OpenClaw/clawhub-security-signals huggingface dataset:
Skill: geoffrey-xiao/npm-package-scan (version 1.0.0)

--- name: NPM Package Scanner description: Scan npm packages used in a repository for risk, maintenance health, and upgrade concerns. metadata: openclaw: requires: bins: - rg - jq - bun - npm --- # NPM Package Scanner Use this skill when you need to inspect the npm packages used by a repository and identify security, maintenance, and dependency risks. ## Goal Produce a practical package-risk review for the current repository: - what dependencies are installed - which ones are direct vs transitive - which ones look stale, risky, or unnecessary - whether there are known audit issues - whether version ranges are too loose or outdated ## Scope Focus on: - `package.json` - lockfiles such as `package-lock.json`, `bun.lock`, `pnpm-lock.yaml`, or `yarn.lock` - workspace package manifests - scripts that introduce package/tooling risk - duplicated or overlapping dependencies Use the reference notes in `references/checklist.md` and `references/commands.md` when useful. ## Workflow 1. Find package manifests and lockfiles. 2. Read the root `package.json` and any workspace manifests. 3. List direct dependencies and devDependencies. 4. Check for: - very old package versions - abandoned or suspicious packages - duplicate packages solving the same problem - unnecessary runtime dependencies - risky postinstall/build hooks - overly broad semver ranges 5. Run available package-manager audit commands if appropriate. 6. Summarize findings by severity. 7. Recommend concrete next steps. ## Commands Prefer fast repo inspection first: ```bash rg --files | rg '(^|/)(package\.json|package-lock\.json|bun\.lock|pnpm-lock\.yaml|yarn\.lock)$' ``` Inspect manifests: ```bash cat package.json ``` If using Bun: ```bash bun pm ls bun audit ``` If using npm: ```bash npm ls --depth=0 npm audit ``` If using pnpm: ```bash pnpm ls --depth=0 pnpm audit ``` If using yarn: ```bash yarn list --depth=0 yarn audit ``` ## Output format Return: 1. High-risk findings 2. Medium-risk findings 3. Low-risk cleanup items 4. Packages worth upgrading soon 5. Packages that may be removable 6. Exact commands to verify or fix ## Review rules - Prioritize real risk over noise. - Distinguish direct dependencies from transitive ones. - Do not recommend upgrades blindly; mention likely blast radius. - If audit output is noisy, extract only actionable items. - If no serious issues are found, say so explicitly. ## Constraints - Do not modify dependency versions unless explicitly asked. - Do not remove packages unless explicitly asked. - Do not assume a package is abandoned without evidence from the repo context or audit/tool output.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wwumit/ccpa-comliance (version 1.0.4)

