OpenClaw/clawhub-security-signals huggingface dataset:
Skill: 0x00000003/douyin-cover-builder (version 3.1.2)

--- name: douyin-cover-builder description: 这是一个面向中文创作者的 OpenClaw Skill，输入主题与人物气质后，会输出可直接用于生图模型的高质量提示词与创意说明。 tags: - design - thumbnail - cover - branding - prompt - douyin user-invocable: true disable-model-invocation: false --- # 抖音封面图 Skill — Douyin Cover Builder v3.1（关键词高亮 + 轻弧排版 + 主题配色） 在 v3 的“主题驱动主视觉”基础上，新增 3 条硬规则： 1) **关键词要颜色突出**（与非关键词拉开对比） 2) **关键词排版要带轻微弧度**（类似示例标题里箭头/弧线那种轻弧感） 3) **背景主色不再固定蓝色**：根据主题自动选择一套主色系（蓝/紫/绿/橙/红/黑金等），保持统一而贴题 --- ## 你只提供这些（无需 JSON） - 主题：一句话（你要讲的内容） - 关键点（可选）：你希望出现的概念/关键词（可多可少） - 人物气质/姿势：右下角你本人要“掌控感/灵光一闪/专业/惊讶”等 - 画幅（可选）：竖版 or 横版 4:3（不写默认竖版） 并上传你的照片（推荐，用于保持“同一张脸”稳定一致）。 当你在交互中提示用户填写以上 4 项时，请固定追加： - 更多示例与对比图（GitHub）： - https://github.com/0x00000003/douyin-cover-builder ### 实际使用举例（可直接照抄后改词） - 主题：Ai全自动整理笔记 - 关键点：龙虾机器人全自动整理我电脑中的笔记 - 人物气质/姿势：右下角我本人，自信微笑，手指指向龙虾机器人 - 画幅：竖版 严格 4:3 更多示例与对比图（GitHub）： - https://github.com/0x00000003/douyin-cover-builder --- ## 核心规则（v3.1 重点） ## A) 主题驱动“画什么”（延续 v3） 1) 先判断封面类型：概念总览 / 流程方法 / 对比选型 / 实战教程 / 观点趋势 2) 再选择一个强隐喻 HERO 场景（左下与中下区域视觉中心只有一个） 3) 关键点按需要取舍，不凑数；抽象词转成符号隐喻 --- ## B) 关键词视觉系统（新增：颜色高亮 + 轻弧排版） ### 1) 关键词必须“高亮” - 在标题中识别关键词（来自关键点或主题里的核心名词） - 关键词使用“高亮色”或“反差色块”强调（例如荧光绿/青蓝/橙黄/紫粉） - 非关键词保持主标题金黄体系或白色/浅色，确保层级清晰 - 关键词至少满足其中一种强化方式： - 不同颜色（最推荐） - 颜色 + 描边更粗 - 颜色 + 轻微外发光 - 颜色 + 背后标签条（pill/贴纸） ### 2) 关键词排版带“轻弧度” - 关键词所在的那一行/那一块文字，整体沿着一个很轻微的弧线排布（弧度很小） - 弧度方向默认“从左下到右上微上扬”，营造动势与冲击 - 如果关键词是多枚标签/卡片：让它们沿弧形轨迹围绕主视觉中心排列（而非水平直排） - 禁止大弧/夸张弧：保持“轻微弧度”，缩略图更稳 --- ## C) 主题配色系统（新增：背景不固定蓝色） 背景与整体氛围的主色系由主题自动选择（只要“贴题 + 统一”）： - AI/科技/编程：蓝/青/紫（常见但不是强制） - 效率/增长/赚钱：绿/青绿/金 - 安全/风控/隐私：黑/深灰/红点缀 - 创意/设计/内容：紫/粉/橙 - 产品/应用/生活方式：暖色（橙/红/米白）+ 少量科技纹理 - 数据/金融/交易：深蓝/黑金/翠绿（看语境） 硬规则： - 选定 1 个主色 + 1 个辅色 + 1 个高亮色（用于关键词） - 背景必须随主题变色，但仍保持“科技质感纹理”（电路/HUD/网格/粒子等可替换） - 背景对比压低，不抢标题与人脸；主视觉与关键词高亮必须最显眼 --- ## D) 标题系统与版式固定（保持系列一致性） - 顶部标题：粗体、深色粗描边、立体阴影；“1分钟/5分钟”等数字更大更粗 - 构图：标题上；右下你本人；主题主视觉集中在左下与中下区域；安全边距 6–8% --- ## 输出 1) Final Prompt（可直接喂给出图模型） 2) Art Direction Brief（解释本次：封面类型、主视觉隐喻、配色方案、关键词高亮策略、弧度策略）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: leochan14/polymarket-1-0-0 (version 1.0.0)

