OpenClaw/clawhub-security-signals huggingface dataset:
Skill: lzmjlrt/gmod-addon-maker (version 1.0.0)

--- name: gmod-addon-maker description: A tool for creating and managing Garry's Mod addons, including Lua scripting, content creation, and addon packaging.Use when: developing new addons, writing Lua scripts for GMod, organizing addon files, or when user mentions Garry's Mod, GMod, Lua scripting, or addon development. metadata: author: SLAR_Edge version: "1.0" --- # GMod Addon Maker You are a GMod addon development assistant, skilled in Lua scripting, content creation, and addon packaging for Garry's Mod. ## When to Apply Use this skill when: - Developing new addons for Garry's Mod - Writing Lua scripts for GMod - Debugging GMod addons - Organizing addon files and directories - Packaging addons for distribution ## Addon Development Workflow When creating a GMod addon, follow these steps: 1. **Conceptualization** - Define the addon’s purpose and features. - Identify target audience and use cases. 2. **Lua Scripting** - **Structure**: Follow the file organization patterns defined in [addon-structure](references/addon-structure.md). - **Core Concepts**: Use [gmod-lua-states](references/state-exp.md) to understand strictly defined Server/Client/Shared realms. - **Specific API Lookup Rule**: - **STRICT PROHIBITION**: You are **FORBIDDEN** from constructing URLs by guessing (e.g., Do NOT try `wiki.facepunch.com/gmod/hook`). Most guessed URLs are 404 errors. - **Action Sequence**: 1. **Search Query**: If you have a search tool, use query `"gmod wiki <term>"` first to extract the correct URL. 2. **Navigation**: If you must browse manually, you just fetch url and search the content,the url is `https://wiki.facepunch.com/gmod` and the search term is the API or concept you want to find. Do NOT guess URLs. 3. **Read & Follow**: Read the index page content to find the specific function link. 3. **Content Creation** - Create or source models, textures, sounds, and other assets as needed for the addon. - Ensure all content is properly licensed for use in your addon. - Ensure content is optimized for performance and compatibility. 4. **Testing and Debugging** - Tell user to test the addon in-game to identify and fix bugs or issues. - See the [common-issues](references/common-error.md) reference for common problems and solutions during addon development.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wuchubuzai2018/wechat-article-search (version 0.1.0)

--- name: wechat-article-search description: 搜索微信公众号文章技能。通过微信搜索获取文章列表，覆盖科技/AI、社会热点、财经、教育、职场等各类中文资讯；可按关键词检索并返回标题、概要、发布时间、来源公众号与链接。当用户需要查找微信公众号文章、整理参考资料或快速获取文章信息时使用此技能。 --- # 微信公众号文章搜索说明 ## 适用场景 - 用户说“帮我搜某个关键词的公众号文章/最近文章” - 需要快速拿到：标题、摘要、发布时间、公众号名称、可访问链接 ## 工作流程 ### 步骤1: 确认已安装依赖包 该脚本依赖NodeJS依赖包 `cheerio`，建议先执行全局安装或在项目中安装： ```bash npm install -g cheerio ``` ### 步骤2: 确认搜索词语数量 1、 确认关键词与数量 ### 步骤3: 执行搜索命令 1、执行常规搜索命令 ```bash node scripts/search_wechat.js "关键词" ``` ## 特殊流程（可选） 1) 执行包含数量限制的搜索命令 ```bash node scripts/search_wechat.js "关键词" -n 15 ``` 2) 如果用户需要保存结果到文件，执行命令 ```bash node scripts/search_wechat.js "关键词" -n 20 -o result.json ``` 3) 若想要获取微信文章域名的真实链接”，执行如下命令 ```bash node scripts/search_wechat.js "关键词" -n 5 -r ``` ## 参数说明 - `query`：搜索关键词（必填） - `-n, --num`：返回数量（默认 10，最大 50） - `-o, --output`：输出 JSON 文件路径（可选） - `-r, --resolve-url`：尝试把中间链接解析成微信文章真实链接（会额外请求每条结果） ## 输出字段（文章对象） 文章标题、文章地址、文章概要、发布时间、来源公众号名称 ## 常见问题处理 - 结果为空：尝试更换关键词、更少的特殊字符、或稍后重试 - 解析真实 URL 失败：这是常态（反爬限制）；可提示用户用浏览器打开中间链接 ## 注意事项 - 本工具仅用于学习和研究目的，请勿用于商业用途或大规模爬取。 - 使用本工具时请遵守相关网站的使用条款和规定。 - 过度使用可能导致 IP 被封禁，请谨慎使用。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: seichris/linkdrop-agent-cli (version 1.0.0)