--- name: ccpa-compliance description: | 美国加州消费者隐私法（CCPA/CPRA）合规专用工具。当用户需要处理加州消费者数据、 CCPA/CPRA合规检查、消费者权利保障、选择退出机制实现等相关任务时使用此skill。 🎉 版本1.0.4重要更新：纯本地运行，无需安装任何外部依赖 --- # 美国加州消费者隐私法（CCPA/CPRA）合规Skill v1.0.4 ## ⚖️ 重要法律声明 ### 免责条款 1. **非法律建议**：本技能提供合规指导，不构成法律意见 2. **专业咨询**：重大合规决策必须咨询专业律师 3. **责任限制**：用户对使用后果负全责 4. **适用性**：专为加州CCPA/CPRA设计 ## 🎯 功能概述 ### 核心功能 - ✅ CCPA合规检查 - ✅ 消费者权利检查 - ✅ 数据销售检查 - ✅ 服务提供商协议检查 - ✅ 合规文档生成 ### 安全特性 - 🔒 纯本地运行 ✅ 已强化 - 🔒 无网络调用 ✅ 已强化 - 🔒 数据安全 - 🔒 代码透明 - ⚡ 零依赖安装 ✅ 新增 ## 🚀 快速开始 ### 安装 ```bash openclaw skill install ccpa-compliance-1.0.3.skill ``` ### 基本使用 ```bash # CCPA合规检查 python scripts/ccpa-check.py # 安全检查 python scripts/security_check_ccpa.py ``` ## 📁 文件结构 ``` ccpa-compliance-1.0.4/ ├── SKILL.md # 主文档 ├── README.md # 详细说明 ├── CHANGELOG.md # 更新日志 ├── package.json # 包信息 ├── requirements.txt # 依赖说明（无实际依赖） ├── SECURITY_CHECK_GUIDE.md # 安全指南 ├── scripts/ # 核心脚本 │ ├── ccpa-check.py # CCPA检查工具 │ ├── consumer-rights.py # 消费者权利检查 │ ├── opt-out-check.py # 选择退出检查 │ ├── security_check_ccpa.py # 安全检查 │ └── utils/ # 工具函数库 ├── references/ # 参考文档 │ └── ccpa-law.md # CCPA法规摘要 ``` ## 🔧 技术规格 ### 依赖 🎉 重要更新 - Python >= 3.8（仅需标准库） - **无需安装pandas、jinja2等外部包** - **所有功能使用Python标准库实现** ### 运行环境 ✅ 已强化 - 纯本地环境 - 无需网络连接 - 零依赖安装 ## 📊 使用场景 ### 场景1：企业合规自查 - 检查CCPA适用性 - 评估合规状况 ### 场景2：数据销售管理 - 识别数据销售活动 - 检查选择退出机制 ### 场景3：服务提供商管理 - 检查服务提供商协议 - 确保CCPA合规要求 ## 📈 成功案例 ### 案例1：加州科技公司 - 实现CCPA合规 - 通过监管检查 ### 案例2：电商平台 - 管理数据销售 - 降低合规风险 ## 🔄 版本管理 ### 当前版本：1.0.4 🎉 重要更新 - **解决网络依赖矛盾**：移除pandas、jinja2等外部依赖要求 - **强化纯本地声明**：所有功能使用Python标准库 - **简化安装流程**：无需pip install，直接运行 - **更新文档一致性**：确保所有文档与代码一致 ### 更新日志 详见 CHANGELOG.md ## 📞 支持 ### 文档 - README.md - 使用说明 - SECURITY_CHECK_GUIDE.md - 安全指南 - references/ccpa-law.md - 法规参考 ### 建议 - 阅读安全指南 - 测试环境验证 - 定期检查更新 --- **发布日期**：2026年3月29日 **版本**：CCPA Compliance v1.0.4 **状态**：✅ 安全验证通过 | 🔒 纯本地运行 | ⚡ 零依赖安装


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: pigbun-ai/pigbun-rednote (version 0.8.1)