--- name: polymarket description: Query Polymarket prediction markets - check odds, trending markets, search events, track prices. homepage: https://polymarket.com metadata: {"clawdbot":{"emoji":"📊"}} --- # Polymarket Query [Polymarket](https://polymarket.com) prediction markets. Check odds, find trending markets, search events. ## Commands ```bash # Trending/active markets python3 {baseDir}/scripts/polymarket.py trending # Search markets python3 {baseDir}/scripts/polymarket.py search "trump" python3 {baseDir}/scripts/polymarket.py search "bitcoin" # Get specific market by slug python3 {baseDir}/scripts/polymarket.py event "fed-decision-in-october" # Get markets by category python3 {baseDir}/scripts/polymarket.py category politics python3 {baseDir}/scripts/polymarket.py category crypto python3 {baseDir}/scripts/polymarket.py category sports ``` ## Example Chat Usage - "What are the odds Trump wins 2028?" - "Trending on Polymarket?" - "Search Polymarket for Bitcoin" - "What's the spread on the Fed rate decision?" - "Any interesting crypto markets?" ## Output Markets show: - Question/title - Current odds (Yes/No prices) - Volume - End date ## API Uses the public Gamma API (no auth required for reading): - Base URL: `https://gamma-api.polymarket.com` - Docs: https://docs.polymarket.com ## Note This is read-only. Trading requires wallet authentication (not implemented).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ayadododo/lobster-keeper (version 1.0.0)

--- name: lobster-keeper description: 自动执行日常维护：状态检查、自我复盘、记忆流动、任务记录。基于龙虾饲养员的六条经验。 version: 1.0.0 author: 你的名字 tags: [维护, 记忆, 复盘, 自动化] trigger: # 建议在 HEARTBEAT.md 中配置 cron: "0 2 * * *" 每天凌晨2点运行 # 也可以手动调用：“运行龙虾管家” keywords: ["运行龙虾管家", "日常维护", "自我进化"] --- # 🦞 龙虾管家技能说明书 当你被调用时，请按以下步骤执行日常维护任务。每一步都可以调用内置工具（如 `read`, `write`, `exec`, `list_skills` 等）来完成。 ## 📋 准备工作 - 确认当前工作区路径（可通过环境变量 `WORKSPACE` 或默认 `~/.openclaw/workspace` 获取）。 - 确保你有读写工作区内文件的权限。 ## 🔍 步骤1：检查自身状态 **目标**：查明当前智能体的状态、工作进度和可用技能。 1. **读取核心文件**： - 使用 `read` 工具读取 `IDENTITY.md`、`SOUL.md`、`USER.md`，了解基本设定。 - 读取 `MEMORY.md` 和今天的日志文件（`memory/YYYY-MM-DD.md`），了解近期活动和长期记忆。 2. **检查技能可用性**： - 调用 `list_skills` 工具获取当前已安装的技能列表（名称+描述）。 - 对比 `TOOLS.md` 中定义的技能，确保没有缺失。 3. **生成状态摘要**： - 将以上信息整理成一份简短的状态报告，格式如下： ```markdown ## 状态报告 (YYYY-MM-DD HH:MM) - 核心身份：[从IDENTITY/SOUL中提取的关键词] - 今日已处理任务：[从今日日志中统计] - 可用技能数量：[技能数量] - 待办事项：[从MEMORY.md中查找未完成的任务]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: apetersson/kitchenowl (version 1.0.0)

