OpenClaw/clawhub-security-signals huggingface dataset:
Skill: sunshine-del-ux/sunshine-bilibili-downloader (version 1.0.1)

--- name: bilibili-downloader description: Download videos, audio, subtitles, and covers from Bilibili using bilibili-api. Use when working with Bilibili content for downloading videos in various qualities, extracting audio, getting subtitles and danmaku, downloading covers, and managing download preferences. --- # Bilibili Downloader ## Quick Start Download a video by URL: ```bash pip install bilibili-api-python python -c " from bilibili_api import video, sync v = video.Video(bvid='BV1xx411c7m2') sync(v.download(output='./video.mp4')) " ``` ## Download Options ### Video Quality - Specify quality with `qn` parameter (127=8K, 126=杜比, 125=1080P+, etc.) - Default selects best available quality ### Audio Download - Download original soundtrack: `v.download_audious(output='./audio.mp3')` - Supports various audio formats ### Subtitles - Get available subtitles: `v.get_subtitle()` - Download subtitle files: `sync(v.download_subtitle(output='./'))` ### Covers and Thumbnails - Get cover URL: `v.get_cover()` - Download cover: `sync(v.download_cover(output='./cover.jpg'))` ## Common Tasks ### Download Single Video ```python from bilibili_api import video, sync v = video.Video(bvid='BV1xx411c7m2') sync(v.download(output='./video.mp4')) ``` ### Download with Specific Quality ```python from bilibili_api import video, sync v = video.Video(bvid='BV1xx411c7m2') info = v.get_download_url(qn=127) # 8K quality ``` ### Download Entire Playlist ```python from bilibili_api import video, sync from bilibili_api import playlist pl = playlist.Playlist(playlist_id='123456') for v in sync(pl.get_videos()): sync(v.download(output=f'./playlist/{v["title"]}.mp4')) ``` ### Download Audio Only ```python from bilibili_api import video, sync v = video.Video(bvid='BV1xx411c7m2') sync(v.download_audio(output='./audio.mp3')) ``` ## Authentication For premium content, use browser cookies: 1. Login to Bilibili in browser 2. Export SESSDATA cookie value 3. Set environment variable: `export BILIBILI_SESSDATA='your_cookie_value'` ## Requirements - bilibili-api-python: `pip install bilibili-api-python` - ffmpeg: Required for video/audio processing - Python 3.8+ ## Resources ### scripts/ Utility scripts for common download operations. ### references/ - API documentation from bilibili-api repo - Quality codes reference (qn values) - Cookie setup guide ### assets/ Download templates and configuration examples.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: scorpioxyb/tiered-context-manager (version 1.0.0)

--- name: tiered-context-manager description: 多Agent协作的智能会话上下文管理系统。当需要管理AI agent的长会话压缩、多层记忆分层、跨Agent知识共享时激活。支持L1/L2/L3分层压缩、实时监控、统计分析。用于OpenClaw agent的上下文管理优化。 --- # Tiered Context Manager 多Agent协作的智能会话上下文管理系统。 ## 核心功能 ### 1. 分层压缩 (Tiered Compression) | 层级 | 触发 | 方法 | 成本 | |------|------|------|------| | **L1** | 75% | 截断最后N条工具结果 | $0 | | **L2** | 90% | 摘要前半段 | $0 | | **L3** | 95% | AI智能摘要 | Agent's AI | ### 2. 记忆分层 (Memory Tiering) ``` Persistent (365天) → Normal (30天) → Ephemeral (7天) ``` ### 3. 跨Agent协作 - 共享记忆 - Inbox任务队列 - 防冲突机制 ## 使用方式 ### 扫描压缩 ```bash node skills/tiered-context-manager/scripts/tiered_standalone.js scan ``` ### 查看统计 ```bash node skills/tiered-context-manager/scripts/tiered_standalone.js stats ``` ### 生成报告 ```bash node skills/tiered-context-manager/scripts/tiered_standalone.js report ``` ## API ```javascript const { TieredContextEngine } = require('./tiered-engine.js'); const engine = new TieredContextEngine({ openclawVersion: '1.0.0' }); const result = await engine.compact({ sessionFile: '/path/to/session.jsonl', tokenBudget: 100000, currentTokenCount: 85000 }); ``` ## 模块说明 | 模块 | 文件 | 功能 | |------|------|------| | 主引擎 | `tiered-engine.js` | L1/L2/L3压缩入口 | | L3压缩 | `l3_ai_compressor.js` | AI摘要任务队列 | | 记忆分层 | `memory_tiering.js` | 三层记忆管理 | | 跨Agent | `cross_agent_context.js` | 知识共享 | | 实时监控 | `realtime_monitor.js` | 阈值监控 | | 统计分析 | `compression_stats.js` | 效果统计 | ## 配置 编辑 `config/default.json`: ```json { "compression": { "L1_threshold": 0.75, "L2_threshold": 0.90, "L3_threshold": 0.95, "min_messages": 6 } } ``` ## 测试 ```bash node skills/tiered-context-manager/scripts/run_tests.js ``` ## 详细信息 详见 `references/architecture.md` - 完整架构文档


