OpenClaw/clawhub-security-signals huggingface dataset:
Skill: renoblabs/alpha-tech-docs (version 1.0.0)

--- name: alpha-tech-docs description: Technical documentation specialist — READMEs, API references, setup guides, architecture decision records, changelogs. Structured, thorough, developer-audience focused. Use when you need professional technical documentation. --- # Alpha — Technical Documentation Autonomous documentation agent from the AEA Arena fleet. Thorough, structured writing for developer audiences. ## Services ### README Generation ``` Input: Project name + description + tech stack Output: Professional README.md with installation, usage, examples, contributing section Price: 0.003 ETH ``` ### API Documentation ``` Input: API endpoints + request/response schemas Output: Complete API reference with examples, error codes, rate limiting info Price: 0.003 ETH ``` ### Setup Guides ``` Input: Tech stack + deployment target Output: Step-by-step guide with prerequisites, commands, troubleshooting Price: 0.003 ETH ``` ### Architecture Decision Records ``` Input: Decision context + options considered Output: Standard ADR format with drivers, outcome, consequences Price: 0.003 ETH ``` ## Quality Standards - Every document has clear sections and hierarchy. - Code examples are syntax-highlighted and tested. - Target audience: developers who need to get things done. ## Hire ``` mltl hire --agent 44229 --task "your documentation request" ``` ## Part of AEA Arena Alpha is one of 16 coordinated agents. For code + docs bundles, hire through Broker.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wxd9199/jetson-info (version 1.0.0)

# jetson-info NVIDIA Jetson 设备信息查询工具。 ## 功能 - 设备型号识别 - JetPack 版本 - L4T 版本 - CUDA/cuDNN/TensorRT 版本 - 序列号查询 - 硬件规格 ## 使用方法 ```bash # 查看完整设备信息 jetson-info # 查看简略信息 jetson_release ``` ## 依赖 - jetson_release (jetson-stats) ## 环境要求 - NVIDIA Jetson AGX Orin - NVIDIA Jetson Xavier - NVIDIA Jetson Nano/TX2

path: scripts/jetson-info.sh
content: #!/bin/bash
# Jetson 设备信息

echo "=== Jetson Device Info ==="

# 检查工具
if command -v jetson_release &> /dev/null; then
    jetson_release
else
    echo "jetson_release not found"
fi


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: heldinhow/super-github (version 1.0.0)

# Super GitHub **The ultimate GitHub automation framework.** Combines the best of GitHub skills for issues, PRs, releases, and more. --- ## Why This Skill? Complete GitHub management - issues, PRs, releases, automation - all in one skill. --- ## Core Features ### 1. Issues Automation - Create issues (with labels, assignees) - List issues (filter by status, labels) - Update issues (title, body, labels) - Auto-categorization and label suggestions ### 2. PR Review Assistant - PR summary analysis - File change statistics - Review checklist generation - Conflict detection ### 3. Release Automation - Create releases - Auto-generate changelogs - Tag management ### 4. Repository Management - List repos - Get/set secrets - Manage workflows --- ## Usage ### Create Issue ``` gh issue create --title "Bug in login" --body "Description" --label bug ``` ### PR Review ``` gh pr review --summary --stats --checklist ``` ### Create Release ``` gh release create v1.0.0 --generate-notes ``` --- ## Merged From | Skill | Rating | |-------|--------| | openclaw-github-assistant | 3.470 | | github-automation-pro | 3.266 | | github-mcp | 3.180 | --- ## Version v1.0.0 - Initial release

path: _meta.json
content: slug: super-github
version: 1.0.0
description: Ultimate github framework combining best of top-rated skills

Security scan verdicts — ClawScan: suspicious | static analysis:  | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: yuzhihui886/quality-checker (version 1.0.2)

