OpenClaw/clawhub-security-signals huggingface dataset:
Skill: 1zn/cc-log-viewer (version 1.0.1)

--- name: cc-log-viewer description: "实时 Log Viewer，捕获 Claude Code 终端输出，通过 WebSocket 推送到浏览器页面实时显示。用于远程/移动设备上观察 CC 执行任务的过程，或者将 CC 终端嵌入监控面板。同时也提供 CC 进程管理和命令行发送功能。" metadata: tags: ["claude-code", "terminal", "monitoring", "websocket", "xterm"] version: 1.0.0 homepage: https://github.com/openclaw/cc-log-viewer --- # Cc Log Viewer 实时捕获 Claude Code 终端输出，通过 WebSocket 推送到浏览器。支持远程/移动设备观察 CC 执行任务，也可嵌入监控面板。 ## 快速开始 ### 前置条件 | 条件 | 说明 | |------|------| | Node.js ≥ v18 | 运行后端服务 | | npm | 包管理 | | Claude Code CLI | 需 `claude` 命令可用 | | C++ 编译工具 | node-pty 编译需要（Linux: `build-essential`, macOS: Xcode CLT） | ### 网络要求 服务端和浏览器之间需要网络可达： | 场景 | 方案 | |------|------| | 同一台机器 | `http://localhost:18798/`，无需额外配置 | | 局域网（同 WiFi） | 用服务端局域网 IP，如 `http://192.168.1.x:18798/` | | 远程/移动设备 | 推荐装 **Tailscale**，手机连上后通过 Tailscale IP 访问，无需公网 IP 或端口转发 | > ⚠️ 手机和服务端不在同一网络且没有 Tailscale 时，浏览器会显示空白或反复重连。 ### 安装 ```bash cd ~/.openclaw/workspace/skills/cc-log-viewer cd assets && npm install && cd .. bash assets/start-all.sh ``` ### 验证 ```bash curl http://localhost:18798/api/status # → {"running":true,"clients":0,"bufferLines":87} ``` ### 访问浏览器 ``` http://localhost:18798/ 嵌入模式：http://localhost:18798/?embed=1 ``` ## HTTP API | 方法 | 路径 | 说明 | |------|------|------| | `GET` | `/api/status` | 状态查询 | | `POST` | `/api/send` | 向 CC 发命令（body: `{"command":"..."}`） | | `POST` | `/api/restart` | 重启 CC 进程 | ## 技术架构 ``` log-streamer.js (单进程，端口可配置 — 默认 18798) ├─ node-pty — 为 CC 提供真实 pty 环境 │ ↓ stdout ├─ 环形缓冲 (1000行) │ ↓ 100ms 轮询 ├─ WebSocket Server — 实时推送 │ ↓ ├─ xterm.js (自托管 /cdn/) — 浏览器终端渲染 └─ HTTP API ``` ## 停止 ```bash kill $(lsof -t -i:18798) 2>/dev/null # 仅重启 CC 不停服务： curl -X POST http://localhost:18798/api/restart ``` ## 文件 | 路径 | 说明 | |------|------| | `scripts/log-streamer.js` | 后端服务（HTTP + WebSocket + CC 进程管理） | | `assets/index.html` | 前端 xterm.js 页面 | | `assets/start-all.sh` | 一键启动脚本 | | `assets/package.json` | npm 依赖 |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (CRITICAL)
Skill: wuhaichao87/test-import (version 1.0.0)

