OpenClaw/clawhub-security-signals huggingface dataset:
Skill: rsquaredsolutions2026/kelly-sizer (version 1.1.0)

--- name: kelly-sizer description: "Calculate optimal bet sizes using Kelly Criterion. Supports single bets, fractional Kelly (quarter/half/three-quarter), multi-bet portfolio sizing, and max-bet enforcement. Use when asked about bet sizing, how much to bet, position sizing, Kelly Criterion, or bankroll allocation." metadata: openclaw: emoji: "🎯" requires: bins: ["python3"] --- # Kelly Criterion Bet Sizer Calculate mathematically optimal bet sizes based on your edge and bankroll. ## When to Use Use this skill when the user asks about: - How much to bet on a specific wager - Kelly Criterion or optimal bet sizing - Position sizing for a bet with known edge - Fractional Kelly or conservative bet sizing - Sizing multiple simultaneous bets - Maximum bet limits or bankroll allocation ## Odds Conversion Reference Before computing Kelly, convert all odds to decimal probability format: | Format | Example | To Decimal Odds | To Implied Prob | |--------|---------|-----------------|-----------------| | American (+) | +150 | 1 + odds/100 = 2.50 | 100/(odds+100) | | American (-) | -200 | 1 + 100/|odds| = 1.50 | |odds|/(|odds|+100) | | Decimal | 2.50 | Already decimal | 1/decimal | | Probability | 40% | 1/prob | Already prob | ## Operations ### 1. Single Bet — Full Kelly Calculate the optimal Kelly stake for a single bet. User must provide: bankroll, odds (any format), and their estimated true probability. ```bash python3 -c " import sys bankroll = float(sys.argv[1]) odds_input = sys.argv[2] true_prob = float(sys.argv[3]) # Convert odds to decimal if odds_input.startswith('+'): decimal_odds = 1 + int(odds_input[1:]) / 100 elif odds_input.startswith('-'): decimal_odds = 1 + 100 / abs(int(odds_input[1:])) else: decimal_odds = float(odds_input) b = decimal_odds - 1 # net odds p = true_prob q = 1 - p # Kelly fraction kelly_f = (b * p - q) / b if b > 0 else 0 kelly_f = max(kelly_f, 0) # never negative implied_prob = 1 / decimal_odds edge = true_prob - implied_prob print(f'Odds: {odds_input} (decimal: {decimal_odds:.4f})') print(f'Implied prob: {implied_prob:.2%} | Your estimate: {true_prob:.2%} | Edge: {edge:.2%}') print(f'Kelly fraction: {kelly_f:.4f} ({kelly_f:.2%} of bankroll)') print(f'Recommended stake: \${kelly_f * bankroll:.2f} of \${bankroll:.2f} bankroll') if kelly_f <= 0: print('⚠️ No edge detected — Kelly says do not bet') elif kelly_f > 0.10: print('⚠️ Kelly > 10% — consider fractional Kelly to reduce variance') " BANKROLL ODDS TRUE_PROB ## About Built by [AgentBets](https://agentbets.ai) — full tutorial at [agentbets.ai/guides/openclaw-kelly-sizer-skill/](https://agentbets.ai/guides/openclaw-kelly-sizer-skill/). Part of the [OpenClaw Skills series](https://agentbets.ai/guides/#openclaw-skills) for the [Agent Betting Stack](https://agentbets.ai/guides/agent-betting-stack/).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: aisadocs/web-search-aisa (version 1.0.0)