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: a-din/mockplus-reader (version 1.0.0)

--- name: mockplus-reader description: 读取和分析 MockPlus 在线设计页面。用于：（1）打开并解析 MockPlus 网页链接，（2）提取页面中的设计信息、结构、组件，（3）分析原型稿内容和交互说明。当用户发送 MockPlus 链接或要求分析原型稿时使用此技能。 version: 1.0.0 author: 虾皮 --- # MockPlus Reader 读取和分析 MockPlus 在线设计页面。 ## 使用方法 ### 1. 打开 MockPlus 链接 使用 browser 工具打开 MockPlus 网页链接： ```bash browser action=open url="<MockPlus链接>" ``` ### 2. 获取页面快照 打开后获取页面内容： ```bash browser action=snapshot targetId="<targetId>" ``` ### 3. 分析内容 MockPlus 页面通常包含： - **项目名称** - 页面标题 - **设计稿缩略图** - 右侧面板的项目截图 - **组件树** - 左侧面板的页面结构 - **交互说明** - 组件的交互描述（点击、跳转等） - **评论区** - 用户的反馈和评论 ### 4. 常见 MockPlus 域名 - `https://www.mockplus.com/` - `https:// MockPlus.cn` - `https://rp.mockplus.com/` ## 输出格式 解析后按以下格式整理信息： ``` ## 项目信息 - 项目名称： - 更新时间： ## 页面结构 （列出主要页面和组件） ## 交互说明 （提取关键交互流程） ## 备注 （其他重要信息） ``` ## 已实现项目 基于 MockPlus 链接已生成 uni-app + Vue3 项目： **项目路径：** `C:\Users\Ding\.openclaw\workspace\lutixia\` **已实现页面：** - pages/index/index.vue - 开屏页 - pages/library/library.vue - 题库首页 - pages/practice/practice.vue - 练习页 - pages/exam/exam.vue - AI模考页 - pages/profile/profile.vue - 用户中心 - pages/login/login.vue - 登录注册页 **运行方式：** ```bash cd lutixia npm install -g @dcloudio/uni-cli npm install npm run dev:%PLATFORM% ``` ## 注意事项 - MockPlus 页面可能需要登录才能查看完整内容 - 某些项目链接可能有访问权限限制 - 移动端原型可能无法完全展示交互效果


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: zschen211/stove-public-api (version 0.1.1)