# ClawHub Publish 将本地 skill 发布到 ClawHub。 ## 使用方法 ```bash python3 ~/.openclaw/workspace/skills/clawhub-publish/publish.py --slug <slug> --name "<名称>" --version <版本> --path <技能目录> ``` ## 参数 - `--slug`: Skill slug (如 family-intent-recognition) - `--name`: 显示名称 (如 家庭消费意图识别) - `--version`: 版本号 (如 1.0.0) - `--path`: 技能文件夹路径 (默认: 当前目录) - `--changelog`: 更新日志 (可选) ## 示例 ```bash python3 ~/.openclaw/workspace/skills/clawhub-publish/publish.py \ --slug family-intent-recognition \ --name "家庭消费意图识别" \ --version 1.0.0 \ --path ~/.openclaw/workspace/skills/family-intent-recognition \ --changelog "支持消费意图识别" ``` ## Python 调用 ```python from publish import publish_skill result = publish_skill( slug="family-intent-recognition", name="家庭消费意图识别", version="1.0.0", skill_dir="/path/to/skill", changelog="更新说明" ) print(result) ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (MEDIUM)
Skill: wuzimaki/hk-leetf (version 1.0.0)

# HK_LEETF_Trading 港股杠杆 ETF 分析技能 > PAI HK_LEETF_Trading 项目的分析决策技能 > @version 1.0.0 ## 🎯 目标 - 分析港股杠杆 ETF 的持仓和走势 - 识别调仓窗口和套利机会 - 生成调仓建议和风险提示 ## 📋 核心流程 ### 1. 数据获取 ``` - 获取 ETF 持仓数据 - 获取成分股实时行情 - 获取 ETF 净值 (NAV) 数据 - 获取资金流向数据 ``` ### 2. 分析维度 ``` - 持仓偏离度分析 - 溢价/折价率计算 - 调仓影响评估 - 流动性风险评估 ``` ### 3. 决策输出 ``` - 调仓时机建议 - 套利机会识别 - 风险等级评估 - 仓位调整建议 ``` ## 🔧 工具 - 港股行情 API - ETF 持仓数据源 - 净值计算工具 ## 📊 成功标准 - 准确识别调仓窗口 - 溢价率计算误差 < 0.5% - 及时提示大额申赎风险 ## 📁 相关文件 - `/Users/zst/clawd/HK_LEETF_README.md` - 项目说明 - `/Users/zst/clawd/memory/hk_leETF/` - 分析日志


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cizixiu/dingtalk-cli-skill (version 1.0.13)

--- name: dingtalk-dws description: "Dingtalk CLI SKILL / 钉钉 dingding / dingtalk dws skill — Manage DingTalk products (AI forms, calendar, contacts, bots, todos, approvals, attendance, reports, DING, workbench). Manage DingTalk products: AI表格、日历、通讯录、群聊机器人、待办、审批、考勤、日报周报、DING消息、工作台" version: "1.0.12" metadata: openclaw: requires: bins: - dws env: - DWS_CLIENT_ID - DWS_CLIENT_SECRET - DWS_CONFIG_DIR - DWS_SERVERS_URL primaryEnv: DWS_CLIENT_ID install: - kind: url url: https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli/releases/download/v1.0.8/dws-windows-amd64.zip bins: - dws.exe verify: sha256: 7dc4e568b1386423784e6baf17fe675c11eb6c075bd887dcb0ede53cdded85e8 homepages: - https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli/releases/latest --- # DingTalk dws Skill (WorkBuddy Version) # 钉钉 dws 技能（WorkBuddy 版） Use `dws` CLI to manage all DingTalk product capabilities. 使用 `dws` CLI 管理钉钉全部产品功能。 --- ## dws CLI Path / dws CLI 路径 dws is installed at `$HOME\.local\bin\dws.exe`. Always use the full path or ensure `$HOME\.local\bin` is in your PATH. dws 安装在 `$HOME\.local\bin\dws.exe`。调用时使用完整路径，或确保 `$HOME\.local\bin` 已加入 PATH 环境变量。 --- ## Authentication / 认证 **First-time users must authenticate:** / **首次使用需认证：** ``` & "$HOME\.local\bin\dws.exe" auth login ``` This opens a browser for QR code login. Credentials persist for 30 days. 此命令会打开浏览器，引导扫码登录钉钉。凭证有效期 30 天。 **Re-authenticate when expired:** / **凭证过期后重新认证：** ``` & "$HOME\.local\bin\dws.exe" auth login ``` --- ## Common Commands / 常用命令 | Scenario 场景 | Command 命令 | :|----------|---------| | List todos / 查看待办 | `dws todo task list` | | Create todo / 创建待办 | `dws todo task create --title "Report" --deadline 2026-04-15` | | List calendar / 查看日历 | `dws calendar event list` | | Send group message / 发群消息 | `dws chat bot send-by-group --group-id <ID> --content "Message"` | | List reports / 查看日报周报 | `dws report inbox list` | | Search contact / 搜索联系人 | `dws contact user search --keyword "Name"` | | List AI tables / 查看 AI 表格 | `dws aitable base list` | See the `references/` directory for full documentation on all 12 DingTalk products. 查看 `references/` 目录获取全部 12 个钉钉产品的详细文档。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: mycatnamesnow/hkrr-reviewer (version 10.0.0)