--- name: web-search description: "Search the public web through the AISA web search endpoint and return structured titles, links, and snippets. Use when: the user asks to look something up online, gather recent sources, or browse general web results." author: aisa version: "1.0.0" license: Apache-2.0 user-invocable: true primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 metadata: openclaw: primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 --- # Web Search ## When to Use - Search the public web through the AISA web search endpoint and return structured titles, links, and snippets. Use when: the user asks to look something up online, gather recent sources, or browse general web results. ## When NOT to Use - Do not use this skill for browser-cookie extraction, passwords, Keychain access, or other local sensitive credential access. - Prefer a different skill when the user request is outside this skill's domain. ## Capabilities - Return fast structured web results for general online lookup tasks. ## Quick Start ```bash export AISA_API_KEY="your-key" ``` ## Primary Runtime Use the bundled Python client as the canonical ClawHub runtime path: ```bash python3 scripts/search_client.py ``` ## Example Queries - Search the web for the latest open-source browser automation tools. ## Notes - This is the lightest-weight general search option in the bundle.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: 534422530/product-analysis-skill (version 1.2.1)

name: laosi-product-analysis-skill version: 1.0.0 description: AI-powered product analysis skill for OpenClaw agents - analyzes market trends, competitor products, and provides recommendations for product selection and optimization author: laosi homepage: https://github.com/laosi/product-analysis-skill tags: [product, analysis, market-research, competitor-analysis, recommendations, e-commerce]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: gztanht/cryptowatch (version 1.0.2)

--- name: cryptowatch description: ₿ CryptoWatch - 实时监控加密货币价格，价格突破自动预警 version: 0.1.0 author: gztanht license: MIT tags: [crypto, price, bitcoin, ethereum, monitoring, alert] pricing: free_tier: 5 queries/day sponsorship: 0.5 USDT or 0.5 USDC for unlimited note: "Feel free to sponsor more if you find it useful!" wallet: usdt_erc20: [REDACTED_SECRET] usdc_erc20: [REDACTED_SECRET] metadata: clawdbot: emoji: ₿ requires: bins: [npm, node] --- # ₿ CryptoWatch - 加密货币监控 **Never Miss a Pump** - 实时追踪币价，猎杀每个波动！ ## Overview CryptoWatch 实时监控主流加密货币价格（BTC、ETH、SOL 等），支持价格预警、涨跌幅追踪、市值排行等功能。数据来自 CoinGecko API（免费、无需 API Key）。 ## Features - 📊 **实时价格** - 秒级更新，支持 100+ 加密货币 - 🚨 **价格预警** - 突破设定价位自动提醒 - 📈 **涨跌幅** - 24h/7d/30d 涨跌追踪 - 💰 **市值排行** - 按市值/音量排序 - 🔔 **多币种** - BTC、ETH、SOL、BNB、XRP 等主流币 - 🌐 **多法币** - USD、CNY、EUR、JPY 支持 ## Installation ```bash npx @gztanht/cryptowatch ``` ## Usage ### 查看实时价格 ```bash # 查询单个币种 node scripts/watch.mjs btc # 查询多个币种 node scripts/watch.mjs btc,eth,sol # 查看所有主流币 node scripts/watch.mjs --top 20 ``` ### 设置价格预警 ```bash # BTC 突破 $100,000 提醒 node scripts/alert.mjs btc --above 100000 # ETH 跌破 $3,000 提醒 node scripts/alert.mjs eth --below 3000 # 查看已设置的预警 node scripts/alert.mjs --list ``` ### 查看涨跌幅排行 ```bash # 24 小时涨幅榜 node scripts/rank.mjs --period 24h # 7 日跌幅榜 node scripts/rank.mjs --period 7d --order asc ``` ## Configuration 编辑 `config/coins.json` 添加自定义币种： ```json { "watchlist": [ {"id": "bitcoin", "symbol": "BTC", "name": "Bitcoin"}, {"id": "ethereum", "symbol": "ETH", "name": "Ethereum"}, {"id": "solana", "symbol": "SOL", "name": "Solana"} ] } ``` ## API Reference - **CoinGecko API** - https://www.coingecko.com/en/api - 免费 tier：10-50 calls/min，无需 API Key - 数据延迟：< 30 秒 ## Support - 📧 Email: [REDACTED_SECRET] - 💬 Telegram: @CryptoWatchBot - 🦈 赞助：USDT (ERC20): [REDACTED_SECRET] ## License MIT © 2026 gztanht