--- name: linkdrop-agent-cli description: Create and redeem Linkdrop claim links from the command line with strict JSON output on Base, Polygon, Arbitrum, Optimism, and Avalanche. version: 1.0.0 metadata: openclaw: requires: env: - PRIVATE_KEY - LINKDROP_API_KEY - RPC_URL - RPC_URL_POLYGON - RPC_URL_BASE - RPC_URL_ARBITRUM - RPC_URL_OPTIMISM - RPC_URL_AVALANCHE - LINKDROP_BASE_URL - LINKDROP_API_URL bins: - node - npm primaryEnv: PRIVATE_KEY homepage: https://github.com/seichris/linkdrop-sdk-cli --- When to use - You need to create a funded Linkdrop claim link from a local wallet. - You need to redeem a Linkdrop claim link to a destination address. - You need stdout to be exactly one JSON object for automation. Files in this skill - `linkdrop-agent.js` is the strict JSON CLI entrypoint. - `agentdrop-core.js` contains the Linkdrop and chain logic used by the CLI. - `.env.example` shows the supported runtime configuration. Setup 1. Run `npm install`. 2. Set secrets in your shell or `.env`: - Required: `PRIVATE_KEY`, `LINKDROP_API_KEY` - Recommended for Base: `RPC_URL_BASE` - Optional fallback: `RPC_URL` 3. Keep secrets out of git history. Supported chains - `base` default - `polygon` - `arbitrum` - `optimism` - `avalanche` Send a claimable transfer 1. Native token on Base: - `node linkdrop-agent.js send --amount 0.01 --token native --chain base` 2. ERC20 on Polygon: - `node linkdrop-agent.js send --amount 5 --token 0xTokenAddress --chain polygon` 3. Read these JSON fields from stdout: - `claimUrl` - `transferId` - `depositTx` Claim a transfer 1. Run: - `node linkdrop-agent.js claim --url "https://..." --to 0xRecipient --chain base` 2. Read `redeemTx` from stdout. JSON contract - Success returns `{ ok: true, ... }`. - Failure returns `{ ok: false, error: { code, name, message, details? } }`. - The CLI writes one JSON object to stdout per invocation. Troubleshooting - `Missing PRIVATE_KEY`: set a 32-byte hex private key with `0x` prefix. - `Missing LINKDROP_API_KEY`: set a valid Linkdrop API key with the `zpka_` prefix. - `No RPC URL available`: set `RPC_URL_BASE` for Base or the matching `RPC_URL_<CHAIN>`. - `Unsupported chain`: use one of the supported chain names above.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: ethan-china/miniest-review (version 1.0.0)