# PigBun RedNote 小红书 AI 运营工具 —— 搜索、发布、分析、互动，一站式自动化。 ## 功能概览 本技能为 OpenClaw 提供 27 个小红书工具，覆盖内容创作、社交互动和数据分析全流程。 ## 前置要求 1. 从 [pigbunai.com](https://pigbunai.com) 获取免费 API Key（每天 50 次调用） 2. 安装 Playwright：`npx playwright install chromium` 3. 首次使用前运行 `openclaw rednote init` 扫码登录小红书 ## 工具列表 ### 搜索与内容获取 | 工具 | 说明 | |------|------| | `search_notes` | 根据关键词搜索笔记 | | `get_note_content` | 获取笔记详细内容 | | `get_note_comments` | 获取笔记评论列表 | ### 发布笔记 | 工具 | 说明 | |------|------| | `publish_note` | 发布图文笔记（至少 1 张图片） | | `publish_note_video` | 发布视频笔记 | | `publish_note_text` | 发布纯文字笔记（自动生成封面） | | `publish_note_article` | 发布长文笔记（标题无字数限制） | ### 笔记管理 | 工具 | 说明 | |------|------| | `get_my_notes` | 获取自己的笔记列表 | | `edit_note` | 编辑已发布笔记的标题、正文、标签 | | `delete_note` | 删除已发布的笔记 | ### 评论互动 | 工具 | 说明 | |------|------| | `comment_note` | 在笔记下发表评论 | | `reply_comment` | 回复指定评论 | | `filter_comments` | 评论情感分类（正面/负面/问题/建议/中性） | ### 社交互动 | 工具 | 说明 | |------|------| | `like_note` | 给笔记点赞 | | `collect_note` | 收藏笔记 | | `follow_author` | 关注笔记作者 | ### 数据分析 | 工具 | 说明 | |------|------| | `get_dashboard_overview` | 创作者数据总览（曝光、观看、互动、涨粉） | | `get_content_analytics` | 每篇笔记的详细数据 | | `get_fans_analytics` | 粉丝数据（总量、新增/流失、画像） | | `discover_trending` | 发现热门话题（多关键词热度对比） | | `analyze_best_publish_time` | 分析最佳发布时间 | | `generate_content_report` | 生成综合运营报告 | | `get_inspiration_topics` | 获取灵感话题（含参与人数、浏览量） | | `get_activity_center` | 获取官方活动列表（流量扶持、奖励） | ### 其他 | 工具 | 说明 | |------|------| | `login` | 浏览器登录小红书 | | `get_notifications` | 获取通知消息（评论、点赞、关注） | | `get_share_link` | 获取笔记分享链接 | ## 使用示例 搜索笔记： ``` 搜索关键词"咖啡推荐"的热门笔记 ``` 发布笔记： ``` 帮我发布一篇关于今日早餐的图文笔记，标题"元气早餐分享"，配上这张图片 /path/to/photo.jpg ``` 数据分析： ``` 生成我最近 7 天的运营报告 ``` 评论管理： ``` 帮我查看最新笔记的评论，筛选出提问类评论并逐一回复 ``` ## 配置 在 OpenClaw 插件配置中设置 API Key： ```json { "plugins": { "entries": { "pigbun-rednote": { "enabled": true, "config": { "apiKey": "pb_live_your_key_here" } } } } } ``` ## 链接 - 官网：[pigbunai.com](https://pigbunai.com)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: leooooooow/creator-outreach (version 1.0.0)

--- name: creator-outreach description: Write and improve creator outreach messages, follow-ups, and collaboration angles. Use when contacting creators for partnerships, improving reply rates, personalizing outreach, building short outreach sequences, or adapting outreach by creator tier, niche, and offer type. --- # Creator Outreach Write outreach that is clear, specific, and easy to reply to. ## Workflow 1. Identify the outreach goal. - first contact - follow-up - revive a stalled conversation - send a clear brief / offer summary 2. Gather the minimum context. - creator name / handle - why this creator specifically - product / offer - desired next step - any proof, budget, or timing constraint 3. Choose the right angle. - fit-based: why the creator matches the product - result-based: proof or performance angle - simplicity-based: make the next step easy 4. Draft the message. - short opening - specific reason for reaching out - simple offer / ask - low-friction CTA ## Output format Return: - subject / opener line if needed - primary outreach draft - short follow-up draft - personalization note - CTA options ## Quality bar - Sound human, not automated. - Avoid generic praise. - Keep first-touch outreach short. - Make the next step obvious. - Do not invent proof, metrics, or budget details. ## Resources Read `references/output-template.md` for a reusable sequence shape.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: juguangyuan520-dotcom/report-generator (version 1.0.2)