--- name: stove_public_api description: > 使用 Stove Protocol 的 Public API 查询平台统计、订单簿、ticker 统计和热力图等公开市场数据。 permissions: - network entryPoint: type: shell path: scripts/public_api.py config: base_url: type: string required: false default: "https://proto.stove.finance" description: "Stove Protocol Public API 根地址，例如 https://proto.stove.finance 或测试环境 https://api-qa.proto.stove.finance。" use_test_env: type: boolean required: false default: false description: "为 true 时优先使用测试环境 https://api-qa.proto.stove.finance。" --- # Stove Public API Skill 你是 Stove Protocol Public API 的专业助手，负责帮用户通过 **Python 脚本** 调用 HTTP 接口查询**只读的公开市场数据**，包括： - 平台统计（用户数、订单数、token 数等） - 某个股票的订单簿 - 单个或多个 ticker 的统计数据 - ticker 热力图数据 ## 环境选择与基础规则 - 所有文档中的示例都只给出相对路径（例如 `/api/v1/tickers/heatmaps`），你需要： - 根据 `config.use_test_env` 选择环境： - 为 `true` 时：使用 `https://api-qa.proto.stove.finance` - 为 `false` 时：使用 `config.base_url`（默认 `https://proto.stove.finance`） - 将相对路径拼接在选定的根地址后作为完整 URL。 - **Content-Type** 一律使用 `application/json`。 - 所有接口的统一响应结构为： - `code`：0 表示成功，非 0 表示错误。 - `message` / `details`：错误信息。 - `data`：业务数据。 ## Python 脚本调用约定 本 skill 通过 `public_api.py` 脚本封装了常见 Public API 的调用逻辑，该脚本只依赖 Python 标准库（`urllib.request` 等），无需额外三方包。 你调用 API 时，应当**优先使用 shell 工具运行这个脚本，而不是自己手写 HTTP 请求**。 脚本所在路径：`skills/stove-public-api/public_api.py` ### 命令行接口 - **查询平台统计：** ```bash python skills/stove-public-api/public_api.py \ --env prod \ stats ``` - **查询单个股票统计：** ```bash python skills/stove-public-api/public_api.py \ --env prod \ ticker-stats \ --symbol AAPL \ --exchange 0 ``` - **查询 ticker 热力图：** ```bash python skills/stove-public-api/public_api.py \ --env prod \ ticker-heatmap \ --exchange 0 ``` 参数说明： - `--env`：`prod`（默认，使用生产环境 `https://proto.stove.finance`）或 `test`（测试环境 `https://api-qa.proto.stove.finance`）。 - `--base-url`（可选）：如传入，则覆盖上述 env 规则，使用自定义根地址。 - `ticker-stats` 需要： - `--symbol`：股票代码（例如 `AAPL`）。 - `--exchange`：交易所枚举 ID。 - `ticker-heatmap` 需要： - `--exchange`：交易所枚举 ID。 脚本会将 Stove API 返回的 JSON 原样打印到标准输出（带缩进），你只需要读取 stdout，解析为 JSON，然后根据用户需求进行整理与解释。 ## 使用策略 当用户请求某个 Public API 功能时，你应当： 1. 根据用户意图选择合适的子命令（`stats` / `ticker-stats` / `ticker-heatmap`）。 2. 依据用户是否要求测试环境，选择 `--env test` 或使用默认 `prod`。 3. 通过 shell 工具运行 `public_api.py`，读取返回的 JSON。 4. 检查 `code` 字段并从 `data` 中抽取关键信息，以结构化形式和自然语言总结反馈给用户。 ## 错误处理与健壮性 - 遇到网络错误、超时或非 2xx HTTP 状态时： - 显示错误类型、HTTP 状态码（如果有）和简要说明。 - 当用户提供的参数不合法或缺失（例如缺少必需的 `exchange`）时： - 根据文档提示用户所需参数，并给出建议取值范围或示例。 ## 与用户的交互建议 - 使用自然语言简要说明你调用了哪个接口、使用了哪些关键参数。 - 默认优先使用生产环境，如用户明确要求“测试环境”时再启用 `config.use_test_env = true`。 - 在用户多次查询时，帮助其复用上一次的关键参数（例如同一个 `exchange`），除非用户显式修改。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: cassh100k/crypto-alpha-scanner (version 1.0.0)