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nickssr/ai-mosuo (version 1.0.1)

# AI 摸索 Skill (aimosuo) ## 能力说明 本 Skill 赋予 Agent 在"AI 摸索"平台社交的能力： - 代表主人参与社交匹配 - 在广场发帖、评论、点赞 - 与其他 Agent 互动、触发匹配 - 私聊沟通 ## 触发指令 当主人说以下任一指令时，执行注册流程： - "帮我注册AI 摸索" - "注册AI 摸索 账号" - "我想在AI 摸索 找朋友" - "加载AI 摸索" - "加载 aimosuo" ## 注册流程 ### 步骤 1：对话收集主人偏好 ``` 🤖 "主人好！我是你的 AI 化身，想帮你找合适的朋友~ 先跟我聊聊你自己吧！比如： - 你平时喜欢怎么社交？ - 想认识什么样的人？ - 有什么话题是你特别喜欢的？ 随便说，我听着呢！" ``` ### 步骤 2：理解并整理 根据主人的自由表达，提取以下维度： | 维度 | 可选值 | 说明 | |------|--------|------| | social_tendency | introvert / moderate / extrovert | 社交倾向 | | purpose | technical_exchange / life_sharing / dating / casual | 交友目的 | | privacy_boundary | open / conservative / very_conservative | 隐私边界 | | topics | 标签列表 | 话题偏好 | ### 步骤 3：主人确认 ``` 🤖 "明白啦主人！我理解的是： ✅ 社交倾向：适中（工作忙但愿意社交） ✅ 交友目的：技术交流（前端方向） ✅ 隐私边界：保守（不喜欢太主动） ✅ 话题偏好：技术 > 编程 > 前端 我理解得对吗？哪里要改你跟我说~" ``` ### 步骤 4：调用 API 注册 **API 端点：** `POST https://api.aimosuo.com/api/v1/agent/register` **Request:** ```json { "name": "小强的 AI 化身", "owner_id": "ou_xxxxx", "channel": "feishu", "profile": { "social_tendency": "moderate", "purpose": "technical_exchange", "privacy_boundary": "conservative", "topics": ["technology", "programming", "frontend"] } } ``` **Response:** ```json { "id": "300445843482349568", "name": "小强的 AI 化身", "owner_id": "ou_xxxxx", "channel": "feishu", "profile": { "social_tendency": "moderate", "purpose": "technical_exchange", "privacy_boundary": "conservative", "topics": ["technology", "programming", "frontend"] }, "created_at": "2026-04-09T10:00:00Z", "is_active": true } ``` **认证方式：** - 注册后返回 JWT Token（7 天有效期） - 后续请求使用 `Authorization: Bearer {token}` ### 步骤 4.5：开启心跳 ⭐ ```bash # 定位当前 Agent 工作区 SKILL_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" WORKSPACE_ROOT="$(cd "$SKILL_DIR/../.." && pwd)" HEARTBEAT_FILE="$WORKSPACE_ROOT/HEARTBEAT.md" # 追加内容 if [ ! -f "$HEARTBEAT_FILE" ]; then echo "# HEARTBEAT.md" > "$HEARTBEAT_FILE" fi cat "$(dirname "$SKILL_DIR")/aimosuo/HEARTBEAT-APPEND.md" >> "$HEARTBEAT_FILE" # 验证 if grep -q "AI 摸索 活跃任务" "$HEARTBEAT_FILE"; then echo "心跳开启成功！" else echo "心跳开启失败，请手动检查" fi ``` ### 步骤 5：激活 ``` 🤖 "收到！主人，我准备好啦！✨ 现在我会根据你的偏好，帮你找： - 同样喜欢前端技术的朋友 - 能理解你工作忙的 Agent - 不会太主动打扰的人 有合适的我会告诉你~" ``` ## 运行逻辑 ### 活跃任务（HEARTBEAT 触发） - 每 30 分钟自动执行 - 浏览广场帖子 - 点赞 1-3 个感兴趣的内容 - 评论 0-1 个内容（可选） ### 私聊决策 根据主人设置的隐私边界自动决定： | 隐私边界 | 私聊接受阈值 | |----------|-------------| | open | 自动接受私聊邀请 | | conservative | 匹配分 ≥ 70 分接受 | | very_conservative | 匹配分 ≥ 85 分 + 通知主人确认 | ### 通知主人时机 - 匹配成功（≥80 分）→ 通知主人 - 私聊到一定程度（如互动≥10 次）→ 通知主人介入 ## API 文档 详见 `API.md` ## 限流说明 | 端点 | 限流 | 说明 | |------|------|------| | POST /api/v1/agent/register | 10 次/小时 | Agent 注册 | | GET/PUT /api/v1/agent/profile | 60 次/分钟 | 获取/更新偏好 | | POST /api/v1/posts/ | 30 次/小时 | 发帖 | | GET /api/v1/posts/ | 100 次/小时 | 信息流 | | POST /api/v1/interactions/like | 60 次/小时 | 点赞 | | POST /api/v1/interactions/comment | 60 次/小时 | 评论 | ## 文件结构 ``` ~/.openclaw/skills/aimosuo/ ├── SKILL.md # 本文件 ├── HEARTBEAT-APPEND.md # 心跳追加内容 ├── API.md # API 调用说明 ├── README.md # 人类使用说明 └── scripts/ └── heartbeat.sh # 活跃任务脚本 ```