--- name: minimalist-review description: > 通过极简主义创业者框架审查任何业务决策、计划或策略。 当有人想对业务决策进行直觉检验、想简化方法，或需要在选项之间做决定时使用。 核心：用8个原则检验任何决策。 trigger_keywords: - 极简主义审查 - 决策检验 - 这个决定好吗 - 我该怎么做 - 帮我评估 - 检查一下 read_when: - 用户面临一个重要的业务决策需要评估 - 用户想知道某个计划是否符合极简主义原则 - 用户在选项之间纠结需要明确方向 --- # 极简主义审查 — 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。通过极简主义创业者框架审查用户的决策或情况。 ## 极简主义创业者的8个原则 将这些原则应用于评估用户提出的任何内容： ### 1. 社群第一 - 这是否服务于你的社群？还是由自我、虚荣指标，或"成功公司所做的事"驱动？ - 你是否与你的客户保持密切联系？ - 亚马逊在每次董事会会议上放一把空椅子代表客户。你在做等同的事情吗？ ### 2. 先手动，再自动化 - 你是否过度构建？这可以先手动完成吗？ - "流程化"先于"产品化" - 你手动做这件事足够多次以知道它有效吗？ ### 3. 尽可能少地构建 - 你能在一个周末内发布这个吗？ - 使某人的生活好一点点的最简单版本是什么？ - 你是为今天的客户构建还是为假想的未来客户构建？ ### 4. 先销售，再扩展 - 真实的人用真实的钱为此付费了吗？ - 你是否在销售之前就试图营销？（销售在前，营销在后） - 手动销售 = 早期增长的99% ### 5. 先花时间，再花钱 - 你能用时间而不是金钱来做这件事吗？ - 博客文章、社交媒体、个人外联都是免费的 - 只有在已经有机运作的基础上才花钱加速 ### 6. 盈利是目标 - 这个决定让你更接近还是更远离盈利？ - 你是"默认存活"还是"默认死亡"？ - 这可逆吗？避免不可逆决策（长期租约、大规模招聘、风投条款） ### 7. 以客户的速度增长 - 你的客户要求这个吗？还是你在猜测？ - 你的公司将以你的客户决定的速度增长 - 绝大多数小企业从未被大鱼吃掉 ### 8. 建造你想住的房子 - 这与你的价值观一致吗？ - 如果你继续做这样的决定，5年后你愿意在这家公司工作吗？ - 你在构建一个不拥有你的业务吗？ ## 决策框架 对于任何决策，评估： | 问题 | 回答 | |------|------| | 这是否服务于我的社群/客户？ | | | 这是最简单的方法吗？ | | | 这是否改善盈利能力？ | | | 如果不成功，这可逆吗？ | | | 我在花时间还是花钱？ | | | 客户要求过这个吗？ | | | 这与我的价值观一致吗？ | | | 一年后我还会想要这个吗？ | | ## 常见的极简主义创业者建议 - "不要发布。先向前100个客户销售。" - "当它很痛苦时才招聘。" - "你的失败会消退，而你的成功会留下来并复利增长。" - "盈利能力让你离开电网。然后你以无限跑道有意地增长。" - "自私地为自己建造正确的业务，同时无私地服务他人社群。" ## 输出 给用户： 1. 明确的建议（做 / 不做 / 简化） 2. 他们计划的极简主义版本是什么样的 3. 他们应该注意的最大风险 4. 本周可以尝试验证决策的一件事


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zero2ai-hub/skill-dropshipping-sourcing (version 1.0.2)

--- name: skill-dropshipping-sourcing description: Query CJ Dropshipping API v2.0 to source products and fetch details for catalog building. Use for CJ keyword search, pulling product records (SPU/SKU, images, categories, variants/colors when available), refreshing access tokens, and producing normalized JSON outputs for dropshipping catalog automation. --- # CJ Sourcing Use this skill to reliably pull CJ product data (instead of manual browsing). ## Files / creds (local convention) - Config: `./cj-api.json` - `apiKey`, `baseUrl`, `accessToken`, `tokenExpiry` ## 1) Refresh access token ```bash node scripts/token.js ``` ## 2) Search products by keyword (listV2) ```bash node scripts/source.js --keyword "sunset lamp" --size 20 --out cj-results.json ``` Output: `cj-results.json` with normalized fields. ## Notes - Token refresh is conservative (refreshes ~10 minutes before expiry). - `source.js` uses `GET /product/listV2` and requests `enable_description` + category fields.


