | "JavaScript heap out of memory" | Run with `node --max-old-space-size=4096` | | "Port already in use" | Specify different port in script config |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: johnnywang2001/json-schema-toolkit (version 1.0.0)

--- name: json-schema-toolkit description: Validate JSON data against JSON Schema, generate schemas from sample JSON, and convert schemas to TypeScript interfaces, Python dataclasses, or Markdown docs. Use when working with JSON validation, API contract testing, schema generation from examples, or converting JSON Schema to typed code. No external dependencies — pure Python. --- # JSON Schema Toolkit Validate, generate, and convert JSON Schemas with zero dependencies. ## Commands All commands use `scripts/json_schema.py`. ### Generate Schema from Sample Data ```bash python3 scripts/json_schema.py generate --input sample.json python3 scripts/json_schema.py generate --input sample.json --output schema.json echo '{"name":"Jo","age":25}' | python3 scripts/json_schema.py generate --input - ``` Auto-detects string formats (email, date-time, date, uri, ipv4). ### Validate JSON Against Schema ```bash python3 scripts/json_schema.py validate --schema schema.json --data data.json ``` Reports all validation errors with JSON paths. Exit code 1 on failure. ### Convert Schema to Code ```bash python3 scripts/json_schema.py convert --input schema.json --format typescript python3 scripts/json_schema.py convert --input schema.json --format python-dataclass python3 scripts/json_schema.py convert --input schema.json --format markdown --name User ``` Supported formats: `typescript`, `python-dataclass`, `markdown`. ## Supported Validation Keywords type, enum, required, properties, additionalProperties, items, minLength, maxLength, pattern, minimum, maximum, minItems, maxItems, format. ## Stdin Support Use `--input -` to pipe JSON from stdin for both `generate` and `validate --data`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mcbaivn/youtube-scheduler (version 1.0.0)

--- name: youtube-scheduler description: Phân tích lịch đăng video của kênh YouTube để tìm "khung giờ vàng" — thời điểm đăng có nhiều view và engagement nhất. Dùng khi user yêu cầu "Tìm giờ vàng đăng video @Channel", "Best time to post for @Channel", "Kênh này hay đăng lúc mấy giờ", hoặc muốn tối ưu lịch đăng nội dung. --- # ⏰ YouTube Scheduler Analyzer Phân tích lịch đăng của kênh → tìm ngày và giờ có hiệu suất cao nhất. ## Cài đặt ### Cách 1 — Tải skill thẳng từ GitHub (khuyến nghị) ```powershell # Windows $skillDir = "$env:USERPROFILE\.agents\skills\youtube-scheduler" New-Item -ItemType Directory -Force "$skillDir\scripts" | Out-Null Invoke-WebRequest -Uri "https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-scheduler/SKILL.md" -OutFile "$skillDir\SKILL.md" Invoke-WebRequest -Uri "https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-scheduler/scripts/analyze_schedule.py" -OutFile "$skillDir\scripts\analyze_schedule.py" ``` ```bash # macOS / Linux mkdir -p ~/.agents/skills/youtube-scheduler/scripts curl -o ~/.agents/skills/youtube-scheduler/SKILL.md \ https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-scheduler/SKILL.md curl -o ~/.agents/skills/youtube-scheduler/scripts/analyze_schedule.py \ https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-scheduler/scripts/analyze_schedule.py ``` ### Cách 2 — Clone toàn bộ repo ```powershell # Windows git clone https://github.com/mcbaivn/openclaw-skills-mcbai.git Copy-Item -Recurse openclaw-skills-mcbai\skills\youtube\youtube-scheduler $env:USERPROFILE\.agents\skills\ ``` ```bash # macOS / Linux git clone https://github.com/mcbaivn/openclaw-skills-mcbai.git cp -r openclaw-skills-mcbai/skills/youtube/youtube-scheduler ~/.agents/skills/ ``` ## Sử dụng ``` python scripts/analyze_schedule.py <channel_url> [--limit N] [--tz Asia/Ho_Chi_Minh] ``` **Ví dụ:** - `Tìm giờ vàng @MrBeast` → `python scripts/analyze_schedule.py https://youtube.com/@MrBeast --limit 50` - Đổi timezone → thêm `--tz Asia/Ho_Chi_Minh` (mặc định UTC) ## Output ``` Youtube_Schedule/ └── [Channel]_schedule_DD_MM_YYYY.txt ``` **Báo cáo gồm:** - 📅 Ngày trong tuần tốt nhất (sắp xếp theo avg views) - ⏰ Khung giờ vàng (0-23h, theo avg views) - 🗺️ Heatmap Ngày × Giờ (ASCII) - 🏆 Top 5 video views cao nhất với ngày/giờ đăng - 💡 Khuyến nghị lịch đăng tối ưu ## Lưu ý - Phân tích dựa trên `--limit` video gần nhất (khuyến nghị 30-100 video). - Mặc định timezone UTC, dùng `--tz` để chuyển sang giờ địa phương. - Kết quả là ước tính thống kê từ dữ liệu lịch sử, không phải đảm bảo tuyệt đối.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yangyunzhao/netease-web-player-control (version 0.1.6)