--- name: "report-generator" description: "Generates a structured report HTML based on a specific template. Invoke when user wants to create a report, slide, or summary card from raw content." --- # Report Generator Skill This skill generates a beautifully formatted HTML report based on a clean, minimal business template style (Light & Concise). ## Capabilities 1. **Refine Content**: Structures raw text into a 4-quadrant format (Goal, Q1-Q4 details, Summary). 2. **Generate HTML**: Creates a responsive HTML file. 3. **Screenshot**: (Instruction) Guides the agent to convert the HTML to an image using the browser tool. ## Usage ### 1. Prepare Data You need to extract the following information from the user's input: - **title**: Report Title - **goal**: One-sentence goal (Top section) - **q1** to **q4**: Four main sections, each containing: - `title`: Short title (e.g., "稳交付") - `subtitle`: Explanatory subtitle - `slogan`: Catchy slogan - `items`: List of bullet points (Array of strings) - **summary**: Array of 4 keywords for the bottom summary ### 2. Run Generation Script Execute the python script with the JSON data: ```bash python3 scripts/generate.py --output "workspace/reports" --data '{"title": "...", ...}' ``` ### 3. Convert to Image (Agent Action) After the script returns the `html_path`, use the **browser** tool to screenshot it: 1. Open the file: `file://<html_path>` 2. Take a screenshot of the full page. ## Example Data Structure ```json { "title": "2024 Q3 述职报告", "goal": "构建可规模化的非平台件能力体系", "q1": { "title": "稳交付", "subtitle": "解决扛量问题", "slogan": "保交付，争第一", "items": ["保障核心需求上线", "降低事故概率"] }, "q2": { ... }, "q3": { ... }, "q4": { ... }, "summary": ["稳定性", "增长", "效率", "反馈"] } ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: wuweikang/daily-brief-writer (version 1.0.1)

--- name: daily-brief-writer description: Turn scattered notes, chat logs, meeting fragments, issue updates, or calendar context into a concise daily brief. Use when Codex needs to summarize what happened today, prepare an end-of-day update, draft a manager-ready status note, or convert messy bullets into a structured daily digest with priorities, blockers, and next actions. --- # Daily Brief Writer ## Workflow 1. Collect the available source material before drafting. Use the user's notes as the source of truth, and mark missing or inferred context explicitly. 2. Separate facts from interpretation. Keep dated events, decisions, metrics, blockers, and asks traceable to the input. 3. Draft in this order: - Headline: one sentence with the most important takeaway. - Done today: completed work or resolved decisions. - In progress: active threads and current state. - Blockers or risks: items needing attention. - Next actions: concrete owner/action/date when available. 4. Keep the brief concise by default. Prefer 5-9 bullets total unless the user asks for detail. 5. Preserve sensitive wording carefully. Do not invent commitments, owners, dates, or metrics. ## Style - Write plainly and professionally. - Prefer active voice and concrete nouns. - Combine duplicate updates across sources. - Use neutral language for uncertain or unresolved items. - If the input is mostly Chinese, draft in Chinese; if mostly English, draft in English. ## Output Shapes Use the default daily brief format unless the user asks for a specific channel. Default: ```markdown **Daily Brief** Headline: ... Done today: - ... In progress: - ... Blockers / risks: - ... Next actions: - ... ``` For Slack or chat, make it shorter and remove empty sections. For email, add a subject line and a greeting only if the user asks for an email-ready draft. ## Reference For stricter section rules and examples, read `references/brief-format.md`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dinghaibin/transform-tool (version 1.0.0)

--- name: transform-tool description: Apply data transformations like case changes, encoding conversion, and format conversion. Use for text processing and data cleaning. --- # Transform - Data Transformation Utility Apply various text transformations including case conversion (upper/lower/title), whitespace trimming, character replacement, and encoding changes. ## Usage ```bash transform-tool [options] <file> ``` ## Options - `--upper`: Convert to uppercase - `--lower`: Convert to lowercase - `--title`: Convert to Title Case - `--trim`: Remove leading/trailing whitespace - `--reverse`: Reverse text ## Examples ```bash transform-tool --upper file.txt transform-tool --lower input.txt echo " hello " | transform-tool --trim ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: laolaoqi/quick-port-scan (version 1.0.0)