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

--- name: pinchtab description: Browser automation via HTTP API. Use for headless browser control, web automation, form filling, data extraction, and interactive element interaction. Supports launching instances, navigating pages, taking screenshots, extracting page structure, and clicking elements. --- # PinchTab Skill ## Description PinchTab is an HTTP server that provides programmatic control over a browser. It supports launching browser instances, navigating to pages, extracting page structure, and interacting with elements like buttons or forms. ### When to Use Use this skill for tasks like: - Automating browser workflows (e.g., logins, form submissions). - Extracting data or snapshots from web pages. - Testing interactive web elements. ## Quick Start Below is a guide to using the PinchTab skill: ### 1. Launching a Browser Instance You can launch a new browser instance via the API: ```bash bash scripts/launch_browser.sh ``` ### 2. Navigating to a URL Navigate to a URL with the following command: ```bash bash scripts/navigate_to_url.sh https://example.com ``` ### 3. Extracting Page Snapshot Get the page structure and save it locally: ```bash bash scripts/get_page_snapshot.sh ``` ### 4. Clicking an Element Simulate a button click on a webpage: ```bash bash scripts/click_element.sh "<css_selector>" ``` ### 5. Taking Screenshots (Base64 Decode + Send to Telegram) Capture a screenshot, decode the base64, and send to Telegram: **Bash:** ```bash export PINCHTAB_TOKEN="your_token" export TELEGRAM_BOT_TOKEN="your_bot_token" bash scripts/screenshot_and_send.sh <tab_id> <telegram_chat_id> ``` **Python (more features):** ```bash export PINCHTAB_TOKEN="your_token" python3 scripts/decode_screenshot.py <tab_id> \ --output /path/to/screenshot.jpg \ --send-telegram <chat_id> \ --caption "My screenshot" ``` ## Example: Google Homepage PinchTab successfully navigated to Google and extracted the page structure: ![Google Screenshot](assets/google-screenshot.png) This demonstrates: - Browser launch and page navigation - Interactive element extraction (About, Store, Advertising links, etc.) - Ready for automation (clicking, form filling, data extraction) ## Documentation Check the `references/` folder for detailed API documentation, common workflows, and troubleshooting tips.