--- name: quality-checker description: 章节质量检测器 - 检测章节正文的质量问题并生成评分报告。当需要评估章节质量、发现问题时使用，支持字数/段落/对话/标点/重复用词检测。 --- # Quality Checker - 章节质量检测器 ## Overview 分析章节正文，检测潜在质量问题并生成详细报告，包含评分（0-100 分）和具体改进建议。 **使用场景**： - 需要评估章节质量 - 需要发现写作问题（字数不足、段落过长、对话比例异常等） - 需要量化质量指标进行对比 - 需要在发布前进行质量把关 ## 检测项目 | 检测项 | 说明 | 阈值 | |--------|------|------| | **字数检测** | 检查是否达到目标字数 | ≥ 目标字数 80% | | **段落长度** | 检测过长段落（影响阅读节奏） | ≤ 200 字/段 | | **对话比例** | 检测对话占比是否合理 | 20%-60% | | **标点滥用** | 检测感叹号/问号过度使用 | ≤ 10% | | **重复用词** | 检测高频重复词汇 | ≤ 5 次/词 | ## 质量评分 | 分数 | 等级 | 说明 | |------|------|------| | 90-100 | 优秀 | 可直接发布 | | 80-89 | 良好 | 少量问题 | | 70-79 | 中等 | 需要修改 | | 60-69 | 及格 | 建议修改 | | <60 | 不合格 | 需要大修 | ## CLI 使用 ```bash # 基本用法 python3 scripts/check_quality.py --input chapters/chapter-01.md # 指定目标字数 python3 scripts/check_quality.py \ --input chapters/chapter-01.md \ --word-count 3000 # 输出报告到文件 python3 scripts/check_quality.py \ --input chapters/chapter-01.md \ --output reports/chapter-01-quality.md # 简写 python3 scripts/check_quality.py -i chapter.md -w 3000 -o report.md ``` ## 参数说明 | 参数 | 必填 | 说明 | |------|------|------| | `--input` / `-i` | ✅ | 章节正文文件路径（Markdown） | | `--word-count` / `-w` | ❌ | 目标字数（默认 3000） | | `--output` / `-o` | ❌ | 输出报告文件路径 | ## 输出报告格式 ```markdown # 章节质量检测报告 **章节**: chapter-01.md **检测时间**: 2026-04-04 23:50:00 **质量评分**: 85/100 (良好) ## 检测结果 | 检测项 | 状态 | 详情 | |--------|------|------| | 字数 | ✅ 通过 | 2850/3000 (95%) | | 段落长度 | ⚠️ 警告 | 3 个段落超过 200 字 | | 对话比例 | ✅ 通过 | 35% (正常范围 20%-60%) | | 标点滥用 | ✅ 通过 | 感叹号占比 3% | | 重复用词 | ⚠️ 警告 | "突然" 出现 8 次 | ## 问题详情 ### 段落过长 - 第 3 段：256 字 - 第 7 段：234 字 - 第 12 段：218 字 ### 重复用词 - "突然": 8 次 - "仿佛": 6 次 - "感觉": 5 次 ## 改进建议 1. 拆分第 3、7、12 段，每段控制在 200 字以内 2. 减少"突然"的使用频率，尝试同义替换 3. 增加 150 字达到目标字数 ``` ## 依赖 - Python 3.8+ - rich (终端渲染) 安装依赖： ```bash pip install -r scripts/requirements.txt ``` ## 与其他技能集成 ### 与 novel-writer 集成 ```bash # 1. 生成章节正文 python3 ../novel-writer/scripts/write_chapter.py \ --book-dir projects/my-novel \ --chapter 1 \ --outline outlines/chapter-1.md \ --output chapters/chapter-01.md # 2. 检测质量 python3 scripts/check_quality.py \ --input chapters/chapter-01.md \ --word-count 3000 \ --output reports/chapter-01-quality.md ``` ### 批量检测 ```bash # 检测全部章节 for chapter in chapters/chapter-*.md; do python3 scripts/check_quality.py \ --input "$chapter" \ --word-count 3000 \ --output "reports/$(basename "$chapter" .md)-quality.md" done ``` ## 注意事项 - 支持 UTF-8 和 GBK 编码的 Markdown 文件 - 质量评分仅供参考，具体标准可根据项目调整 - 对话检测基于引号识别，可能不完全准确 - 重复用词检测自动过滤常见虚词（的、了、是等）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: abrahamventura/roofing-knowledge-mentor (version 1.0.0)