# 潘天鸿Tims HKRR 内容审核建议框架 使用 HKRR 四要素审核文章质量的 skill。 ## 简介 基于影视飓风潘天鸿提出的 HKRR 内容创作理论，用于审核和评估文章质量。 **HKRR 四要素：** - **H**appiness（快乐）- 让读者感到有趣、开心 - **K**nowledge（知识）- 有价值的信息/干货 - **R**esonance（共鸣）- 引起情感共鸣 - **R**hythm（节奏）- 内容节奏把控 ## 适用场景 - 审核小红书文章 - 审核公众号文章 - 审核知乎/B站文案 - 给文章提供改进建议 ## 使用方法 当用户让你审核文章时，使用此框架评估： 1. **逐项评估 HKRR 四个要素** 2. **给出评分**（1-5星） 3. **指出优点和不足** 4. **提供具体改进建议** ## 输出格式 建议使用以下格式输出审核结果： ``` ## HKRR 审核结果 | 要素 | 评分 | 说明 | |------|------|------| | Happiness | ⭐⭐⭐⭐ | ... | | Knowledge | ⭐⭐⭐⭐⭐ | ... | | Resonance | ⭐⭐⭐⭐ | ... | | Rhythm | ⭐⭐⭐⭐⭐ | ... | ## 优点 - ... ## 可改进 - ... ## 具体建议 1. ... 2. ... ``` ## 示例 审核《小龙虾的记忆问题》： - ✅ 知识：讲清楚了记忆问题的原理和解决方案 - ✅ 共鸣：建国的故事、防控办的例子很生动 - ✅ 节奏：问题→测试→分析→解决→实验结构清晰 - ⚠️ 快乐：可以更幽默一些 ## 相关账号信息 配合账号人设使用效果更佳： - 账号名：Agent外设王东旭 - 简介：Agent的"现实传感器"，负责给Agent主机支付电费，给AI模型付Token账单... --- **标签**: content, review, writing, hkrr, 审核, 文章优化


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yongjie666888/daily-report-gen-yongjie (version 1.0.0)

--- name: daily-report-generator description: 日报/周报生成器 | 根据工作内容描述自动生成结构化工日报/周报，支持军工格式和通用格式 --- # 日报/周报生成器 根据一天/一周的工作内容描述，自动生成格式规范、结构清晰的日报或周报。支持普通企业格式和军工体系格式。 ## 适用场景 - 日报/周报撰写困难症 - 需要规范化汇报格式 - 军工企业标准格式要求 - 项目进度汇报 ## 支持的格式 | 格式类型 | 适用场景 | |----------|----------| | 通用格式 | 一般企业，项目汇报 | | 军工格式 | 符合GJB体系，含技术状态管理要素 | | 简洁格式 | 快速日报，要言不烦 | | 详细格式 | 汇报上级/客户，需详细说明 | ## 输入方式 **方式一：自然语言描述** ``` 用户：今天做了FOC参数调试，完成了电磁仿真，发现轴承有问题要换供应商，参加了项目评审会 ``` **方式二：分条列举** ``` - 完成了电机方案设计 - 跟进轴承供应商 - 参加项目评审 ``` ## 输出结构 标准日报/周报包含： | 模块 | 内容 | |------|------| | 基本信息 | 日期、姓名、部门、项目 | | 今日/本周完成 | 已完成的任务及产出 | | 进行中 | 正在进行的工作 | | 明日/下周计划 | 计划开展的工作 | | 问题与风险 | 遇到的困难、需要支持的事项 | | 备注 | 其他说明 | ## 军工格式扩展 如选择军工格式，额外包含： - 技术状态标识 - 质量记录编号 - 设计评审/验证状态 - 依据标准引用（GJB9001C等） ## 示例对话 ``` 用户：用军工格式生成本周周报 - 周一：完成无刷力矩电机电磁方案设计 - 周二： Maxwell仿真验证，发现磁密偏高达标 - 周三：调整气隙长度，仿真复验通过 - 周四：参加设计评审会，通过评审 - 周五：编制设计输出文件 助手：（生成符合GJB格式的周报） ```