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: garibong-labs/ipo-alert (version 0.1.2)

--- name: ipo-alert description: 한국 공모주 청약/신규상장 일정 알림. 38.co.kr에서 데이터 수집, D-1/당일 알림, 주간 요약 제공. metadata: openclaw: requires: bins: ["python3", "curl"] triggers: - 공모주 - IPO - 청약 - 상장 - 38.co.kr --- # IPO Alert Skill 38.co.kr에서 공모주청약 일정과 신규상장 정보를 모니터링하고 알림을 보냅니다. ## 포함 파일 | 파일 | 설명 | |------|------| | `SKILL.md` | 이 문서 | | `check_ipo.py` | 메인 스크립트 (Python 3.6+, 표준 라이브러리만 사용) | ## 데이터 소스 - 공모주청약 일정: https://www.38.co.kr/html/fund/index.htm?o=k - 신규상장: https://www.38.co.kr/html/fund/index.htm?o=nw ## 의존성 - Python 3.6+ (표준 라이브러리만 사용, 추가 패키지 불필요) - `curl` (38.co.kr 데이터 수집에 사용) ## 설치 후 설정 1. 상태 파일 디렉토리 생성: `mkdir -p ~/.config/ipo-alert` 2. 크론잡 또는 HEARTBEAT.md에 체크 추가 ## 스크립트 스킬 디렉토리 기준 상대경로로 실행합니다: ```bash # 스킬 경로 변수 (설치 위치에 맞게) SKILL_DIR="<workspace>/skills/ipo-alert" # 일일 체크 (청약 D-1, 당일 알림) python3 "$SKILL_DIR/check_ipo.py" daily # 주간 요약 (다음주 일정) python3 "$SKILL_DIR/check_ipo.py" weekly # 현재 일정 확인 (테스트용) python3 "$SKILL_DIR/check_ipo.py" list ``` ## 알림 규칙 ### 일일 알림 (daily) - 청약 시작 **하루 전** (D-1): "⏰ [내일 청약 시작]" - 청약 시작 **당일** (D-day): "🚀 [오늘 청약 시작]" - 신규상장 **하루 전**: "⏰ [내일 신규상장]" - 신규상장 **당일**: "🎉 [오늘 신규상장]" ### 주간 요약 (weekly) - 매주 일요일 저녁에 실행 - 다음주 월~금 청약/상장 일정 리스트 ## 상태 파일 `~/.config/ipo-alert/state.json` - 이미 알림 보낸 종목 추적 (중복 알림 방지) ## HEARTBEAT.md 설정 예시 ```markdown ## 공모주 알림 (every heartbeat) On each heartbeat: 1. Run `python3 <skill_dir>/check_ipo.py daily` 2. If output contains alerts (not "알림 없음") → 사용자에게 알림 전송 ``` ## Cron 설정 (주간 요약) 일요일 저녁 7시에 다음주 일정 요약: ```json { "schedule": { "kind": "cron", "expr": "0 19 * * 0", "tz": "Asia/Seoul" }, "payload": { "kind": "agentTurn", "message": "공모주 주간 요약 발송해줘." } } ``` ## 알림 예시 ### 일일 알림 ``` ⏰ [내일 청약 시작] 📋 [카나프테라퓨틱스](https://www.38.co.kr/html/fund/?o=v&no=2269) 청약: 03/05(목)~06(금) 공모가: 16,000~20,000 주간사: 한국투자증권 ``` ### 주간 요약 ``` 📅 다음주 공모주 일정 (03/03 ~ 03/07) 【청약 일정】 📋 [카나프테라퓨틱스](https://www.38.co.kr/html/fund/?o=v&no=2269) 청약: 03/05(목)~06(금) 공모가: 16,000~20,000 주간사: 한국투자증권 【신규상장】 🔔 [케이뱅크](https://www.38.co.kr/html/fund/?o=v&no=2271) 상장일: 03/05(수) 공모가: 8,300~9,500 ``` ## 라이선스 MIT ## 문의 / Feedback 버그 리포트, 기능 요청, 피드백은 아래로 보내주세요. - Email: [REDACTED_SECRET] - Developer: Garibong Labs (가리봉랩스)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: tylordius/tavily-tool (version 0.1.1)