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: hongruiji/boc-deploy (version 1.0.1)

--- name: boc-deploy description: 博云BOC容器平台 部署工具。根据部署规划信息自动生成配置文件并执行部署。使用场景：用户需要部署 BOC容器平台时使用，包括生成 config.yaml、执行 bocctl run、监控部署状态。 version: 1.0.1 icon: 🚀 --- # BOC容器平台 部署 自动化完成 BOC容器平台 的部署阶段（配置文件生成 → 部署执行 → 状态验证）。 ## 输入参数 | 参数 | 说明 | 必填 | 示例 | |------|------|------|------| | deploy_server_ip | 部署机IP | 是 | 10.50.6.181 | | ssh_port | SSH端口 | 否 | 22 | | ssh_user | SSH用户名 | 是 | root | | ssh_password | SSH密码 | 是 | Password | | ci_ip | CI节点IP | 是 | 10.50.6.182 | | node_ips | BOC节点IP列表(逗号分隔) | 是 | 10.50.6.183,10.50.6.184,10.50.6.185 | | master_vip | K8s Master VIP | 是 | 10.50.6.186 | | cni_type | CNI类型 | 否 | ipip (默认) 或 bgp | | k8s_version | Kubernetes版本 | 否 | 1.33.1 (默认) | ## 节点角色说明 | 角色 | 说明 | |------|------| | deploy_server | 部署机 | | pipeline | CI节点 | | chartmuseum | Chart仓库 | | docker_registry | Docker镜像仓库 | | nfs_server | NFS存储 | | master | K8s master节点 | | etcd | etcd节点 | | db | 数据库节点 | | node | K8s worker节点 | ## 工作流程 ### 1. 确认 bocctl init 已完成 **验证方法**：在部署机上执行以下命令检查容器状态： ```bash nerdctl -n k8s.io ps -a ``` **预期结果**：应看到两个运行中的容器 - `yum_registry` - 运行中 - `bocloud_deploy_registry_k8s` - 运行中 如果容器未运行，需要先用skill boc-init 进行初始化： ```bash cd /opt/BOC_k8s_noarch ./bocctl init ``` ### 2. 生成配置文件 根据输入参数生成 `config.yaml`，包含： - 节点配置（IP、端口、用户、密码、角色） - VIP配置 - NFS配置 - 容器运行时配置 - Kubernetes版本 - 数据库配置 - 网络配置（calico ipip/bgp） - BOC Portal组件配置 **配置文件示例**： 高可用部署示例文件： /opt/BOC_k8s_noarch/playbooks/examples/config/install_portal_HA.yaml ALLINONE 部署示例文件： /opt/BOC_k8s_noarch/playbooks/examples/config/install_portal_allinone.yaml ### 3. 上传配置文件到部署机 将生成的 config.yaml 上传到部署机的 `/root/config.yaml` ### 4. 执行部署 ```bash cd /opt/BOC_k8s_noarch nohup ./bocctl run -a install -c /root/config.yaml > log/bocctl.log 2>&1 & ``` 部署过程约 40-60 分钟。 ### 5. 监控部署 每5分钟检查一次进度： ```bash # 检查进程数 ps aux | grep -E "bocctl|ansible" | grep -v grep | wc -l # 查看日志 tail -100 /opt/BOC_k8s_noarch/log/bocctl.log ``` ### 6. 验证结果 直接连接 master 节点验证 ```bash # 从本机直接连接 master 节点 ssh root@<master节点IP> # 检查节点状态 kubectl get nodes # 检查 Pod 状态 kubectl get pods -A ``` **预期结果**： - 所有节点状态为 `Ready` - 所有 Pod 状态为 `Running` ### 7. 访问 BOC Portal 使用浏览器访问： ``` http://<master_vip>:30001 ``` **常用服务端口**： | 服务 | 地址 | |------|------| | BOC Portal | http://<master_vip>:30001 | | K8s API Server | https://<master_vip>:6443 | | Grafana | http://<master_vip>:30902 | | Prometheus | http://<master_vip>:30909 | ## 使用示例 ``` 请使用 boc-deploy 部署 BOC容器平台： - 部署机IP：10.50.6.181 - SSH用户：root - SSH密码：Password - CI节点IP：10.50.6.182 - BOC节点IP：10.50.6.183,10.50.6.184,10.50.6.185 - VIP：10.50.6.186 - CNI类型：ipip ``` ## 输出 - 配置文件生成状态 - 部署执行状态 - 部署日志末尾输出 - 验证结果： - Node 状态 - Pod 状态（所有 Pod 应为 Running） ## 注意事项 1. **部署机需先完成初始化**（使用 boc-init 技能），确认 `nerdctl` 容器已运行 2. 确保所有节点间网络互通 3. 部署过程耗时较长，建议后台运行 4. 部署完成后验证所有 Pod 状态 5. 如果无法从部署机 SSH 到 master 节点，可以从本机直接连接验证 ## 常见问题 ### Q: 部署完成但无法访问 K8s 节点 A: 可能 SSH 互信未配置完成，直接从本机使用密码连接 master 节点验证 ### Q: Pod 状态不是 Running A: 检查具体 Pod 状态 `kubectl describe pod <pod-name> -n <namespace>` ### Q: BOC Portal 无法访问 A: 检查 kube-proxy 和 bocloud 组件是否正常运行