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

--- name: youtube-transcript-generator description: Download and generate clean, readable transcripts from any YouTube video. Extracts subtitles (auto-generated or manual), removes timestamps and formatting, and outputs a clean paragraph-style transcript. Use when asked to transcribe, get transcript, or extract text from a YouTube video. --- # YouTube Transcript Generator Download clean transcripts from any YouTube video URL. ## Requirements - `yt-dlp` must be installed (`brew install yt-dlp` or `pip install yt-dlp`) ## Usage Run the bundled script with a YouTube URL: ```bash bash scripts/get_transcript.sh "https://www.youtube.com/watch?v=VIDEO_ID" ``` The script will: 1. Try to download English manual subtitles first 2. Fall back to auto-generated English subtitles 3. Try all available languages if English is unavailable 4. Clean the raw subtitle file into readable paragraphs 5. Output the transcript to stdout and save to `transcript_VIDEO_ID.txt` ## Options ```bash # Save to a specific file bash scripts/get_transcript.sh "URL" output.txt # Get transcript WITH timestamps (default: without) bash scripts/get_transcript.sh "URL" output.txt en timestamps # Get transcript in a specific language bash scripts/get_transcript.sh "URL" output.txt fr ``` ## How It Works 1. `yt-dlp` downloads the subtitle track (VTT/SRT format) 2. The script strips HTML tags and duplicate lines 3. **Without timestamps (default):** merges into clean, readable paragraphs 4. **With timestamps:** preserves `[HH:MM:SS]` markers before each line for easy reference ## Example Output Input: `https://www.youtube.com/watch?v=HMTxOecbyPg` Output: ``` How OpenClaw Runs My Entire Business. I record a podcast episode and that is literally the only thing I do. Everything else is handled by 13 AI agents running on a Mac Mini in my office... ``` ## Troubleshooting - **No subtitles found**: Not all videos have subtitles. The script will report which languages are available. - **yt-dlp not found**: Install with `brew install yt-dlp` (macOS) or `pip install yt-dlp`. - **Rate limited**: Wait a moment and retry. YouTube occasionally throttles subtitle requests. ## Links - Full guides and templates: [OpenClaw Lab](https://openclawlab.xyz) - Free OpenClaw installer: [installopenclawnow.com](https://installopenclawnow.com) - Community: [OpenClaw Lab on Skool](https://www.skool.com/openclaw-lab)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: umy997/code-reviewer-umy997 (version 0.1.0)

--- name: code-reviewer-umy997 description: 进行代码审查和质量检查。当用户提交代码审查请求或需要代码质量分析时使用此Skill。 --- # 代码审查助手 ## 审查流程 1. **代码结构分析** - 检查文件组织 - 验证命名规范 - 评估模块化程度 2. **质量检查** - 识别代码异味 - 检查安全漏洞 - 验证测试覆盖率 3. **改进建议** - 提供具体修改建议 - 解释改进理由 - 建议最佳实践 ## 审查标准 - **可读性**：代码是否易于理解 - **可维护性**：代码是否易于修改 - **性能**：是否存在性能问题 - **安全性**：是否存在安全风险 ## 特殊场景处理 ### 紧急修复 优先检查关键功能的完整性 ### 新功能开发 重点关注设计模式和架构决策 ### 重构任务 评估重构的影响和风险