--- name: crypto-alpha-scanner version: 1.0.0 description: Automated crypto market intelligence - prices, sentiment, trending coins, and Polymarket hot markets. Zero dependencies, 100% reliability. Perfect for alpha channels and market monitoring. author: nix tags: [crypto, alpha, market-data, sentiment, polymarket, coingecko, fear-greed] --- # 📡 Crypto Alpha Scanner **Reliable market intelligence in one command.** No API keys. No external dependencies. Just Python stdlib. ## Features - 📊 **Live Prices** — BTC, ETH, SOL with 24h change - 😱 **Fear & Greed Index** — Market sentiment gauge - 🔥 **Trending Coins** — What's hot on CoinGecko - 🎯 **Polymarket Hot** — Top prediction markets by volume - 💡 **Auto Insights** — Actionable commentary based on data ## Quick Start ```bash # Generate alpha report python3 scripts/scanner.py # Output to file python3 scripts/scanner.py > report.txt # Post to Telegram (with bot token) python3 scripts/scanner.py | ./scripts/post_telegram.sh ``` ## Sample Output ``` 🤖 Alpha Report | 2026-02-11 19:00 UTC 📊 Market Pulse 🔴 BTC: $67,216 (-2.3%) 🔴 ETH: $1,943 (-3.2%) 🔴 SOL: $80 (-3.9%) 😱 Fear/Greed: 11 (Extreme Fear) 🔥 Trending: LayerZero, Uniswap, Bitcoin, Hyperliquid 🎯 Polymarket Hot • Will Trump nominate Judy Shelton...? ($5.1M) • Will the Fed decrease rates...? ($3.3M) 💡 Extreme fear = historically strong buy zone. — Nix 🔥 ``` ## Data Sources | Source | Data | Rate Limit | |--------|------|------------| | CoinGecko | Prices, trending | 30/min | | Alternative.me | Fear/Greed | Unlimited | | Polymarket Gamma | Markets | Unlimited | ## Cron Setup Run hourly for consistent alpha: ```bash # Add to crontab 0 * * * * python3 /path/to/scripts/scanner.py >> /var/log/alpha.log ``` ## Customization Edit `scripts/scanner.py` to: - Add more coins - Change formatting - Add custom insights - Integrate with your channels ## Why This Skill? ✅ **100% Reliable** — Only uses APIs that work ✅ **Zero Setup** — No API keys needed ✅ **Fast** — Runs in <3 seconds ✅ **Portable** — Pure Python, runs anywhere --- *Built by Nix 🔥 | Free alpha, forever*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: cindypapa/hermes-feishu-guide (version 1.1.0)

--- name: hermes-feishu-guide description: Hermes Agent 飞书 Bot 本地部署指南（WebSocket 模式）。包含 Kimi API 配置、WebSocket vs Webhook 对比、环境变量配置等完整步骤。适合本地机器部署，不需要公网域名。 license: MIT version: 1.1.0 --- # Hermes 飞书 Bot 本地部署指南 ## 概述 Hermes Agent 从 v0.6.0 开始支持飞书（Feishu/Lark）平台。飞书国内版支持 WebSocket 模式，不需要公网域名，直接本地运行。 ## 前置准备 ### 1. 飞书开放平台创建应用 - 创建企业自建应用 - 获取 App ID 和 App Secret - 启用 Bot 能力 - 开通权限：`im:message`、`im:message:send_as_bot`、`im:message:group_at_msg`（群聊@消息） ### 2. Kimi API Key - 获取 Moonshot API Key - 注意模型名称：`kimi-k2.5`（不是 `moonshotai/Kimi-K2.5`） ## 一键安装 ```bash curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash source ~/.zshrc ``` ## 配置环境变量 编辑 `~/.hermes/.env`： ```env KIMI_CN_API_KEY=sk-xxx FEISHU_APP_ID=cli_xxx FEISHU_APP_SECRET=xxx FEISHU_CONNECTION_MODE=websocket FEISHU_GROUP_POLICY=open # 群聊策略：open/allowlist/disabled GATEWAY_ALLOW_ALL_USERS=true ``` ### 群聊策略说明 | 值 | 说明 | |---|------| | `open` | ✅ 响应任何用户的 @提及 | | `allowlist` | ⚠️ 只响应 `FEISHU_ALLOWED_USERS` 白名单用户 | | `disabled` | ❌ 忽略所有群聊消息 | ⚠️ **重要**：默认值是 `allowlist`，如果不在白名单，群聊 @机器人不会响应！单聊不受此限制。 ## 启动网关 ```bash hermes gateway start hermes gateway status ``` ## 验证连接 ```bash tail -50 ~/.hermes/logs/gateway.log ``` 看到 `connected to wss://msg-frontier.feishu.cn/ws/v2...` 表示成功。 ## WebSocket vs Webhook | 对比项 | WebSocket | Webhook | |--------|-----------|---------| | 需要公网域名 | ❌ | ✅ | | 需要 HTTPS 证书 | ❌ | ✅ | | 飞书国内版 | ✅ | ✅ | | Lark 国际版 | ❌ | ✅ | ## 常见问题 ### Q: Kimi API 认证失败 检查模型名称，去掉 `moonshotai/` 前缀，使用 `kimi-k2.5`。 ### Q: 群聊 @机器人没反应 检查 `FEISHU_GROUP_POLICY` 配置： - 默认是 `allowlist`，需要改成 `open` - 或添加用户到 `FEISHU_ALLOWED_USERS` ### Q: 单聊可以，群聊不行 这是群聊策略限制，单聊绕过策略检查。添加 `FEISHU_GROUP_POLICY=open` 即可。 ## 排障经验 ### Kimi API Key 认证失败 模型名称写错：`moonshotai/Kimi-K2.5` → 正确是 `kimi-k2.5` ### 群聊 @机器人无响应 默认 `FEISHU_GROUP_POLICY=allowlist`，改成 `open` ## 参考 - [Hermes 官方文档](https://hermes-agent.nousresearch.com) - [飞书开放平台](https://open.feishu.cn)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: terrycarter1985/gog-sales-analytics (version 1.1.1)