--- name: tavily description: Use Tavily web search/discovery to find URLs/sources, do lead research, gather up-to-date links, or produce a cited summary from web results. metadata: {"openclaw":{"requires":{"env":["TAVILY_API_KEY"]},"primaryEnv":"TAVILY_API_KEY"}} --- # Tavily Use the bundled CLI to run Tavily searches from the terminal and collect sources fast. ## Quick start (CLI) The scripts **require** `TAVILY_API_KEY` in the environment (sent as `Authorization: Bearer ...`). ```bash export TAVILY_API_KEY="..." node skills/tavily/scripts/tavily_search.js --query "best rust http client" --max_results 5 ``` - JSON response is printed to **stdout**. - A simple URL list is printed to **stderr** by default. ## Common patterns ### Get URLs only ```bash export TAVILY_API_KEY="..." node skills/tavily/scripts/tavily_search.js --query "OpenTelemetry collector config" --urls-only ``` ### Restrict to (or exclude) specific domains ```bash export TAVILY_API_KEY="..." node skills/tavily/scripts/tavily_search.js \ --query "oauth device code flow" \ --include_domains oauth.net,datatracker.ietf.org \ --exclude_domains medium.com ``` ## Notes - The bundled CLI supports a subset of Tavily’s request fields (query, max_results, include_domains, exclude_domains). - For API field notes and more examples, read: `references/tavily-api.md`. - Wrapper script (optional): `scripts/tavily_search.sh`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: huajianjiu000/cv-enhancer (version 1.0.0)

--- name: cv-enhancer description: 优化您的简历通过ATS筛选。获得HR青睐的专业中文简历，含STAR法则、量化数据、关键词优化，符合国内求职市场习惯。 version: 1.0.0 author: muqing tags: [简历, 求职, 找工作, ATS, 职业发展] --- # 简历优化助手 ## 功能说明 将您的简历打造成HR眼中脱颖而出的求职利器。优化ATS（人才管理系统）友好格式、专业措辞、量化成果，帮您获得更多面试机会。 ## 使用方法 1. 提供您的现有简历（或关键信息） 2. 说明目标岗位/行业 3. 突出您的核心成就 4. 提及目标公司或职位 5. 获取专业优化的简历 ## 示例 **输入**： 我有一个3年工作经验的运营简历，想应聘产品经理岗位，简历内容如下： - 负责公司公众号运营，粉丝增长 - 参与产品需求讨论 - 用户反馈收集 **输出**： 优化后的简历片段： - 主导公司公众号运营策略制定，**粉丝量从2万增长至8万，增长率300%**，单篇爆款阅读量突破10万+ - **深度参与5个核心产品功能的需求调研与迭代**，协同产品团队完成用户需求文档撰写 - 建立用户反馈闭环机制，**累计收集分析用户反馈2000+条**，推动产品优化20余项


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

--- name: segmentfault-hot-trend description: 注册“SegmentFault”热门技能；当需要访问或自动化SegmentFault相关内容时调用。 homepage: `https://segmentfault.com/` metadata: {"clawdbot":{"emoji":"🔥"}} --- # SegmentFault 用途与边界 - 面向公开问答与文章页的检索与技术要点摘要 - 不提供接口逆向或批量抓取能力 - 仅用于公开页面的轻量信息整理 关键入口 - 主页：https://segmentfault.com/ - 问答与文章频道：站点入口 - 搜索入口：https://segmentfault.com/search 常见任务 - 指定关键词的问答摘要（标题、标签、点赞/回答数） - 技术文章的要点提取（技术栈、问题/解决方案） - 标签分布与主题趋势统计 数据字段 - 标题、作者、发布时间、标签、点赞数、回答数、链接 - 技术栈、问题与解决方案摘要 - 采集时间、来源链接 自动化要点 - 动态渲染与人机校验，建议人工打开后触发解析 - 请求频率需控制，不进行批量抓取 - 不进行接口调用 示例流程 - 问答摘要：输入关键词 → 搜索 → 抽取条目 → 输出互动指标 - 文章要点：访问文章页 → 提取技术栈/问题/方案 → 输出摘要 - 标签统计：收集条目 → 基于标签分类 → 生成主题趋势 合规提示 - 遵守平台规则，不进行接口调用或批量采集 - 结果仅用于内部分析与提醒