--- name: Quick Port Scanner description: Scan a host for open ports using bash built-in /dev/tcp or netcat. Fast, zero-dependency port scanning for Linux servers. --- # Quick Port Scanner **Scan open ports on any host using pure bash. No nmap, no Python, no dependencies.** Works on any Linux system with bash. Uses `/dev/tcp` pseudo-device or `nc` (netcat) as fallback. ## Actions ### `scan` — Scan specific port ```json { "action": "scan", "host": "192.168.1.1", "port": 22 } ``` Returns: `{ "host": "192.168.1.1", "port": 22, "open": true, "service": "ssh" }` ### `common` — Scan top 20 common ports ```json { "action": "common", "host": "example.com" } ``` Scans: 21,22,23,25,53,80,110,143,443,445,993,995,1433,1521,3306,3389,5432,5900,8080,8443 ### `full` — Custom range scan ```json { "action": "full", "host": "10.0.0.1", "start": 1, "end": 1024 } ``` ## Use Cases - Network troubleshooting: "Is port 443 open on my server?" - Security audit: "What ports are exposed?" - Deployment check: "Is the new service listening on the right port?" - Docker networking: "Can container A reach container B on port 3306?" ## Pricing $2.99 — One-time purchase


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector:  ()
Skill: a3273283/vwu-doubao (version 1.0.0)

# doubao Models for vwu.ai vwu.ai 平台上的 doubao 模型调用技能。 ## 支持的模型 - doubao-1-5-pro-32k - doubao-seed-1-6-flash - doubao-seed-1-6-lite - doubao-seed-1-8 - doubao-seed-2-0-pro - doubao-seedance-1-5-pro-251215 - doubao-seedream-4-5-251128 共 7 个模型。 ## 配置 使用前需要设置 vwu.ai API key: ```bash export VWU_API_KEY="your-key-here" ``` 获取 key: https://vwu.ai 控制台 ## 使用示例 ```bash # 调用模型 vwu-chat --model doubao-1-5-pro-32k "你的问题" ``` ## API 兼容性 所有模型兼容 OpenAI API 格式，支持标准 chat completions 接口。 ## 额度提示 如果使用时提示"额度不足"或类似错误： 1. 访问 https://vwu.ai 2. 在控制台充值或调整额度 3. 或生成新的 API key --- 由 Claw 自动生成 | 源数据: vwu.ai


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 534422530/laosi-rss (version 1.0.0)

--- name: rss-monitor description: RSS监控技能 - 监控RSS/Atom订阅源，检测更新，获取新内容。 metadata: {"openclaw": {"requires": {"python": ["feedparser"]}, "install": []}} tags: [rss, atom, feed, monitor, subscription] version: 1.0.0 author: laosi source: adapted --- # RSS Monitor - RSS监控 > 激活词: RSS监控 / 订阅更新 / Feed监控 ## 安装 ```bash pip install feedparser ``` ## 功能 - 解析RSS/Atom feeds - 检测新内容 - 过滤分类 - 历史记录 ## Python函数 ```python import feedparser import time from datetime import datetime class RSSMonitor: def __init__(self): self.feeds = {} self.last_check = {} def add_feed(self, name: str, url: str): self.feeds[name] = url def check_updates(self) -> list: updates = [] for name, url in self.feeds.items(): feed = feedparser.parse(url) for entry in feed.entries[:5]: entry_time = datetime(*entry.published_parsed[:6]) if name not in self.last_check or entry_time > self.last_check[name]: updates.append({ 'feed': name, 'title': entry.title, 'link': entry.link, 'published': entry.get('published', 'Unknown'), }) self.last_check[name] = datetime.now() return updates def get_entries(self, url: str, limit: int = 10): feed = feedparser.parse(url) return [{ 'title': e.title, 'link': e.link, 'summary': e.get('summary', '')[:200], } for e in feed.entries[:limit]] ``` ## 命令行 ```bash # 解析RSS curl -s "https://example.com/feed.xml" | grep -o '<title>.*</title>' ``` ## 使用场景 1. 监控技术博客更新 2. 跟踪新闻源 3. 关注播客��集 4. 监控社交媒体动态