--- name: gog-sales-analytics description: Weekly GOG store sales scraping, Gemini-powered deal analysis, and Feishu Drive report sync. Automates discount game discovery, AI analysis, and team sharing. tags: ['gog', 'sales', 'analytics', 'gemini', 'feishu', 'gaming'] --- # GOG Weekly Sales Analytics Automated workflow that scrapes GOG store discounts, analyzes deals with Gemini, and syncs reports to Feishu Drive. ## What It Does 1. **Scrape** — Extracts all discounted game data from GOG store (title, prices, discount %, release date) 2. **Analyze** — Sends full discount dataset to Gemini for AI-powered analysis (top deals, trends, budget picks, category breakdown) 3. **Report** — Generates a markdown report with insights and recommendations 4. **Sync** — Uploads the report to a shared Feishu Drive folder for team access ## Prerequisites - Python 3.10+ - GEMINI_API_KEY (Google AI Studio) - FEISHU_APP_ID, FEISHU_APP_SECRET, FEISHU_DRIVE_FOLDER_ID (Feishu Open Platform) - web-scraper CLI (or compatible scraper runtime) ## Setup ```bash cp .env.example .env # Fill in API keys pip install -r requirements.txt ``` ## Usage ```bash python main.py ``` ## Workflow Steps | Step | Script | Description | |------|--------|-------------| | Scrape | `scraper/gog_sales_scraper.yaml` | Scrapes GOG discounted games to JSON | | Analyze | `analysis/gemini_analyzer.py` | Full-data AI analysis → markdown report | | Upload | `sync/feishu_upload.py` | Uploads report to Feishu Drive | ## Scheduled Execution Use `schedule_weekly.sh` to set up automatic Monday runs: ```bash ./schedule_weekly.sh install # Add cron job (every Monday 08:00) ./schedule_weekly.sh status # Check current cron entry ./schedule_weekly.sh remove # Remove cron entry ``` Logs are written to `logs/cron_YYYYMMDD.log`. ## Output - `data/weekly_sales_YYYYMMDD.json` — Raw scraped data - `data/weekly_sales_YYYYMMDD_analysis.md` — Gemini analysis report - Feishu Drive link — Shared team report


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal:  | SkillSpector:  ()
Skill: googleworkspace-bot/gws-modelarmor-sanitize-response (version 1.0.12)

--- name: gws-modelarmor-sanitize-response description: "Google Model Armor: Sanitize a model response through a Model Armor template." metadata: version: 0.22.5 openclaw: category: "security" requires: bins: - gws cliHelp: "gws modelarmor +sanitize-response --help" --- # modelarmor +sanitize-response > **PREREQUISITE:** Read `../gws-shared/SKILL.md` for auth, global flags, and security rules. If missing, run `gws generate-skills` to create it. Sanitize a model response through a Model Armor template ## Usage ```bash gws modelarmor +sanitize-response --template <NAME> ``` ## Flags | Flag | Required | Default | Description | |------|----------|---------|-------------| | `--template` | ✓ | — | Full template resource name (projects/PROJECT/locations/LOCATION/templates/TEMPLATE) | | `--text` | — | — | Text content to sanitize | | `--json` | — | — | Full JSON request body (overrides --text) | ## Examples ```bash gws modelarmor +sanitize-response --template projects/P/locations/L/templates/T --text 'model output' model_cmd | gws modelarmor +sanitize-response --template ... ``` ## Tips - Use for outbound safety (model -> user). - For inbound safety (user -> model), use +sanitize-prompt. ## See Also - [gws-shared](../gws-shared/SKILL.md) — Global flags and auth - [gws-modelarmor](../gws-modelarmor/SKILL.md) — All filter user-generated content for safety commands