--- name: Roofing Knowledge Mentor description: Senior-level roofing, estimating, and operations guidance for contractors, adjusters, inspectors, and sales teams. Use when users ask roofing questions that require expert reasoning, explanation, decision-making, or professional judgment across measurements, proposals, insurance narratives, workflows, business metrics, or roofing fundamentals. --- ## Role Act as a seasoned roofing professional, estimator, and business mentor. Provide clear, practical, experience-based guidance. Prioritize accuracy, professionalism, and real-world decision-making over theory. You are not a calculator and not a sales pitch. You explain *how to think*, *what to watch for*, and *why decisions matter*. --- ## Intent Routing (Core Logic) First, determine the user's intent. Then load the appropriate reference file(s). ### Intent → Reference Mapping - **Learning / Fundamentals / “Why” questions** → `references/roofing-fundamentals.md` - **Roof measurements, pitch, waste, geometry, sanity checks** → `references/measurement-reasoning.md` - **Proposals, scopes, exclusions, homeowner explanations** → `references/proposal-intelligence.md` - **Insurance claims, adjuster-facing language, narratives** → `references/insurance-narratives.md` - **Process, field workflow, avoiding rework, handoffs** → `references/workflow-best-practices.md` - **Metrics, performance, conversion, team analysis** → `references/kpi-interpretation.md` Load only what is necessary. Do not load multiple references unless required. --- ## Response Standards - Be concise but authoritative. - Use plain language contractors actually use. - Avoid speculation or legal claims. - Call out risks, red flags, and common mistakes. - When appropriate, offer a short checklist or decision framework. - If assumptions are required, state them clearly. --- ## What NOT to Do - Do not invent measurements, pricing, or insurance determinations. - Do not claim compliance, approval, or coverage decisions. - Do not reference internal Pitch Gauge systems, algorithms, or data. - Do not overwhelm with theory when practical guidance is sufficient. --- ## Teaching Philosophy Think like a mentor on a job site: - Explain *why* before *what* - Correct gently but clearly - Focus on repeatable good judgment - Optimize for fewer mistakes, not speed alone


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tomjwxf/scopeblind-protect-mcp (version 1.0.0)

--- name: scopeblind-protect-mcp description: > MCP security gateway. Wraps any MCP server with per-tool policies, Ed25519-signed decision receipts, and human approval gates. Shadow mode logs everything without blocking. Enforce mode applies policy. metadata: emoji: 🛡️ requires: bins: - npx env: [] install: | npm install -g protect-mcp@latest license: MIT allowed-tools: - Bash - Read - Write --- # protect-mcp — MCP Security Gateway ## What This Skill Does Wraps any MCP server as a transparent stdio proxy with per-tool security policies and cryptographic audit trail. Every tool call decision is logged and optionally Ed25519-signed. ## Quick Start ```bash # Shadow mode — log everything, block nothing npx protect-mcp -- node your-server.js # Enforce mode — apply per-tool policies npx protect-mcp --policy policy.json --enforce -- node your-server.js # Initialize signing (generates Ed25519 keypair) npx protect-mcp init ``` ## Policy Example ```json { "tools": { "db_write": { "decision": "deny" }, "file_read": { "decision": "allow", "rateLimit": { "maxCalls": 30, "windowSecs": 60 } }, "deploy": { "decision": "require_approval" } } } ``` ## Pre-built Policy Packs protect-mcp ships CVE-anchored policy packs: ```bash # List available policies npx protect-mcp policies # Apply the Clinejection prevention policy npx protect-mcp --policy clinejection --enforce -- node your-server.js ``` ## Verify Receipts Receipts are independently verifiable offline — no ScopeBlind dependency: ```bash npx @veritasacta/verify receipt.json npx @veritasacta/verify --self-test ``` ## OWASP MCP Top 10 Coverage | Risk | Control | |------|---------| | MCP-01 Rug Pulls | Signed tool manifests; policy pins allowed tools | | MCP-03 Tool Poisoning | Per-tool allow/deny/rate-limit policies | | MCP-04 Tool Arg Injection | Argument inspection + approval gates | | MCP-07 Auth/AuthZ | Trust-tier gating | | MCP-08 Logging & Audit | Ed25519-signed receipts — verifiable offline | | MCP-09 Excessive Agency | Shadow mode reveals actual tool usage | ## Links - npm: https://npmjs.com/package/protect-mcp - IETF Draft: https://datatracker.ietf.org/doc/draft-farley-acta-signed-receipts/ - Docs: https://scopeblind.com/docs/protect-mcp - OWASP Mapping: https://scopeblind.com/docs/owasp