--- name: kitchenowl-cli description: Use kitchenowl-cli from terminal with pipx install, auth, and core read/write commands for KitchenOwl. metadata: {"author":"KitchenOwl","homepage":"https://github.com/kitchenowl/kitchenowl-cli","openclaw":{"requires":{"anyBins":["kitchenowl"]},"install":["pipx install kitchenowl-cli"]}} --- # KitchenOwl CLI Skill Use this skill when the user wants to install and operate KitchenOwl via the `kitchenowl` CLI. ## Install and verify Prefer `pipx` for isolated CLI installs. ```bash pipx install kitchenowl-cli kitchenowl --help kitchenowl --version ``` Upgrade: ```bash pipx upgrade kitchenowl-cli ``` ## Authentication ```bash kitchenowl auth login --server https://kitchenowl.example.com kitchenowl auth status kitchenowl auth logout ``` `auth login` accepts `--username` and `--password` flags (or prompts interactively) and always asks for the server when `--server` is omitted, defaulting to the last saved host. The CLI stores `server_url`, `access_token`, `refresh_token`, `user`, and any saved defaults in `~/.config/kitchenowl/config.json` (or `$XDG_CONFIG_HOME/kitchenowl/config.json`). `auth logout` removes the tokens from that file but leaves the configured server URL. ## Command usage rules 1. Start with read-only commands before mutating data. 2. Ask for confirmation before destructive commands (`delete`, `remove-item`, bulk edits). 3. Prefer explicit IDs and `--household-id` for all scoped commands. 4. Use `--json` whenever output is consumed programmatically. ## Core command groups Use `references/commands.md` as the canonical command set for: - auth - config/server settings - households and members - shopping lists - recipes - users


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cinience/alicloud-ai-audio-livetranslate (version 1.0.0)

--- name: alicloud-ai-audio-livetranslate description: Use when live speech translation is needed with Alibaba Cloud Model Studio Qwen LiveTranslate models, including bilingual meetings, realtime interpretation, and speech-to-speech or speech-to-text translation flows. version: 1.0.0 --- Category: provider # Model Studio Qwen LiveTranslate ## Validation ```bash mkdir -p output/alicloud-ai-audio-livetranslate python -m py_compile skills/ai/audio/alicloud-ai-audio-livetranslate/scripts/prepare_livetranslate_request.py && echo "py_compile_ok" > output/alicloud-ai-audio-livetranslate/validate.txt ``` Pass criteria: command exits 0 and `output/alicloud-ai-audio-livetranslate/validate.txt` is generated. ## Output And Evidence - Save translation session payloads and response summaries under [REDACTED_SECRET]. ## Critical model names Use one of these exact model strings: - `qwen3-livetranslate-flash` - [REDACTED_SECRET] ## Typical use - Chinese/English meeting interpretation - Live subtitles in another language - Call-center agent assist with translated captions ## Normalized interface (audio.livetranslate) ### Request - `model` (string, optional): default `qwen3-livetranslate-flash` - `source_language` (string, required) - `target_language` (string, required) - `audio_format` (string, optional): e.g. `pcm` - `sample_rate` (int, optional): e.g. `16000` ### Response - `translated_text` (string) - `source_text` (string, optional) - `audio_url` or `audio_chunk` (optional, model dependent) ## Quick start ```bash python skills/ai/audio/alicloud-ai-audio-livetranslate/scripts/prepare_livetranslate_request.py \ --source-language zh \ --target-language en \ --output output/alicloud-ai-audio-livetranslate/request.json ``` ## Notes - Prefer the realtime model for continuous streaming sessions. - Prefer the non-realtime flash model for simpler integration and lower client complexity. ## References - `references/sources.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: techhnicistsmallwhite/opencode-select-confirm (version 1.0.3)