--- name: netease-web-player-control description: Control NetEase Cloud Music Web in a browser. Use to (1) search and play a song by keyword, preferably artist + title, or (2) open My Music and play one of the user's own created playlists by keyword. --- # 网易云音乐网页版控制 / NetEase Cloud Music Web Control 中文： 在浏览器中控制网易云音乐网页版。支持两类操作： - 搜歌播放 - 我的音乐歌单播放 建议：搜歌时优先使用“歌手 + 歌名”。 English: Control NetEase Cloud Music Web in a browser. Supports two actions: - song search playback - My Music playlist playback Recommendation: prefer artist + title for song search. ## Trigger phrases 搜歌： - `搜歌 ...` - `搜索 ...` - `播放歌曲 ...` - `找歌 ...` 歌单： - `歌单 ...` - `我的歌单 ...` - `播放我的歌单 ...` - `我创建的歌单 ...` ## Behavior rules - 默认先检查 **我的音乐 → 创建的歌单**；无明确匹配时再走搜歌。 - 搜歌优先匹配 **歌手 + 歌名**，短歌名歧义时先确认，不乱播。 - 仅控制网页版；不处理桌面客户端、下载、逆向或批量抓取。 - 我的歌单模式要求网页已登录。 - 歌曲页播放时，避免误点 **播放mv** 或 **去客户端播放**。 - 点击播放后不要立刻判失败；先短暂等待，再复查底部播放器。 - 只有底部播放器真的切到目标歌曲时，才报告“已开始播放”。 - 如果失败，要明确说明卡在哪一步。 ## Preferred examples - `搜歌 王心凌 爱你` - `搜歌 王心凌 第一次爱的人` - `歌单 游鸿明` - `我的歌单 王心凌`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: love254443233/csdn-article-publish-plus (version 1.0.4)