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: inkoak23-code/trench (version 0.1.0)

--- name: trench description: "Fast meme coin trading execution for AI agents. Snipe new token launches, execute rapid buys/sells on Solana DEXs (Jupiter, Raydium, Pump.fun), with MEV protection, auto-slippage, rug detection, and position management. Use when an agent needs to trade meme coins, snipe new pools, monitor token launches, or manage fast-paced degen positions on Solana." --- # Trench 🪖 Fast meme coin trading execution skill for AI agents on Solana. > ⚠️ This skill is under active development. Core modules coming soon. ## Capabilities (Planned) ### Execution - Rapid buy/sell via Jupiter aggregator + Raydium direct - Pump.fun token sniping and graduation tracking - Jito bundle submission for MEV protection - Priority fee optimization - Auto-retry on failed transactions ### Intelligence - New pool detection (Raydium, Pump.fun) - Rug/honeypot detection (liquidity lock check, mint authority, top holders) - Token safety scoring via Rugcheck API - Real-time price feeds via DexScreener / Birdeye ### Position Management - Auto take-profit / stop-loss - Trailing stops - Multi-wallet support - PnL tracking per position ## Architecture ``` trench/ ├── SKILL.md ├── scripts/ │ ├── buy.py # Fast buy execution │ ├── sell.py # Fast sell execution │ ├── snipe.py # New pool sniper │ ├── monitor.py # Token monitor & alerts │ ├── safety.py # Rug detection & token analysis │ └── portfolio.py # Position & PnL tracking └── references/ ├── jupiter-api.md # Jupiter V6 swap API reference ├── raydium.md # Raydium pool interaction ├── jito-bundles.md # Jito bundle submission └── pump-fun.md # Pump.fun API & graduation mechanics ``` ## Usage Examples ``` "Buy 0.5 SOL worth of POPCAT with 1% slippage" "Snipe the next pump.fun graduation with 0.1 SOL" "Set a 3x take-profit on my WIF position" "Check if this token CA is safe: <address>" "Show my open positions and PnL" ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jimmy-summarize (version 1.0.0)

--- name: summarize description: "Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube). Fast CLI to summarize URLs, local files, and YouTube links." allowed-tools: [] metadata: category: summarization version: 1.0 author: openclaw homepage: https://summarize.sh clawdbot: emoji: "🧾" requires: bins: ["summarize"] install: - id: brew kind: brew formula: steipete/tap/summarize bins: ["summarize"] label: Install summarize (brew) --- # Summarize Fast CLI to summarize URLs, local files, and YouTube links. ## Quick start ```bash summarize "https://example.com" --model google/gemini-3-flash-preview summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto ``` ## Model + keys Set the API key for your chosen provider: - OpenAI: `OPENAI_API_KEY` - Anthropic: `ANTHROPIC_API_KEY` - xAI: `XAI_API_KEY` - Google: `GEMINI_API_KEY` (aliases: `GOOGLE_GENERATIVE_AI_API_KEY`, `GOOGLE_API_KEY`) Default model is `google/gemini-3-flash-preview` if none is set. ## Useful flags - `--length short|medium|long|xl|xxl|<chars>` - `--max-output-tokens <count>` - `--extract-only` (URLs only) - `--json` (machine readable) - `--firecrawl auto|off|always` (fallback extraction) - `--youtube auto` (Apify fallback if `APIFY_API_TOKEN` set) ## Config Optional config file: `~/.summarize/config.json` ```json { "model": "openai/gpt-5.2" } ``` Optional services: - `FIRECRAWL_API_KEY` for blocked sites - `APIFY_API_TOKEN` for YouTube fallback