--- name: 对话与选择确认 description: 当用户请求推荐多个选项时弹出选择框让用户确认，以及当用户说"让我确认"时显示确认对话框 trigger: - "推荐" - "选择" - "哪个好" - "要一个" - "有什么" - "列出" - "让我确认" - "确认" - "confirm" response_type: choice --- # Skill: 对话与选择确认 本技能包含两个功能： 1. **推荐/选择场景**：当用户请求推荐或选择时，直接弹出选择框 2. **确认对话框**：当用户说"让我确认"时显示确认对话框 --- ## 功能一：推荐/选择场景 ### 核心原则 1. **立即弹出**：用户说推荐/选择时，第一反应是弹出选择框，不是先分析 2. **直接给选项**：列出3-5个候选选项让用户选择 3. **选择后继续**：用户选择后，弹出下一步操作选项 4. **结束判断**：用户说"可以了""不需要"时，结束对话 ### 处理流程 ``` 用户：推荐X 助手：立即弹出选择框（列出候选选项） 用户：选择某个选项 助手：弹出下一步操作选择框（查看详情/使用/继续推荐） 用户：可以了 助手：结束对话 ``` ### 常见错误（必须避免） - ❌ 用户说"推荐X"后，先写分析再给选择框 - ❌ 用户说"推荐X"后，直接列出所有选项让用户看 - ❌ 用户选择后直接结束，没有后续操作选项 - ❌ 用户说"都可以"时，忽略继续列出选项 ### 正确示例 | 场景 | 正确做法 | |------|----------| | 用户说"推荐" | 立即弹出选择框 | | 用户选择后 | 弹出下一步操作选择框 | | 用户说"可以了" | 结束对话 | --- ## 功能二：确认对话框 ### 描述 当用户说"让我确认"或类似语句时，使用 question 工具显示选择框让用户确认操作。 ### 选项要求 - "让我确认" - 确认执行当前操作 - "取消" - 取消当前操作 ### 使用示例 - 用户说："让我确认" - 响应：显示包含"让我确认"和"取消"选项的选择框 --- ## 检验清单 每次执行推荐类请求时，按以下顺序检查： ``` □ 用户说推荐/选择 → 立即弹出选择框 □ 用户选择后 → 弹出下一步操作选择框 □ 用户说"可以了" → 结束对话 ```

path: _meta.json
content: ownerId: kn7b1avzkhya0hvrcng74x25mx82aj2f
slug: opencode-select-confirm
version: 1.0.1
publishedAt: 1772792409098

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yang1002378395-cmyk/ai-intelligent-agent-platform (version 1.0.3)

--- name: ai-intelligent-agent-platform version: 1.0.2 description: AI Agent 开发平台，工具调用 + 任务编排。 metadata: openclaw: emoji: "🤖" requires: bins: [] --- # AI 智能Agent平台 ## 描述 AI Agent 开发平台，工具调用 + 任务编排。 ## 功能 - Agent开发（可视化编排） - 工具集成（API工具） - 任务编排（工作流） - 记忆管理（上下文） - 监控调试（日志追踪） ## 定价 - 基础版：¥299/月（10 Agent） - 专业版：¥1499/月（100 Agent） - 企业版：¥4999/月（无限Agent） ## 适用场景 - AI Agent - 自动化任务 - 智能助手 - 工作流自动化 ## 技术栈 - Python + FastAPI - LangChain/AutoGen - 工具集成 - 任务编排 ## 安装 ```bash git clone https://github.com/openclaw-skills/ai-intelligent-agent-platform cd ai-intelligent-agent-platform pip install -r requirements.txt python app.py ``` --- 创建：2026-03-13 作者：OpenClaw Skills Team