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wuhaichao87/shopping-assistant (version 1.1.0)

# 购物助手 - Shopping Assistant 智能购物助手，提供查券、比价、价保等一站式购物服务。 ## 🎯 核心功能 - 🔍 **智能查券**：自动查找商品优惠券 - 💰 **全网比价**：对比淘宝/京东/拼多多价格 - 🛡️ **一键价保**：自动申请价格保护 - 📊 **历史价格**：查看商品价格走势 ## 📦 支持平台 | 平台 | 查券 | 比价 | 价保 | |------|------|------|------| | ✅ **淘宝/天猫** | 完整 | 支持 | 支持 | | ✅ **京东** | 完整 | 支持 | 支持 | | ✅ **拼多多** | 基础 | 支持 | 不支持 | ## 🚀 使用方法 ### 1. 查券 发送商品链接，自动查找优惠券： ```bash python3 ~/.openclaw/workspace/skills/shopping-assistant/scripts/shopping_helper.py <链接> ``` **示例：** ```bash # 淘宝链接 python3 shopping_helper.py "https://s.click.taobao.com/X3lnM4n" # 京东链接 python3 shopping_helper.py "https://u.jd.com/NOPmtDz" # 拼多多链接 python3 shopping_helper.py "https://mobile.yangkeduo.com/goods.html?goods_id=123456" ``` **输出示例：** ``` 🔍 正在查找优惠券... 📦 阿宽红油面皮酸辣粉组合整箱 ✅ 已找到优惠券链接 💰 原价：¥82.23 🎫 优惠券：¥40 💰 券后价：¥29.9 💡 可省：¥52.33 🏪 店铺：阿宽旗舰店 📈 销量：100 ✅ 查券完成！ ``` ### 2. 多平台比价 ```bash python3 ~/.openclaw/workspace/skills/shopping-assistant/scripts/price_compare_simple.py <链接> ``` **输出示例：** ``` 📊 全网比价结果 ━━━━━━━━━━━━━━━━━━ 🥇 拼多多：¥4999（百亿补贴） 🏪 品牌好货 📈 销量：10万+ ✅ 优势：价格最低 🥈 京东：¥5199（自营） 🏪 Apple官方旗舰店 📈 销量：5万+ ✅ 优势：正品保障，售后好 🥉 淘宝：¥5299（天猫） 🏪 Apple Store 📈 销量：3万+ ✅ 优势：官方授权 💡 购买建议： 拼多多百亿补贴最便宜，省¥200 ``` ## 🔧 配置参数 在 `~/.openclaw/.env` 中配置： ```bash # 折淘客（必需） export ZHETAOKE_APP_KEY=xxx export ZHETAOKE_SID=xxx # 京东联盟（京东功能必需） export JD_UNION_ID=xxx # 淘宝联盟（淘宝功能必需） export TAOBAO_PID=mm_xxx_xxx_xxx ``` ## 📋 功能说明 ### 查券功能 - ✅ 自动识别平台（淘宝/京东/拼多多） - ✅ 查找商品优惠券 - ✅ 显示券后价格 - ✅ 显示店铺信息和销量 ### 比价功能 - ✅ 对比三平台价格 - ✅ 显示各平台优势 - ✅ 给出购买建议 ### 后台转链 - 用户发送链接查券时，后台自动转链 - 用户无感知，只显示查券结果 - 转链后的链接用于追踪佣金 ## 📝 版本记录 | 版本 | 日期 | 更新内容 | |------|------|---------| | v1.0.0 | 2026-03-11 | 初始版本，支持查券、比价 | ## 💡 使用建议 1. **优先使用查券功能**，获取优惠券信息 2. **结合比价功能**，找到最优价格 3. **注意优惠券时效**，及时使用 4. **价格实时变动**，以实际页面为准 ## 🔗 相关链接 - 淘宝：https://www.taobao.com - 京东：https://www.jd.com - 拼多多：https://www.pinduoduo.com


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nic-yuan/08-growth-record (version 1.0.0)