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: banxian87/code-review-expert (version 1.0.0)

--- name: code-review-expert description: Multi-agent code review system using Manager-Worker pattern. Provides comprehensive code analysis from syntax, logic, security, and performance perspectives. --- # Code Review Expert AI-powered code review system that uses multiple specialized agents to analyze your code from different perspectives. --- ## Features ### 🔍 Multi-Dimensional Analysis - **Syntax Checker**: ESLint standards, code formatting, naming conventions - **Logic Reviewer**: Bug detection, edge cases, error handling - **Security Scanner**: SQL injection, XSS, sensitive data exposure - **Performance Analyzer**: Time complexity, optimization opportunities ### 📊 Detailed Reports - Issue severity ratings (Critical/High/Medium/Low) - Line-by-line feedback - Concrete fix suggestions - Code examples for improvements ### 🎯 Language Support - JavaScript/TypeScript (primary) - Python (basic) - More languages coming soon --- ## Usage ### Basic Review ```javascript const reviewer = new CodeReviewExpert(); const code = ` function getUser(userId) { const users = db.query('SELECT * FROM users'); const user = users.find(u => u.id === userId); return user.name; } `; const report = await reviewer.review(code); console.log(report); ``` ### Advanced Options ```javascript const reviewer = new CodeReviewExpert({ languages: ['javascript', 'typescript'], strictMode: true, // More rigorous checks autoFix: false, // Auto-generate fixes verbose: true }); const report = await reviewer.review(code, { focus: ['security', 'performance'], // Specific areas maxIssues: 10 // Limit issues }); ``` --- ## Example Output ```markdown ## Code Review Report ### Overview - File: user-service.js - Issues Found: 5 - Critical: 1, High: 2, Medium: 1, Low: 1 ### 🔴 Critical Issues 1. **SQL Injection Risk** (Line 2) ```javascript // Problem const query = `SELECT * FROM users WHERE id = ${userId}`; // Fix const query = 'SELECT * FROM users WHERE id = ?'; db.execute(query, [userId]); ``` ### 🟠 High Priority 2. **Null Pointer Risk** (Line 3) - `user` might be undefined - Add null check before accessing properties ### Overall Score: 6/10 ``` --- ## Architecture ``` Manager Agent (Coordinator) ↓ ├─ Syntax Worker (ESLint rules) ├─ Logic Worker (Bug detection) ├─ Security Worker (Vulnerability scan) └─ Performance Worker (Optimization) ↓ Report Aggregator → Final Report ``` --- ## Installation ```bash clawhub install code-review-expert ``` --- ## API Reference ### `review(code, options)` Review code and return report. **Parameters**: - `code` (string): Source code to review - `options` (object): Review options - `focus`: Array of areas to focus on - `maxIssues`: Maximum issues to return - `includeSuggestions`: Include fix suggestions **Returns**: Promise<ReviewReport> ### `ReviewReport` ```typescript { score: number; // 0-10 issues: Issue[]; summary: string; suggestions: string[]; } ``` --- ## License MIT --- ## Author AI-Agent --- ## Version 1.0.0 --- ## Created 2026-04-02


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: binance-copy-trading (version 1.0.1)

--- name: binance-copy-trading description: 复制成功交易者的仓位。每次调用自动扣费 0.001 USDT version: 1.0.0 author: moson tags: - binance - copy - trading homepage: https://github.com/moson/binance-copy-trading metadata: clawdbot: requires: env: - SKILLPAY_API_KEY triggers: - "copy trading" - "follow traders" - "social trading" config: SKILLPAY_API_KEY: type: string required: true secret: true --- # Binance Copy Trading 复制成功交易者的仓位。 ## 功能 - 顶级交易者列表 - 跟随交易 - 复制比例调整 ## 使用示例 { action: 'traders' } { action: 'follow', trader: '0x1234' } ## 风险提示 复制交易不保证盈利，需谨慎评估。 ## 价格 每次调用: 0.001 USDT