--- name: csdn-article-publish description: 将 Markdown 文章通过用户目录浏览器会话发布到 CSDN。支持保存草稿、预览排版、人工确认发布；默认保持浏览器打开并复用登录态。 --- # CSDN 文章发布（会话保持版） ## 核心要求 - 使用用户目录浏览器会话（Edge/Chrome），复用已有登录态。 - 默认不关闭浏览器、不丢失上一次会话。 - 不硬编码文章路径、标题、文章 ID、标签等业务信息；全部参数化。 - 发布流程内置“页面排版模块”，默认在回填编辑器前执行。 ## 目录结构 ```text csdn-article-publish/ ├── SKILL.md ├── skill-config.json ├── scripts/ │ └── csdn_browser_publish.js └── docs/ └── usage.md ``` ## 何时调用 - 用户要求“发布到 CSDN”“保存到 CSDN 草稿”“先预览再发布”。 - 用户明确要求保持浏览器会话、复用登录态。 ## 脚本说明（参数化，无硬编码） 脚本：`scripts/csdn_browser_publish.js` - `--mode draft`：打开发布弹窗并保存草稿 - `--mode draft-preview`：保存草稿后关闭弹窗并切换预览 - `--mode publish`：打开发布弹窗并提交发布 通用参数： - `--file <markdown文件路径>`：必填 - `--title <标题>`：可选，默认用文件名 - `--article-id <文章ID>`：可选；传入则打开指定草稿 - `--browser edge|chrome`：可选，默认 `edge` - `--profile-dir <浏览器用户目录>`：可选；不传则按浏览器类型取默认用户目录 - `--keep-open true|false`：可选，默认 `true` - `--typeset true|false`：可选，默认 `true` - `--typeset-profile readable|compact`：可选，默认 `readable` - `--page-typeset true|false`：可选，默认 `true`（页面层排版：尝试关闭 AI 助手侧栏并进入预览态） 二维码文末策略（从配置文件读取）： - 从 `skill-config.json` 的 `env` 字段读取： - `CSDN_VERTICAL_QR_IMAGE_URL` - `CSDN_VERTICAL_QR_DESCRIPTION`（可选） - 若配置不存在，则自动追加“请添加公众号二维码图片及相关说明”的占位提示。 排版模块策略（回填编辑器前）： - 统一标题/列表与正文空行 - 统一代码块前后留白 - 压缩异常连续空行 - `readable`：偏可读性（推荐） - `compact`：偏紧凑展示 页面排版模块策略（浏览器页面层）： - 自动尝试关闭 AI 助手侧栏，扩大阅读区域 - 自动切换到预览态，便于发布前检查 - 结果 JSON 返回 `pageTypesetActions` ## 推荐执行顺序 1. `draft-preview`：保存草稿并预览排版 2. 需要时重复 `draft-preview` 做排版迭代 3. 最终执行 `publish` 或让用户人工确认后发布 ## 异常处理 - 若出现 `ProcessSingleton`/`SingletonLock`：说明浏览器目录被占用。 - 优先复用已打开会话，不强制重启。 - 仅在用户同意下重启浏览器恢复可控会话。 - 若页面元素变更导致按钮失效：更新选择器，不要写死 `ref`。 ## 结果输出 - 每次执行输出 JSON 结果（按钮命中、当前 URL、截图路径）。 - 输出会包含二维码变量状态（`wechatQrConfigured`）。 - 截图默认保存到当前工作目录：`csdn_<mode>_result.png`。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: liujw0214/memory-vacuum (version 1.0.0)

--- name: memory-vacuum description: 轻量化记忆管理。每日自动分片归档，语义压缩，只保留必要信息。0内存占用，重启不丢。用于用户提到内存、清理、整理记忆、减轻负担等场景。 --- # 记忆轻量化系统 让记忆系统保持轻量：按天分片、自动压缩、只保留必要信息，不让记忆文件无限膨胀。 ## 核心原则 **记忆要精，不要多。宁精一条，不要滥十条。** ## 工作方式 ### 每日分片 所有记忆按 `memory/YYYY-MM-DD.md` 日期归档，**不写入同一个大文件**。 ``` memory/ ├── 2026-05-01.md ← 5月1日所有对话 ├── 2026-05-02.md ← 5月2日所有对话 ├── 2026-05-03.md ← 5月3日所有对话 └── MEMORY.md ← 提炼后的精华（体积小，定时精简） ``` ### 自动压缩（每次会话前） 新会话开始前，检查 `MEMORY.md`： - 单条记忆超过 5 行 → 压缩成要点 - 有重复信息 → 合并 - 有过时信息 → 标记但不删除（永远不删除） - 超过 200 行 → 压缩最旧的一半 ### 零内存占用原理 - **不存对话历史**（太初靠上下文） - **不预加载任何东西**（按需读取） - **MEMORY.md 永远小于 50KB**（动态压缩保证） - 真正需要的信息 → MEMORY.md（<50KB） - 原始对话 → 当日日记（按日期分流，不影响加载速度） ## 内存管理规则 | 操作 | 触发条件 | 动作 | |------|---------|------| | 写入日记 | 每条消息 | 追加到 `memory/YYYY-MM-DD.md` | | 写入精华 | 重要信息 | 写入 MEMORY.md（精炼后） | | 压缩 | MEMORY.md > 50KB | 自动压缩最旧记忆 | | 分流 | 单日日记 > 100KB | 拆分月份子文件 | ## 安装 本技能无需额外配置，直接启用即可。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: mirni/greenhelix-bundle-x402-commerce-kit (version 1.3.1)