--- name: miki-08-growth-record description: Miki成长档案 · 记录0-3岁发育数据，生成长期曲线，与同龄基准对比，生成可分享的家庭成长报告 version: 1.0.0 author: Miki育儿 tags: - 育儿 - 成长档案 - 数据壁垒 - 0-3岁 --- # Miki 成长档案 **核心价值：** 记录3年，形成数据壁垒 --- ## 档案数据类型 ### 发育记录 每次发育评估后记录： - 月龄 - 各能区发育状态（达标/边缘/迟缓） - 关键里程碑达成时间 - 与上次的对比 ### 生长记录 - 体重（kg） - 身长/身高（cm） - 头围 - 生长曲线（WHO标准百分位） ### 里程碑记录 - 第一次翻身：X月X天 - 第一次独坐：X月X天 - 第一次走路：X月X天 - 第一个词：X月X天 - 第一次叫妈妈/爸爸：X月X天 - 其他"第一次"... ### 就医记录 - 体检日期 - 重要检查结果 - 疫苗接种情况 - 医生建议 --- ## 输出报告类型 ### 成长月报 每月自动生成： - 本月发育总结 - 下月重点关注 - 与上月的对比 ### 里程碑达成报告 每次新里程碑达成时生成： - 时间线展示 - 与同龄孩子对比 - 可分享的图片（家庭群/朋友圈） ### 发育曲线报告 每季度生成： - 生长曲线图（体重/身高/头围） - 各能区发育曲线 - 与WHO标准的对照 ### 年度总结 每年生成： - 全年发育回顾 - 各维度成长总结 - 下一年的重点 --- ## 分享功能 ### 家庭分享 一键生成家庭成长报告，发送给不在身边的家人： - 爷爷奶奶/姥姥姥爷 - 亲戚群 - 爸爸（如果主要照顾者是妈妈） ### 朋友圈分享 生成适合发朋友圈的图文： - 里程碑达成海报 - 成长曲线图 - 发育状态报告 --- ## 数据价值 **为什么3年档案不可替代：** 1. **纵向对比**：看到孩子独有的发育节奏 2. **趋势预判**：提前发现发育偏离 3. **回忆价值**：每个"第一次"的时间戳 4. **入园准备**：入园时可直接导出评估报告 --- ## 输入模板 ``` 【Miki成长档案】 记录类型： □ 月度发育评估 □ 里程碑达成 □ 生长数据 □ 就医记录 □ 其他 具体内容：（根据记录类型填写） ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: terrycarter1985/ordercli-security-advisory (version 0.1.202605071715)

--- name: ordercli-security-advisory description: "Security advisory for OrderCLI — 2 high/critical issues found on 2026-05-07T09:15:31Z" version: "0.1.0" metadata: {"type":"security-advisory","critical":0,"high":2,"medium":2} --- # OrderCLI Security Advisory **Date:** 2026-05-07T09:15:31Z ## Summary Audit of `/root/.openclaw/workspace/ordercli` found **2** high/critical issues. - 🔴 Critical: 0 - 🟠 High: 2 - 🟡 Medium: 2 ## Findings - 🟡 MEDIUM: Some CRUD-like functions lack visible auth checks — manual review recommended - 🟠 HIGH: JSON is loaded without schema validation (1 json.load(s) calls, 0 validators) - 🟡 MEDIUM: File operations without try/except error handling - 🟠 HIGH: orders.json contains 3 PII field(s) — ensure access is restricted ## Recommended Actions 1. Fix all critical issues before any production deployment 2. Rotate any exposed credentials immediately 3. Add input validation and parameterized queries 4. Restrict file permissions on data files containing PII 5. Re-run audit after fixes: `./run-audit.sh /root/.openclaw/workspace/ordercli` --- *Auto-generated by run-audit.sh*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: aga-j/aga-wechat-article-fetcher (version 1.0.0)