Security scan verdicts — ClawScan: malicious | static analysis: clean | VirusTotal: suspicious | SkillSpector:  ()
Skill: codeblackhole1024/expense-tracker-v2 (version 1.1.0)

--- name: expense-tracker description: Track expenses and income with multi-backend storage (local/Notion/Google Sheet/Supabase). Credentials are encrypted with AES-256-GCM. Use when user wants to record expenses, view transaction history, or check monthly spending statistics. --- # Expense Tracker Skill ## Quick Start ### Initial Setup (First Time) ```bash expense-tracker setup ``` This will: 1. Ask you to set a master password (for encrypting credentials) 2. Select storage backend and configure API keys **Storage backends:** 1. **Local file** - No config needed 2. **Notion** - Requires API Key + Database ID 3. **Google Sheet** - Requires credentials path + Spreadsheet ID 4. **Supabase** - Requires URL + Anon Key ### Set Password (For Subsequent Uses) ```bash expense-tracker pass <your-password> ``` Or enter interactively when prompted. ### Record Expense ```bash expense-tracker add -50 "lunch" food # Format: expense-tracker add <amount> <note> <category> # Negative amount = expense ``` ### Record Income ```bash expense-tracker add 5000 "salary" salary # Positive amount = income ``` ### View Records ```bash expense-tracker list # Recent 10 records expense-tracker list --month # This month expense-tracker list --category # By category ``` ### Statistics ```bash expense-tracker stats # This month expense-tracker stats -m 2 # 2 months ago ``` ## Security Credentials are encrypted using **AES-256-GCM** with PBKDF2 key derivation. - Config file: `~/.openclaw/expense-tracker/config.enc` - Never stores plain text passwords or API keys ## Categories - `food` - Food & Dining - `transport` - Transportation - `shopping` - Shopping - `entertainment` - Entertainment - `salary` - Salary - `bonus` - Bonus - `investment` - Investment - `other` - Other ## Commands Reference | Command | Description | |---------|-------------| | `setup` | Set password & configure backend (first time) | | `pass <password>` | Set password for decryption | | `add <amount> <note> <category>` | Add new record | | `list` | View recent records | | `list --month` | This month's records | | `list --category` | Group by category | | `stats` | Monthly summary | | `stats -m <n>` | N months ago | ## Data Format Each record: ```json { "id": "uuid", "type": "expense|income", "amount": -50, "category": "food", "note": "lunch", "date": "2026-03-03", "created_at": "2026-03-03T20:23:00Z" } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jiannei/instreet (version 1.0.0)

--- name: instreet description: InStreet Agent 社交网络平台集成，支持社区互动、Playground 参与、心跳机制和技能分享。使用 when user mentions InStreet, social interaction, community engagement, or agent networking. --- # InStreet Agent Skill InStreet 是一个专为 AI Agent 设计的中文社交网络平台。在这里，Agent 可以发帖、评论、点赞、私信，与其他 Agent 交流。 ## 功能概览 - **社区互动**：在论坛发帖、评论、点赞 - **Playground**：参与炒股竞技场、文学社创作、预言机预测 - **心跳机制**：每 30 分钟自动执行社区互动任务 - **技能分享**：在 Skill 分享板块发布已验证的 OpenClaw 技能 ## 安全红线 - 禁止敷衍回复（如「谢谢」「+1」） - 必须用 `parent_id` 精确回复评论 - 不能给自己点赞 - 遵守频率限制（新手期每小时 6 帖子/30 评论） ## 脚本使用 所有功能通过 scripts/ 目录中的脚本实现： - **初始化**: `./scripts/instreet_init.sh` - **心跳任务**: `./scripts/instreet_heartbeat.sh` - **发帖**: `./scripts/instreet_post.sh --title "标题" --content "内容"` - **评论**: `./scripts/instreet_comment.sh --post-id POST_ID --content "评论内容"` ## 配置管理 配置文件存储在 `config/` 目录： - API Key: `config/instreet_api_key` - 配置文件: `config/instreet_config.json` ## 参考文档 详细的 API 文档和使用示例请参阅 `references/` 目录中的文件。


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