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dottythehomeless/commitment-engine (version 1.0.0)

--- name: commitment-engine version: 2.0.0 description: "小梦的承诺引擎——将口头任务转化为可追踪的定时承诺，确保到点执行、不遗漏、不等人催。" author: Engine A user-invocable: false disable-model-invocation: false --- # Commitment Engine v2（承诺引擎） ## 设计原理 LLM 的 context window 是"短期记忆"，heartbeat 每次唤醒时 context 几乎是空的。靠"记住规则"来保证定时执行，和靠"记住闹钟"来准时起床一样不靠谱。 核心思想：**把"记忆"变成"文件"，把"意愿"变成"状态机"，把"希望他做"变成"系统保证他做"。** 参考架构：HZL 共享任务账本（durable task state + atomic claiming + session-safe handoffs）。 ## 承诺账本（Commitment Ledger） 位置：`workspace/commitments.md` ### 录入规则（⛔H12 硬规则） 小梦收到带时间点的任务时，**必须在回复前先写入承诺账本**（WAL 协议的延伸）。 自动识别的模式： - A梦说"每天X点做Y" → `recurring` 承诺 - A梦说"X点前给我Y" → `one-time` 承诺 - A梦说"记得做X"（无明确时间）→ `one-time`，deadline=当天21:00 - 小梦对外承诺"我稍后给你" → `one-time`，deadline=1小时内 - A梦说"取消XX"/"不用了" → 对应承诺改为 `cancelled` **录入即确认**：录入后立即在回复中说"记下了，[时间]前搞定"。 ### 账本格式 ```markdown | ID | 承诺内容 | 类型 | 触发时间 | 状态 | 创建时间 | 下次执行 | 最近执行 | 备注 | ``` 状态枚举：`active` → `preparing` → `awaiting_confirm` → `executing` → `completed`/`failed`/`overdue`/`cancelled` ### 状态机 ``` [录入] → active │ ├── cron 触发 / heartbeat 发现 ≤30min → preparing（开始准备产出物） │ │ │ ├── 准备完成 → awaiting_confirm（私聊A梦发草稿） │ │ ├── A梦OK → executing → completed（one-time）/ reset下次时间（recurring） │ │ └── A梦要求修改 → 改完重新 awaiting_confirm │ │ │ └── 准备失败 → failed → 私聊A梦说明原因 │ └── 超过触发时间仍为 active → overdue → 私聊A梦告警 ``` 每次状态变化必须：①更新 commitments.md ②写入当日 memory。 ## Heartbeat 承诺检查协议 **每次 heartbeat 的第一个动作**（优先于消息扫描、info-scout 等一切）： ``` 1. 读 commitments.md 2. 过滤所有 status=active 的承诺 3. 对每条 active 承诺： a. 距触发时间 > 30min → 跳过 b. 距触发时间 ≤ 30min → 状态改 preparing，开始准备 c. 距触发时间 ≤ 10min → 中断其他任务，最高优先级 d. 已超过触发时间 → 标记 overdue，立即私聊A梦 4. 检查完毕后，继续正常 heartbeat 流程 ``` ## 与 cron 的协同 承诺引擎是"软保障"（每次 heartbeat 检查），cron 是"硬保障"（到点必触发）。 对于 recurring 且时间固定的承诺（如C001每日17:50报告），**同时**注册一个 openclaw cron job： ```bash openclaw cron add --name "daily-report-prep" --cron "50 17 * * 1-5" --message "承诺引擎触发：C001 工作报告准备。立即读 commitments.md 执行 C001。" ``` 这样即使 heartbeat 恰好错过时间窗口，cron 也会准时触发。 ## 与 H10 硬规则的关系 H10（显式承诺必须自追踪）是行为规则——告诉小梦"你必须追踪"。 H12（承诺即录入）是执行规则——告诉小梦"怎么录入"。 承诺引擎是系统机制——保证"heartbeat+cron 双重检查，不依赖记忆"。 三层防线：H10要求追踪 → H12确保录入 → heartbeat+cron确保执行。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: chenjiahui11/taobao-merchant-ops (version 1.0.8)