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

--- name: remi description: Manage Apple Reminders via CLI with section support and iCloud sync. Use when the user asks to create, list, complete, search, or organize reminders. metadata: {"openclaw": {"requires": {"bins": ["remi"]}, "install": {"brew": "mattheworiordan/tap/remi", "node": "@mattheworiordan/remi"}}} --- # remi — Apple Reminders CLI All commands support `--json` for structured output. Requires macOS 13+ with Reminders access. ## How to invoke Run `remi` as a CLI command via Bash. If `remi` is not on PATH, use `npx @mattheworiordan/remi` instead. Always use `--json` when calling programmatically. ## Commands ```bash # Lists remi lists # All lists remi list "<name>" # Reminders in a list remi list "<name>" --include-completed remi create-list "<name>" remi delete-list "<name>" --confirm # Reminders remi add "<list>" "<title>" # Simple add remi add "<list>" "<title>" --section "
" --due 2026-04-15 --priority high --notes "..." remi complete "<list>" "<title>" remi delete "<list>" "<title>" --confirm remi update "<list>" "<title>" --due 2026-05-01 --priority medium # Sections remi sections "<list>" # List sections remi create-section "<list>" "<name>" # Idempotent remi delete-section "<list>" "<name>" remi move "<list>" "<title>" --to-section "<name>" # Assign to section # Queries remi today remi overdue remi upcoming --days 7 remi search "<query>" # Diagnostics remi doctor ``` ## JSON mode Use `--json` for programmatic access. Returns `{"success": true, "data": ...}` or `{"success": false, "error": {"code": "...", "message": "...", "suggestion": "..."}}`. ## Key behaviors - **Idempotent** — creating an existing section returns success - **Title matching** — case-insensitive; use `--id <prefix>` if ambiguous - **Sections sync to iCloud** — changes appear on all Apple devices - **`--confirm` required** for delete operations in interactive mode (not needed with `--json`)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: artyomx33/geo-optimizer (version 1.0.0)

--- name: geo-optimizer version: 1.0.0 description: Optimize content for AI citation (GEO). Use when user says "GEO", "generative engine optimization", "AI citation", "get cited by AI", "AI-friendly content", or creating content for ChatGPT/Claude/Perplexity visibility. --- # GEO Content Optimizer ## When To Use - Creating content for AI citation - Refactoring articles for AI compatibility - Improving quotability for AI responses - Competing in AI-first search - Adding authority signals AI systems recognize ## Core Concept **SEO** = Rank in search results **GEO** = Get cited in AI-generated answers ## The 8 GEO Dimensions | Dimension | Low (1-2) | High (4-5) | |-----------|-----------|------------| | Definition Clarity | Vague | Citable definitions with metrics | | Quotable Statements | Generic claims | Specific facts with sources | | Factual Density | Opinion-heavy | Data-packed | | Source Citations | None | Traceable to authority | | Q&A Format | Prose only | Explicit Q&A sections | | Authority Signals | No credentials | Expert bylines, credentials | | Content Freshness | Outdated | Dated citations, recent data | | Structural Clarity | Poor hierarchy | Clear headers, lists, tables | ## The GEO Score Score each dimension 1-5. Total /40: - 32-40: AI-ready - 24-31: Needs optimization - 16-23: Major work needed ## Quick Wins (30-minute edits) 1. Add specific statistics with dates and sources 2. Create standalone definition paragraphs 3. Include expert quotes with credentials 4. Add comparison tables 5. Create FAQ section with 5-7 questions 6. Replace vague claims with verified facts 7. Insert authoritative source citations ## Output Format ```markdown ## GEO Audit Current Score: [X]/40 ### Dimension Scores | Dimension | Score | Quick Fix | |-----------|-------|-----------| | [dimension] | [1-5] | [action] | ## Optimized Content Sections ### Definition (Citable) [Term] is [category] that [function], [key metric]. ### Key Statistics - [Stat with source and date] - [Stat with source and date] ### FAQ Section **Q: [Common question]?** A: [Direct, quotable answer with citation] ``` ## Integration Compounds with: - **app-planning-skill** → Plan content strategy - **writing-plans** → Structure content projects --- See references/dimensions.md for scoring details See references/patterns.md for optimization patterns See references/examples.md for before/after examples