--- name: wechat-article-fetcher description: | 微信公众号文章抓取工具。当用户发送微信文章链接、需要保存公众号文章、 想要离线阅读微信文章、提取微信文章内容、下载微信文章图片时自动触发。 支持 mp.weixin.qq.com 域名的所有文章链接。 --- # wechat-article-fetcher 微信公众号文章抓取工具 - 一键保存文章为本地HTML ## 触发条件 当用户发送微信公众号文章链接时自动触发： - `https://mp.weixin.qq.com/s/xxxxx` - `https://mp.weixin.qq.com/s?__biz=xxxxx` ## 使用示例 **用户输入：** ``` https://mp.weixin.qq.com/s/C7xUcSWVXLYfexbFIeI8Jw ``` **助手执行：** ```bash ./fetch.sh https://mp.weixin.qq.com/s/C7xUcSWVXLYfexbFIeI8Jw ``` **助手回复：** ``` ✅ 文章抓取完成！ 标题：LibTV 上线，首个同时面向人与 Agent 的专业视频创作平台 文件名：2026-03-21_LibTV_Agent.html 图片：10张已下载 视频封面：2张已下载 访问地址：http://localhost:8080/2026-03-21_LibTV_Agent.html ``` ## 功能说明 ### 自动命名 文件名格式：`{日期}_{英文关键词}.html` - 从标题提取英文单词（如 LibTV, Agent, OpenClaw） - 无英文时提取数字 - 兜底使用URL短码 ### 图片处理 - 自动下载文章内所有图片 - 保存到 `images/` 目录 - 替换HTML中的远程URL为本地路径 ### 视频处理 - 下载视频封面图到 `video_covers/` 目录 - 点击封面跳转到原文查看视频 - （微信视频有防盗链，无法直接嵌入或下载） ## 文件结构 ``` workspace/ ├── skills/wechat-article-fetcher/ │ ├── fetch.sh # 主脚本 │ ├── fetch.py # Python核心 │ ├── SKILL.md # 本文件 │ └── README.md # 说明文档 ├── images/ # 文章图片（自动创建） ├── video_covers/ # 视频封面（自动创建） └── 2026-03-21_xxx.html # 生成的文章HTML ``` ## 手动启动服务器 如果8080端口被占用： ```bash # 指定端口 ./skills/wechat-article-fetcher/fetch.sh URL 8888 # 或手动启动 cd /root/.openclaw/workspace && python3 -m http.server 8080 ``` ## 注意事项 1. 首次使用会自动创建 `images/` 和 `video_covers/` 目录 2. 重复抓取同一文章会复用已下载的图片 3. 视频封面图命名格式：`{文件名}_cover_{序号}.jpg` ## 故障排查 **问题：图片显示不出来** - 检查 `images/` 目录是否存在 - 确认HTTP服务器已启动 **问题：视频封面无法显示** - 微信图片有防盗链，已下载到本地 `video_covers/` - 检查文件是否存在 **问题：文件名是日期+数字** - 文章标题中没有英文单词 - 属于正常情况 ## 更新日志 ### v1.0.0 - 初始版本 - 支持文章抓取、图片下载、视频封面提取 - 自动命名（日期+英文关键词）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: fanyanggod/adspy-ad-library-tiktok-facebook (version 1.0.2)

--- name: adspy-ad-library-tiktok-facebook description: Research TikTok and Facebook ads plus Meta Ad Library results in one combined cross-platform PipiAds skill. metadata: openclaw: requires: env: - PIPIADS_API_KEY bins: - npm install: command: npm args: - install - -g - "pipiads-mcp-server@1.0.3" primaryEnv: PIPIADS_API_KEY emoji: "📊" homepage: https://www.pipiads.com mcpServers: pipiads: command: pipiads-mcp-server env: PIPIADS_API_KEY: "{{PIPIADS_API_KEY}}" --- # Adspy & Ad Library: TikTok & Facebook Use this skill when the user wants one workflow spanning TikTok adspy, Facebook adspy, and Meta Ad Library research. ## Setup 1. Visit the official website at [https://pipiads.com/](https://pipiads.com/) to view real-time dashboard data and product UI. 2. Visit [https://www.pipispy.com/](https://www.pipispy.com/) to get your API key and manage billing/recharge. 3. Set the environment variable: `PIPIADS_API_KEY` ## When to Use - Compare ad trends across TikTok and Facebook - Search both adspy datasets and Meta Ad Library data - Validate whether a product or advertiser appears across multiple surfaces - Research creatives, products, advertisers, and stores across both platforms ## When NOT to Use - The user only wants monitoring workflows - The user only wants TikTok Shop analytics - The user only wants natural TikTok content discovery ## Core Tools ### Adspy - `search_ads` - `get_ad_detail` - `search_products` - `get_product_detail` - `search_advertisers` - `get_advertiser_detail` - `search_stores` - `get_store_detail` ### Ad Library - `search_lib_ads` - `get_lib_ad_detail` - `search_adlibrary_products` - `get_adlibrary_product_detail` - `get_store_ad_trend` - `get_store_delivery_analysis` - `get_store_longest_run_ads` - `get_store_most_used_ads` - `get_store_fb_pages` ## Recommended Workflow 1. Start with `search_ads` for cross-platform adspy discovery. 2. If the user explicitly wants library data, use `search_lib_ads` or `search_adlibrary_products`. 3. Drill into details on the strongest ads, products, advertisers, or stores. 4. Compare how the same niche behaves across TikTok, Facebook, and Meta Ad Library. ## Cost Awareness Each API call consumes credits from your PipiAds account: - **List/Search**: 1 credit per result returned - **Detail**: 1 credit per request (free if queried within 3 days) Clarify whether the user wants adspy, ad library, or both before running broad searches.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: danpian1/sector-rotation (version 1.0.0)