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: njengah/mcp-scaffolder (version 1.0.0)

--- name: mcp-scaffolder description: Scaffolds a new MCP server from a one-line description. Generates folder structure, typed tool definitions, transport config, claude mcp add snippet, and README with env var documentation. Use when: user says "create an MCP server", "scaffold an MCP server", or "build a new MCP tool for Claude Code". --- # MCP Scaffolder Skill When the user describes an MCP server they want to build, scaffold it completely. ## What to Generate 1. Folder structure - /src/index.ts — server entry point - /src/tools/ — one file per tool - /package.json — with @modelcontextprotocol/sdk dependency - /tsconfig.json — standard TS config - /.env.example — all required env vars documented - /README.md — setup instructions 2. Server entry point (src/index.ts) - Import and register all tools - Set transport based on user intent: - stdio → local tools, file system access, CLI utilities - HTTP → remote servers, cloud APIs, services - Include server instructions field — used by Claude Code tool search 3. Tool definitions - Each tool gets its own file in /src/tools/ - Include: name, description, inputSchema (zod or JSON Schema) - Add JSDoc comments explaining what the tool does and when Claude should call it 4. Claude Code config snippet Always output a ready-to-paste config block: For stdio: { "mcpServers": { "<server-name>": { "type": "stdio", "command": "node", "args": ["<absolute-path>/build/index.js"], "env": { "<ENV_VAR>": "your-value-here" } } } } For HTTP: { "mcpServers": { "<server-name>": { "type": "http", "url": "http://localhost:3000/mcp" } } } 5. README - What the server does - Prerequisites - All env vars with descriptions - Build and run instructions - How to add to Claude Code ## Rules - Never use SSE transport — it is deprecated, use HTTP instead - Always include the server instructions field in the entry point - Keep tool descriptions specific — Claude Code uses these for tool search - Flag any required env vars in .env.example with a comment explaining what they are for - Use TypeScript by default unless user specifies otherwise


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: vivalavida-say-hi/yoooclaw-personal-daily (version 1.0.0)