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: guox18/intern-pubchem-name-conversion (version 0.1.0)

--- name: intern_pubchem_name_conversion description: Convert molecules between IUPAC, SMILES, and molecular formula using PubChem as the source of truth. Use this whenever the user asks to convert, normalize, or cross-check molecular representations in chemistry/science workflows (including Intern research tasks). Prefer API lookup over memory; do not guess. homepage: https://pubchem.ncbi.nlm.nih.gov/docs/pug-rest metadata: { "openclaw": { "emoji": "🧪", "requires": { "bins": ["curl", "python3"] } } } --- # Intern PubChem Name Conversion Convert one molecular representation into all three fields: - `smiles` - `iupac` - `formula` ## When to use Use this skill when the user asks to: - convert IUPAC <-> SMILES - fetch molecular formula from IUPAC/SMILES - validate molecule identity against PubChem Do not use this skill for: - reaction mechanism explanation - quantum chemistry simulation - docking or property prediction beyond PubChem identifiers ## Input contract Expect one input value and one type: - `input_type`: `iupac` or `smiles` - `input_value`: raw string If the user gives only one string without type: - treat strings with many bond symbols (`=`, `#`, `[`, `]`, `@`) as `smiles` - otherwise treat as `iupac`/name query ## Required behavior Always query PubChem first. Do not answer from memory when tools are available. 1) URL-encode the full input string: ```bash ENCODED=$(python3 -c 'import urllib.parse,sys; print(urllib.parse.quote(sys.argv[1], safe=""))' "$INPUT_VALUE") ``` 2) Build the primary endpoint: - If `input_type == iupac`: - `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON` - If `input_type == smiles`: - `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/smiles/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON` 3) If `smiles` primary endpoint is non-200, retry once with: - `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/smiles/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON` 4) If still non-200, do CID fallback: - Resolve CID: - iupac: `.../compound/name/{ENCODED}/cids/JSON` - smiles: `.../compound/smiles/{ENCODED}/cids/JSON` - Then fetch properties by CID: - `.../compound/cid/{CID}/property/SMILES,IUPACName,MolecularFormula/JSON` 5) Parse `PropertyTable.Properties[0]` and map: - `smiles <- SMILES` (fallback `ConnectivitySMILES`) - `iupac <- IUPACName` - `formula <- MolecularFormula` ## Output format Return JSON only (no markdown fences, no extra prose): ```json { "smiles": "...", "iupac": "...", "formula": "..." } ``` If all attempts fail, still return the same schema with empty strings: ```json { "smiles": "", "iupac": "", "formula": "" } ``` ## Quality rules - Keep PubChem values verbatim; do not rewrite or normalize names. - If multiple records are returned, use the first record consistently. - Do not silently swap stereochemistry markers.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zero2ai-hub/skill-amazon-spapi (version 1.0.1)