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fhekg/session-rename-zh (version 1.0.2)

--- name: session-rename description: "改会话名、rename session、会话标签、修改会话标题、session label" metadata: openclaw: displayName: 会话名称修改 tagline: 直接编辑 sessions.json 给会话加 label，修改 OpenClaw 会话显示名称 slug: session-rename-zh homepage: https://github.com/fhekg/openclaw-session-rename --- # 会话名称修改 (Session Rename) 通过直接编辑 `sessions.json` 给会话加 `label` 字段来修改显示名称。 OpenClaw 没有 CLI 或 RPC 方式修改会话标题，但 JSON store 可以直接编辑。 ## 效果演示 ![改名效果](assets/demo.png) ## 触发 用户说「改会话名」「把这个会话叫 XXX」「rename session」「设置会话标签」「修改会话标题」等。 ## 工作流 1. 确认目标会话（当前会话 / 指定会话）和想要的名字 2. 如果是当前会话，用 `sessions_list` 拿到当前 session key 3. 用 python3 安全读取、修改、写回 `sessions.json` ## 改当前会话 ```bash python3 -c " import json path = '/Users/xingbin/.openclaw/agents/main/sessions/sessions.json' with open(path, 'r') as f: data = json.load(f) key = '<SESSION_KEY>' # 从 sessions_list 获取 if key in data: data[key]['label'] = '<新名称>' with open(path, 'w') as f: json.dump(data, f, indent=2, ensure_ascii=False) print(f'✅ 已设置 label: <新名称>') " ``` 4. 改完后用 `sessions_list` 验证 `displayName` 和 `derivedTitle` 已生效 ## 改其他会话 - `sessions_list` 找到目标会话的 key - 同上流程，替换 key 和 label 值 ## 列出所有会话 ```bash python3 -c " import json data = json.load(open('/Users/xingbin/.openclaw/agents/main/sessions/sessions.json')) for k, v in data.items(): print(f'{k} → {v.get(\"label\", \"(无标签)\")}') " ``` ## 注意事项 - `sessions.json` 路径固定：`~/.openclaw/agents/main/sessions/sessions.json` - 用 python3 操作 JSON，不要用 sed/shell 字符串拼接，避免破坏格式 - 安全操作：读取→修改→写回，不删不改其他字段 - 只添加 `label` 字段，不影响其他功能


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chongjie-ran/memory-health-check (version 1.0.0)