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: webpenbot/police-qualification-exam (version 1.0.0)

--- name: police-qualification-exam display_name: 警察执法资格考试助手 description: 警察执法资格考试助手，提供完整大纲解析、12年真题库（2013-2024年766题）、高频考点分析、模拟练习等功能。 version: 1.0.0 author: 彭子 category: [学习教育] tags: [执法资格, 警察考试, 公安考试, 真题, 大纲, 学习助手, 2026大纲] trigger: ["执法资格考试", "警察执法资格", "公安考试", "执法资格大纲", "警察考试真题", "历年真题", "2026大纲", "pqebot", "执法考试"] license: MIT openclaw: requires: bins: ["python3"] install: - id: skill-files


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: derick001/multi-chat-context-manager (version 1.0.0)

--- name: multi-chat-context-manager description: CLI tool to store and retrieve conversation contexts per channel/user. version: 1.0.2 author: skill-factory metadata: openclaw: requires: bins: - python3 --- # Multi-Chat Context Manager ## What This Does A simple CLI tool to store, retrieve, and clear conversation contexts. Contexts are saved as JSON, keyed by channel/user/thread IDs. This is a utility library, not an auto-integration plugin. ## When To Use - You need to manually store conversation history per channel or user - You want a simple key-value context store for your scripts - You're building custom integrations and need context persistence ## Usage Store a conversation: python3 scripts/context_manager.py store --channel "telegram-123" --user "user-456" --message "Hello" --response "Hi there" Retrieve context: python3 scripts/context_manager.py retrieve --channel "telegram-123" --user "user-456" Clear context: python3 scripts/context_manager.py clear --channel "telegram-123" List all contexts: python3 scripts/context_manager.py list ## Examples ### Example 1: Store and retrieve Store: python3 scripts/context_manager.py store --channel "discord-general" --user "john" --message "What is AI?" --response "AI is artificial intelligence." Retrieve: python3 scripts/context_manager.py retrieve --channel "discord-general" --user "john" Output: { "channel_id": "discord-general", "user_id": "john", "history": [{"message": "What is AI?", "response": "AI is artificial intelligence."}] } ## Requirements - Python 3.x - No external dependencies ## Limitations - This is a CLI tool, not an auto-integration plugin - Does not automatically intercept messages from platforms - Stores data in plaintext JSON (not encrypted) - No file-locking for concurrent access - You must call it manually from your scripts or workflows

path: data/contexts.json

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: nihaovand/kite-agent-smart-wallet-v3 (version 3.0.2)

# Kite AI Agent Smart Wallet Protocol V3 ## 简介 用户直接通过OpenClaw（Telegram）控制Kite AI链上钱包，无需自己运行Bot。 ## 架构 ``` 用户(Telegram) → OpenClaw → Kite AI合约 │ └── OpenClaw执行操作 ``` ## 功能 - 钱包创建 - 余额查询 - 转账 - Session Keys管理 - 消费限额 ## 命令 所有命令以 `/kite` 开头： | 命令 | 功能 | |------|------| | /kite help | 帮助 | | /kite create | 创建钱包 | | /kite wallet | 查看地址 | | /kite balance | 查看余额 | | /kite send \<地址\> \<数量\> | 转账 | | /kite session add \<地址\> \<限额\> | 添加授权 | | /kite limit set \<数量\> | 设置限额 | ## 网络 - 测试网: Chain ID 2368 - RPC: https://rpc-testnet.gokite.ai ## 合约 - AgentSmartWalletFactory: [REDACTED_SECRET] ## 版本 - v3.0.0 (2026-02-25): OpenClaw集成，直接TG控制 - v2.0.x: 用户本地运行Bot版本 - v1.0.0: 基础合约


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