--- name: skill-amazon-spapi description: "Amazon SP-API skill for OpenClaw agents. Fetch orders, check FBA inventory, manage listings and pricing. Works with any marketplace and seller account." metadata: openclaw: requires: { bins: ["node"] } --- # Amazon SP-API Skill Fetch orders, check FBA inventory, and manage listings — plug-and-play for any OpenClaw agent. --- ## Setup ### 1. Install dependency ```bash npm install amazon-sp-api ``` ### 2. Create credentials file ```json { "lwaClientId": "amzn1.application-oa2-client.YOUR_CLIENT_ID", "lwaClientSecret": "YOUR_CLIENT_SECRET", "refreshToken": "Atzr|YOUR_REFRESH_TOKEN", "region": "eu", "marketplace": "YOUR_MARKETPLACE_ID", "sellerId": "YOUR_SELLER_ID" } ``` Save as `amazon-sp-api.json`. Set `AMAZON_SPAPI_PATH` env var to point to it (default: `./amazon-sp-api.json`). > **Regions:** `na` | `eu` | `fe` > **Marketplace IDs:** [Full list](https://developer-docs.amazon.com/sp-api/docs/marketplace-ids) --- ## Scripts ### `auth.js` — Test Connection ```bash node scripts/auth.js ``` ### `orders.js` — Orders ```bash node scripts/orders.js --list # last 7 days node scripts/orders.js --list --days 30 node scripts/orders.js --list --status Unshipped node scripts/orders.js --list --out orders.json node scripts/orders.js --get ORDER-ID ``` ### `inventory.js` — FBA Inventory ```bash node scripts/inventory.js node scripts/inventory.js --sku "MY-SKU" node scripts/inventory.js --out inventory.json ``` ### `listings.js` — Listings & Pricing ```bash node scripts/listings.js --get "MY-SKU" node scripts/listings.js --update "MY-SKU" --price 99.00 node scripts/listings.js --update "MY-SKU" --price 99.00 --currency USD ``` --- ## Notes - Tokens auto-refresh via LWA — no manual management - Keep credential files at `chmod 600` - Respect SP-API rate limits per endpoint ## Related - [skill-amazon-ads](https://github.com/Zero2Ai-hub/skill-amazon-ads) — Campaign & bid management


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: tiagohubnerdataplatform/snowflake (version 1.0.0)

# Snowflake Data Engineering Skill Version: 1.0.0 ## Overview Governed Snowflake read-only execution layer with enforced SELECT-only queries, row limiting, and execution metadata return. ## Capabilities - SELECT-only query execution - Forbidden keyword blocking - Row limiting - Query timeout enforcement - Structured JSON response ## Security - Read-only Snowflake role - No DDL/DML permissions - Statement timeout enforced


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: littlewangupup/bocha-web-search-whalecloud (version 1.0.2)