# 🩺 memory-health-check > **Version:** 1.0.0 > **Skill ID:** `memory-health-check` > **Status:** Ready for Development ## Quick Reference | 项目 | 内容 | | ---- | ---- | | 核心功能 | 6维内存健康诊断（完整性/新鲜度/膨胀率/孤儿/去重/覆盖率） | | 主入口 | `bin/health_check.sh` | | 依赖 | OpenClaw v2026.4.9+, sqlite3 | ## Features (MVP) 1. **Integrity scan** — DB corruption / checksum checks 2. **Bloat detection** — DB size, file count, growth rate 3. **Orphan detection** — Entries with zero inbound references 4. **Freshness report** — Entry age distribution 5. **Dedup scanner** — Duplicate / near-duplicate entries 6. **Health score** — Aggregate 0–100 score across all dimensions 7. **Auto-repair** — Orphan cleanup on user approval ## File Structure ``` memory-health-check/ ├── SKILL.md # This file ├── bin/ │ ├── health_check.sh # Main entry point │ ├── integrity_scan.py # DB corruption checks │ ├── bloat_detector.py # Size analysis │ ├── orphan_finder.py # Reference graph orphan detection │ ├── dedup_scanner.py # Duplicate detection │ ├── freshness_report.py # Entry age distribution │ └── health_score.py # Aggregate scoring ├── scripts/ │ ├── generate_report.py # Report generator │ └── auto_repair.py # Cleanup script ├── config/ │ └── thresholds.yaml ├── reports/ │ └── .gitkeep └── README.md ``` ## Usage ```bash # Full health check memory-health-check/bin/health_check.sh # With auto-repair memory-health-check/bin/health_check.sh --auto-repair # Specific dimensions only memory-health-check/bin/health_check.sh --dims integrity,bloat ``` ## Health Score Dimensions | Dimension | Healthy | Warning | Critical | |-----------|---------|---------|----------| | Integrity | ✅ | ⚠️ | 🔴 | | Freshness (>70%) | >70% | 40–70% | <40% | | Bloat | <500MB | 500MB–2GB | >2GB | | Orphans | 0% | 1–5% | >5% | | Dedup | <2% | 2–10% | >10% | | Coverage | >80% | 50–80% | <50% | ## Pricing | Tier | Price | Features | |------|-------|----------| | Free | $0 | 1 scan/week, text report | | **Pro** | **$9.90/mo** | Unlimited scans, 6-dim diagnostics, auto-repair, 90-day history | | Bundle | **$17.90/mo** | dreaming-optimizer Pro + memory-health-check Pro | ## Development See: ``


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tsekaluk/mineru-skill (version 3.1.0)

--- name: mineru description: An AI-Native skill for parsing PDF / Office / image files into Markdown with MinerU — a fast, zero-config document parser for AI agents. Works with NO token via the Agent API and auto-upgrades to the Standard API (token) for large files, batches, and DOCX/HTML/LaTeX export. Use when converting PDF/Word/PPT/Excel/image documents, extracting text/tables/formulas, running OCR, or batch processing. metadata: author: Nebutra version: "3.1.0" argument-hint: <pdf-file-or-url> --- # MinerU PDF Parser Parse PDF, Office, and image documents into structured Markdown via the MinerU API. ## Quick Start ```bash # Zero-config: no token, no install (free Agent API) python3 "${CLAUDE_PLUGIN_ROOT}/scripts/mineru.py" ./document.pdf --output ./output/ # Pipe Markdown back to an agent python3 "${CLAUDE_PLUGIN_ROOT}/scripts/mineru.py" ./document.pdf --stdout # Power mode: token unlocks large files / batch / extra formats export MINERU_TOKEN="..." # https://mineru.net/apiManage/token python3 "${CLAUDE_PLUGIN_ROOT}/scripts/mineru.py" ./pdfs/ --output ./output/ --workers 8 --resume ``` ## Features - **Auto-routing**: free Agent API by default, auto-upgrades to the Standard API (token) for large/batch/extra-format jobs - **Multi-modal**: PDF, images, Word, PPT, Excel, HTML - **High-performance OCR**: `--ocr` with language selection (`--lang`) - **Formula & table recognition**: LaTeX formulas, structured tables - **Multi-format export**: Markdown (default), plus DOCX / HTML / LaTeX - **AI-Native output**: `--stdout` (Markdown) and `--json` (machine status) - **Batch + resume**: parallel workers with `--resume` - **Zero dependencies**: standard library only ## Authentication A token is **optional** — the Agent API works without one. Set a token to unlock the Standard API (≤ 200 MB / ≤ 200 pages, batch, DOCX/HTML/LaTeX): ```bash export MINERU_TOKEN="your-token-here" # https://mineru.net/apiManage/token ``` Official API docs: https://mineru.net/apiManage/docs


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sky-lv/skylv-mock-server-generator (version 1.0.0)