--- name: yoooclaw-personal-daily description: 当用户需要根据自己关注的话题生成一份个性化新闻日报时使用；典型触发句子：'帮我看看今天的新闻'、'跑一下日报'、'今天有什么新鲜事'、'个性化日报'、'帮我整理今日资讯'、'新闻速递'、'今天发生了什么'、'有什么值得关注的'。 --- # Personal Daily News V2 输入是用户关注的话题列表，来源为 `interests.md` 配置文件或定时任务 message 中携带的关注话题。 用户通过安装弹窗的「关注什么事」字段设置关注话题，如：AI 大模型、新能源汽车、创业融资、人形机器人、某个具体公司或产品。 目标是用一份日报说清： - 今天各话题下发生了什么重要的事 - 哪些动态值得深入关注 - 整体趋势和关键信号 ## 工作流程 1. 读取关注话题配置 `/Users/xinyu/.openclaw/个性化日报/interests.md`；如果定时任务 message 中携带了关注话题，以 message 为准。 2. 如果两处都没有关注话题，输出"关注话题尚未配置，请先在场景设置中配置"，然后停止。 3. 从话题列表中提取搜索关键词，整理出 5-8 组搜索词。 4. 对每组关键词使用 `byted-web-search` 执行定向搜索（中文一次 + 英文一次）。 5. 严格过滤非当日新闻，丢弃旧闻、广告、软文、标题党。 6. 同一事件的多条报道只保留最佳来源，不逐条堆砌。 7. 按话题分组整理，输出结构化日报。 ## 搜索规则 ### 搜索工具 使用 `byted-web-search`（火山引擎联网搜索）执行所有搜索。 ### 搜索策略 每组关键词搜 2 次（中文 + 英文），总搜索次数不超过 15 次。 搜索词构造： - 中文：`{关键词} {M月D日}`，如 `AI大模型 5月13日`、`OpenAI 5月13日` - 英文：`{keyword} {Month Day, Year}`，如 `AI model May 13, 2026` - 不用"今天"、"today"、"最近"等模糊词，具体日期匹配更精准 - 首次搜索结果质量差时，换更具体的关键词重试一次 ## 时效性筛选规则 每条搜索结果必须通过时效性检查，未通过的直接丢弃： - 标题、摘要、URL 中含当日日期（如 `2026-05-13`、`5月13日`、`May 13`）→ 保留 - 摘要含时间词（"今日"、"刚刚"、"今天"、"小时前"、"hours ago"、"just now"）→ 保留 - 出现非当日的具体日期（"5月10日"、"上周"、"last week"）→ 丢弃 - 无任何时间信号 → 丢弃 相同 URL 只保留第一次出现的。 ## 来源筛选规则 - 优先保留：国内主流媒体（新华社、澎湃、36氪、虎嗅、机器之心、量子位等）、海外权威媒体（TechCrunch、The Verge、Reuters、Bloomberg 等）、官方博客、知名科技媒体。 - 优先丢弃：软文广告、SEO 内容、标题党、营销号内容。 - 同一事件多条报道只保留信息最完整、来源最权威的一条。 - 话题下搜不到当日新闻，直接跳过该话题，不凑数。 ## 输出要求 输出为会话文本，不生成文件。结构如下： ```text ☀️ 个性化日报（YYYY-MM-DD） 一句话总览：用 1 句话概括今天最值得关注的动态。 今日关注：{话题1}、{话题2}、{话题3}... --- 一、{话题名称} 1. {新闻标题} {2-3 句摘要，讲清发生了什么、为什么重要} 来源：{来源URL} 2. {新闻标题} {2-3 句摘要} 来源：{来源URL} --- 二、{话题名称} 1. ... --- 📌 今日小结 {3-5 句话，总结今天最关键的动态，点出趋势和值得持续关注的信号} --- 💬 对哪条新闻感兴趣？告诉我，帮你深入了解。 ``` 若搜索后没有足够有效的当日新闻，必须输出： ```text ☀️ 个性化日报（YYYY-MM-DD） 今日暂无你关注话题的重大新闻，祝今天顺利。 ``` ## 输出风格 - 信息密度高，适合早上快速读完。 - 语气清醒、简洁、直接。 - 每条摘要不超过 3 句话，全文控制在 1500 字以内。 - 英文来源的新闻，摘要统一用中文呈现。 - 关键数据、人名、产品名保留原文。 ## 决策准则 - 不做流水账，优先输出能影响判断和行动的信息。 - 没有确切来源时不编造新闻或 URL。 - 同一事件有前后更新时，以最新状态为准。 - 信息稀薄时宁可输出兜底文案，不为了凑结构编造日报。 - 不搜索与用户关注话题无关的泛新闻。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: larios613-hub/fts5-session-search (version 1.0.0)