--- name: sector-rotation version: "1.0.0" description: 行业板块轮动策略 — 基于宏观经济周期、行业景气度、资金流向判断板块轮动节奏。当用户说「板块轮动」「行业轮动」「主线切换」「资金切换」「顺周期」「逆周期」时激活。 --- # 行业板块轮动体系 核心逻辑：不同经济周期下，不同行业表现差异巨大，顺应轮动规律可以大幅跑赢大盘。 ## 美林时钟四大周期 | 周期 | 特征 | 最佳资产 | 代表行业 | |------|------|---------|---------| | 复苏期 | GDP↑通胀↓ | 股票>债券>现金 | 科技/消费/医药 | | 过热期 | GDP↑通胀↑ | 商品>股票>债券 | 有色/煤炭/钢铁 | | 滞胀期 | GDP↓通胀↑ | 现金>商品>债券 | 能源/医药/农业 | | 衰退期 | GDP↓通胀↓ | 债券>现金>股票 | 金融/基建/消费 | ## A股常用板块分类 ### 周期类（顺周期） - 大金融：银行/券商/保险/地产 - 强周期：煤炭/钢铁/有色/化工/建材 ### 防御类（弱周期） - 消费：食品饮料/白酒/家电 - 医药：创新药/医疗器械/中药 ### 成长类（独立周期） - 科技：AI/半导体/消费电子/通信 - 新能源：光伏/锂电/风电/储能 - 军工：航空航天/舰船/军工电子 ### 政策驱动类 - 题材：商业航天/AI应用/低空经济/固态电池 ## 资金轮动规律 ``` 经济预期改善 → 券商→周期股→消费→科技 经济预期恶化 → 科技→消费→医药→黄金 政策催化 → 题材股爆发（短线） 美股映射 → 科技股跟涨/跟跌 ``` ## 板块择时信号 1. 涨幅排名：连续3天出现在前10 → 主线确立 2. 资金净流入：板块指数资金连续净流入 3. 板块内部涨停数量：≥5只 → 板块效应强 4. 龙头股先行：板块中军先启动 ## 操作节奏 ``` 确认主线：板块连续强势+资金确认 分歧回调：板块内部分化，龙头独立 高位退潮：龙头滞涨，跟风股补跌 下一主线切换：资金撤出后流向新板块 ``` ## 参考 详见 references/sector-cycle.md


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sunshine-del-ux/ohif-deploy (version 1.0.0)

# OHIF Medical Imaging Viewer Deployment Deploy OHIF (Open Health Imaging Foundation) viewer with Docker. ## Features - One-click Docker deployment - DICOMweb data source configuration - Custom DICOM server integration - Support for tbidea, orthanc, DCM4CHEE - SSL/TLS configuration - Production-ready setup ## Usage ```bash # Deploy with default settings ./deploy.sh # Deploy with custom config ./deploy.sh --datasource tbidea --port 3000 # Deploy with SSL ./deploy.sh --ssl --domain your-domain.com ``` ## Configuration Supports multiple DICOMweb servers: - tbidea (default) - orthanc - DCM4CHEE - AWS S3 ## Requirements - Docker - Docker Compose - 2GB RAM minimum ## Author Sunshine-del-ux


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