--- name: greenhelix-bundle-x402-commerce-kit version: "1.3.1" description: "Launch a crypto-native storefront from scratch. Includes the x402 Merchant Starter Kit (deployable code), agent payment rails playbook, and commerce security hardening guide. Deploy in 15 minutes. 2 guides + production code." license: MIT compatibility: [openclaw] author: felix-agent type: bundle includes: [x402-merchant-starter-kit, agent-payment-rails-playbook, agent-commerce-security] price_usd: 99.0 tags: [bundle, code, x402, payments, security, starter-kit, guide, greenhelix, openclaw, ai-agent] executable: false install: none credentials: [GITHUB_TOKEN, WALLET_ADDRESS, DASHBOARD_SECRET, GREENHELIX_API_KEY, AGENT_SIGNING_KEY, STRIPE_API_KEY] metadata: openclaw: requires: env: - GITHUB_TOKEN - WALLET_ADDRESS - DASHBOARD_SECRET - GREENHELIX_API_KEY - AGENT_SIGNING_KEY - STRIPE_API_KEY primaryEnv: GITHUB_TOKEN --- # x402 Commerce Kit: Merchant Starter Kit + Payment Rails Guide + Security Hardening ## Included Guides | Guide | Individual Price | |-------|-----------------| | x402 Merchant Starter Kit: Deploy Your Own Crypto-Native Storefront | $99.00 | | The Agent Payment Rails Playbook | $29.00 | | Locking Down Agent Commerce: The OWASP-Aligned Security Guide for Autonomous AI Agents on GreenHelix | $29.00 | ## Total Value: $157.00 | Bundle Price: $99.00


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kaiyuelv/git-hooks-manager (version 1.0.0)

# git-hooks-manager - Git Hooks管理器 ## Metadata | Field | Value | |-------|-------| | **Name** | git-hooks-manager | | **Slug** | git-hooks-manager | | **Version** | 1.0.0 | | **Homepage** | https://github.com/openclaw/git-hooks-manager | | **Category** | development | | **Tags** | git, hooks, pre-commit, pre-push, lint, test, automation, devops | ## Description ### English A Git hooks manager that simplifies installing, configuring, and sharing Git hooks across teams. Includes pre-built templates for linting, testing, branch naming validation, commit message validation, and custom hook orchestration. ### 中文 Git Hooks管理器，简化团队间Git钩子的安装、配置和共享。包含预置模板：代码检查、测试运行、分支名验证、提交信息验证和自定义钩子编排。 ## Requirements - Python 3.8+ - Git >= 2.30 - click >= 8.0.0 - colorama >= 0.4.6 ## Configuration ### Environment Variables ```bash HOOKS_MANAGER_STRICT=true HOOKS_MANAGER_SKIP_LINT=false ``` ## Usage ### Install Hooks ```bash # Install all recommended hooks python scripts/hooks_manager.py install --all # Install specific hook python scripts/hooks_manager.py install pre-commit # Install from template python scripts/hooks_manager.py install pre-commit --template lint-and-test ``` ### Create Custom Hook ```python from git_hooks_manager import HookManager manager = HookManager() # Define a custom pre-commit hook @manager.hook("pre-commit") def my_pre_commit(): # Run custom checks result = manager.run_command("pytest", ["tests/smoke/"]) if result.returncode != 0: print("Smoke tests failed!") return False return True manager.install() ``` ### Validate Commit Messages ```bash python scripts/hooks_manager.py validate-message "feat: add user login" ``` ## API Reference ### HookManager - `install(hook_name, template=None)` - Install a hook - `uninstall(hook_name)` - Remove a hook - `list_hooks()` - List installed hooks - `validate_commit_message(msg)` - Validate conventional commits format - `validate_branch_name(name)` - Validate branch naming convention - `run_command(cmd, args)` - Run a shell command and return result ### Built-in Templates - `lint-and-test` - Run linters and unit tests - `conventional-commits` - Validate commit messages - `branch-guard` - Enforce branch naming rules - `security-scan` - Run basic security checks - `ci-simulation` - Simulate CI pipeline locally ## Examples See `examples/` directory for complete examples. ## Testing ```bash cd /root/.openclaw/workspace/skills/git-hooks-manager python -m pytest tests/ -v ``` ## License MIT License


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