# mock-server-generator Create mock HTTP servers for API testing and development. Generate fake data, define endpoints, and simulate responses without a real backend. ## Overview A skill that helps developers create mock APIs quickly for testing frontend applications, prototyping, or decoupling microservices development. ## Features - **Quick Server Creation**: Generate a mock server with a single command - **Custom Endpoints**: Define custom routes, methods, and response bodies - **Dynamic Responses**: Use templates to generate realistic fake data - **Delay Simulation**: Add latency to simulate real network conditions - **Error Simulation**: Easily simulate 4xx/5xx error responses - **Data Persistence**: Store and retrieve mock data across requests - **OpenAPI Import**: Generate mocks from OpenAPI/Swagger specifications ## Commands ### Start a Basic Mock Server ``` start mock server on port 3000 ``` ### Define Custom Endpoints ``` add GET /api/users returning [{"id": 1, "name": "John"}] add POST /api/posts with delay 500ms ``` ### Import from OpenAPI ``` generate mock from https://api.example.com/openapi.json ``` ## Use Cases - Frontend development without a backend - API testing and test data generation - Prototyping and demo environments - CI/CD pipeline testing - Microservice decoupling ## Requirements - Node.js 18+ - Optional: Docker for containerized deployment


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: freedompixels/cn-age-calculator (version 1.2.5)

slug: cn-age-calculator name: 年龄计算器 version: "1.0.0" author: 千策 # 年龄计算器 年龄计算器。精确计算年龄、生日倒计时、星座生肖。 ## 功能 - **精确年龄**：年/月/日精确计算 - **生日倒计时**：距离下次生日还有多少天 - **星座判定**：12星座自动识别 - **生肖判定**：12生肖自动识别 - **多格式输入**：YYYY-MM-DD / YYYY年MM月DD日 / MM-DD ## 安装要求 - Python 3.6+ - 无外部依赖 ## 使用方法 ```bash # 计算全部信息 python3 scripts/age_calculator.py "1990-05-15" # 指定计算类型 python3 scripts/age_calculator.py "1990-05-15" --action age python3 scripts/age_calculator.py "1990-05-15" --action countdown python3 scripts/age_calculator.py "1990-05-15" --action zodiac ``` ## 示例 输入：`1990-05-15` 输出： ``` 年龄: 35岁11个月12天 星座: 金牛座 生肖: 马 距离下次生日: 23天 ``` ## 分类 生活工具 ## 关键词 年龄, 生日, 星座, 生肖, 倒计时, age, birthday, zodiac


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: a-vb/indexquery (version 1.0.0)

--- name: 承运商指数查询 description: 基于Excel表格及指标定义，生成承运商维度的指数、行业平均数据，并支持历史趋势图展示与指标构成解析 --- ## How To Use 当承运商或者运营查询某天的承运商物流指数总分时输出 ## Rules 1. 用户输入excel路径，读取excel信息，表头行为统计日期，列为承运商名称 2. 解析表格内容，查询输入中的承运商名称及统计日期的物流指数总分数据 3. 计算出在该统计日期下所有承运商物流指数总分的平均值作为行业平均 4. 计算查询的承运商在该统计日期下与行业平均的差值，及行业排名。若低于行业平均值大于5%，记为严重，红色标签；若低于行业平均值3%，记为警告，黄色标签；若低于行业平均值1%，记为提示，蓝色标签； 5. 调用http://jingwe.jdl.com/#/indexCenter/indexDirection 获取物流指数总分分子指标的构成，及权重占比。 6. 调用Delta法定位物流总分变动的主要影响子指标 7. 点击下载后，调用在该统计日期下该承运商在影响最大子指标的异常明细才进行下载。http://jingwe.jdl.com/#/indexCenter/shipperOverview 在该网址下筛选条件为用户输入承运商、统计日期，省份默认全国 ## input - 读取本地文件.xlsx 或 .csv 表格数据 ## output 1. 该承运商在该统计日期的物流指数总分，行业平均值，与行业平均值的差值及标签，该承运商行业排名 2. 该承运商在该统计日期T-7至统计日期的物流指数总分曲线图，行指标为日期，列值为该承运商在曲线日期的值 3. 定位影响比例最大的子指标 4. 输出运营建议及异常明细


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