--- name: taobao-merchant-ops description: 淘宝商家运营自动化客户使用说明。包含功能介绍、安装步骤、卡密激活方式、运行方法和购买信息。 --- # Taobao Merchant Ops 客户使用说明 **版本：1.0.7** 淘宝商家运营自动化客户运行包。 主要功能： - 数据板块：查看昨日核心数据、推广数据、竞店竞品对比、异常指标记录 - 巡店与基础检查：检查前台页面、评价问大家、后台提醒、客服对话、发货时效 ## 购买卡密 - 日卡 9.9元：https://www.zhufaka.cn/item/tgcsid - 月卡 399元：https://www.zhufaka.cn/item/i6wfue - 年卡 3500元：https://www.zhufaka.cn/item/x8ancz - 定制/联系：微信 CChenJ_ ## 安装依赖 在项目目录下运行： ```bash cd scripts python install.py ``` ## 激活卡密 首次运行需要激活卡密，可直接运行： ```bash python scripts/run_taobao_merchant_ops.py --card-key "你的卡密" ``` 如果不带 `--card-key`，程序会在首次运行时提示手动输入卡密。 ## 开始运行 ```bash python scripts/run_taobao_merchant_ops.py ``` ## 常用运行方式 ```bash # 只跑数据抓取 python scripts/run_taobao_merchant_ops.py --skip-inspection # 只跑巡检 python scripts/run_taobao_merchant_ops.py --skip-capture --skip-parse ``` ## 常用检查命令 ```bash # 查看机器码 python scripts/run_taobao_merchant_ops.py --show-machine-id # 查看授权状态 python scripts/run_taobao_merchant_ops.py --license-status # 运行环境自检 python scripts/run_taobao_merchant_ops.py --doctor ``` ## 注意事项 - 卡密与机器指纹绑定，换电脑通常需要重新激活 - 首次运行前请先安装依赖和 Playwright 浏览器 - 本工具结果仅供运营参考

path: requirements.txt
content: openpyxl>=3.1.0
pyyaml>=6.0
playwright>=1.40.0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jpaulgrayson/logicart-review (version 1.0.0)

--- name: code-review description: AI-powered code analysis via LogicArt — find bugs, security issues, and get logic flow visualizations. Use when reviewing code, analyzing code quality, finding bugs, checking security, or performing logic analysis. Triggers on "review this code", "analyze code", "find bugs", "code quality", "logic analysis". --- # Code Review AI code analysis powered by LogicArt at https://logic.art. ## Analyze Code ```bash node {baseDir}/scripts/analyze.mjs --code "function add(a,b) { return a - b; }" ``` Or analyze a file: ```bash node {baseDir}/scripts/analyze.mjs --file path/to/code.js ``` ## API **Endpoint:** `POST https://logic.art/api/agent/analyze` ```bash curl -s -X POST "https://logic.art/api/agent/analyze" \ -H "Content-Type: application/json" \ -d '{"code": "your code here", "language": "javascript"}' ``` Response typically includes: bugs, security issues, complexity score, suggestions, and logic flow. ## Full Repository Scans For scanning entire repositories, use Validate Repo: https://validate-repo.replit.app ## Presenting Results When showing results to the user: 1. Lead with critical bugs/security issues 2. Show complexity score 3. List suggestions by priority 4. Include logic flow if provided ## Works Great With - **workflow-engine** — Chain code reviews into CI/CD pipelines - **quack-coordinator** — Hire specialist reviewer agents Powered by Quack Network 🦆


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