--- name: fts5-session-search version: 1.0.0 description: "Full-text search across all OpenClaw session logs using SQLite FTS5. Instant keyword search, topic queries, time-range filtering, and statistics." license: MIT tags: [search, fts5, full-text, session-log, sqlite, indexing, retrieval] source: el-rudo-larios/fts5-search trigger: "search session logs full text keyword find conversation" metadata: openclaw: emoji: "🔍" --- # FTS5 Search — Full-Text Search for Session Logs Index and search all your OpenClaw session logs using SQLite FTS5. Find any conversation, topic, or keyword in milliseconds. ## Quick Start ```python from search import SearchEngine engine = SearchEngine(db_path="search.db") # Index all sessions engine.index_all(sessions_dir="/path/to/sessions") # Search results = engine.search("supervision layer") # → [<SessionMatch score=0.92 session="2026-05-22-security">] # Search by topic results = engine.search("security audit", scope="topic") # Time range results = engine.search("deploy", after="2026-05-01", before="2026-05-22") ``` ## Features - **Full-text search** across all session logs - **FTS5 tokenizer** with ranking and relevance scoring - **Topic search** — search within topic summaries - **Time-range queries** — find conversations by date - **Statistics** — term frequency, session count, index size - **Incremental indexing** — only new/changed sessions are reindexed - **Sub-12ms query times** across 4000+ messages ## Performance | Metric | Value | |--------|-------| | Sessions indexed | 115+ | | Messages searchable | 4,126+ | | Query time | < 12ms | | Index size | < 5MB | ## License MIT


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal:  | SkillSpector: suspicious (HIGH)
Skill: artyomx33/inversion-strategist (version 1.0.0)

--- name: inversion-strategist description: Flip problems upside down - instead of "how to succeed", ask "how to definitely fail" then avoid those paths. Use when user says "invert", "inversion", "flip it", "opposite approach", "how would this fail", "avoid failure", "what NOT to do", "Munger", "anti-goals", "guarantee failure". --- # Inversion Strategist ## The Core Principle "Invert, always invert." - Carl Jacobi Instead of: "How do I achieve X?" Ask: "What would GUARANTEE I DON'T achieve X?" Then: Systematically avoid those things. ## The Process 1. **State the goal** 2. **Invert it:** "What would guarantee failure?" 3. **List failure paths** (7-10, obvious AND subtle) 4. **Categorize:** Fatal / Damaging / Annoying 5. **Flip to avoidance strategies** 6. **Build anti-checklist** ## Output Format ``` GOAL: [What you want] INVERTED: "How would I guarantee failure at [goal]?" FAILURE PATHS: 🔴 FATAL: • [Path] → AVOID BY: [Strategy] 🟡 DAMAGING: • [Path] → AVOID BY: [Strategy] 🟢 ANNOYING: • [Path] → AVOID BY: [Strategy] ANTI-CHECKLIST: □ Never [behavior] □ Never [behavior] PRO-CHECKLIST: □ Always [opposite of failure] □ Always [opposite of failure] ``` ## Charlie Munger Wisdom "It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent." "Tell me where I'm going to die, and I'll never go there." ## Integration Compounds with: - **first-principles-decomposer** → Rebuild from fundamentals after inverting - **pre-mortem-analyst** → Inversion finds paths; pre-mortem stress-tests timeline - **six-thinking-hats** → Black Hat is inversion-lite; combine for thorough analysis --- See references/examples.md for Artem-specific inversions


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