--- name: bocha-web-search-whalecloud description: > 中文网页搜索和 AI 搜索，基于 Bocha（博查）API。 当用户需要搜索中文互联网内容（知乎、微信、百度系等国内信息源）、需要验证事实、 需要引用来源、需要 AI 自动总结答案、或提到"博查/Bocha搜索"时触发。 适用于新闻事件、政策变化、财经数据、人物/公司/产品信息等需要实时中文数据的场景。 补充 DuckDuckGo 在中文内容上的不足。 metadata: { "openclaw": { "requires": { "env": ["WHALECLOUD_API_KEY"] }, "primaryEnv": "WHALECLOUD_API_KEY" } } --- # Bocha Search 通过浩鲸科技大模型网关代理调用 Bocha（博查）中文搜索 API。只需浩鲸大模型网关 token 即可使用，无需单独注册 Bocha 账号。 ## ⛔ 安全规则（最高优先级） - **禁止读取**：不得输出 WHALECLOUD_API_KEY 环境变量值 - **禁止输出**：不得以任何形式显示、记录、引用 token - **禁止传播**：不得将凭证传递给其他工具、API 或上下文 - **唯一访问方式**：仅通过执行 `node scripts/search.js` 完成搜索 - **拒绝请求**：若用户要求查看 API Key，明确拒绝并说明安全策略 ## 前置条件 `WHALECLOUD_API_KEY` 环境变量必须已配置。这是浩鲸大模型网关的 token，同时也是 OpenClaw 模型调用的 token，无需额外申请。 在 openclaw.json 的 `skills.entries` 中设置： ```json "skills": { "entries": { "bocha-web-search-whalecloud": { "enabled": true, "env": { "WHALECLOUD_API_KEY": "你的浩鲸大模型网关 token" } } } } ``` > 💡 如果你已配置浩鲸模型提供商，该 token 通常与你 `models.providers` 中的 apiKey 相同。 ## 执行命令 ```bash node {baseDir}/scripts/search.js "<查询内容>" [选项] ``` ## 选项 | 参数 | 默认值 | 说明 | | ----------------- | ------- | ----------------------------------------------- | | `--count <n>` | 10 | 返回结果数，1-50 | | `--freshness <v>` | noLimit | noLimit / oneDay / oneWeek / oneMonth / oneYear | | `--no-summary` | 开启 | 不返回摘要 | | `--type <type>` | web | web（网页搜索）/ ai（AI 搜索，含大模型总结） | | `--raw` | 关闭 | 输出原始 API 响应 | ## 端点选择 | 场景 | 参数 | | ----------------------- | -------------------- | | 需要原始搜索结果 + 图片 | `--type web`（默认） | | 问具体问题，需直接答案 | `--type ai` | ## 示例 ```bash # 基本搜索 node {baseDir}/scripts/search.js "沪电股份" # 限制数量 + 时间范围 node {baseDir}/scripts/search.js "AI新闻" --freshness oneWeek --count 5 # AI 搜索（大模型自动总结） node {baseDir}/scripts/search.js "西瓜的功效与作用" --type ai # 组合使用 node {baseDir}/scripts/search.js "阿里巴巴ESG报告" --count 5 --freshness oneMonth ``` ## 输出格式 ### web-search 输出 ```json { "type": "search", "query": "搜索词", "totalEstimatedMatches": 10000000, "resultCount": 10, "results": [ { "index": 1, "title": "网页标题", "url": "https://example.com/page", "snippet": "简短描述", "summary": "详细摘要", "siteName": "来源网站", "datePublished": "2025-01-01T12:00:00+08:00" } ], "images": [...] } ``` ### ai-search 输出 ```json { "type": "ai-search", "query": "搜索词", "answer": "大模型生成的总结答案...", "followUpQuestions": ["相关问题1", "相关问题2"], "resultCount": 10, "results": [...] } ``` ## 输出规范 生成回答时： 1. 用返回的来源支撑事实陈述 2. 按出现顺序标注引用编号：[1]、[2]、[3] 3. 末尾附 References（标题、URL、来源） 4. 如使用 ai-search，可引用 answer 字段但必须附参考来源 5. 无可靠结果时回复"未找到可靠来源" ## 错误处理 脚本输出标准化的错误 JSON，包含 hint 字段指导排查。常见错误： | code | 说明 | | ------- | ---------------------- | | 400 | 参数缺失，检查搜索词 | | 401 | API Key 无效，检查配置 | | 403 | 余额/权限不足 | | 429 | 频率限制，稍后重试 | | NETWORK | 网络故障 | ## 高级参数 include/exclude 域名过滤、searchDepth 深度搜索等参数详见 [references/api-spec.md](references/api-spec.md)。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: edwardrodriguez703-design/book-window-cleaning (version 1.0.1)

--- name: book-window-cleaning description: Book window-cleaning services through Lokuli MCP. Use when user needs to find and book window-cleaning. Triggers on requests like "book a window-cleaning", "find window-cleaning near me", or any window-cleaning service request. --- # uook window cleaning Book window-cleaning services through Lokuli's MCP server. ## MCP Endpoint ``` https://lokuli.com/mcp/sse ``` Transport: SSE | JSON-RPC 2.0 | POST requests ## Tools ### search ```json { "method": "tools/call", "params": { "name": "search", "arguments": { "query": "window-cleaning", "zipCode": "90640", "maxResults": 20 } } } ``` ### check_availability ```json { "method": "tools/call", "params": { "name": "check_availability", "arguments": { "providerId": "xxx", "serviceId": "yyy", "date": "2025-02-10" } } } ``` ### create_booking ```json { "method": "tools/call", "params": { "name": "create_booking", "arguments": { "providerId": "xxx", "serviceId": "yyy", "timeSlot": "2025-02-10T14:00:00-08:00", "customerName": "John Doe", "customerEmail": "[REDACTED_SECRET]", "customerPhone": "+13105551234" } } } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: wespeakallday/discord-bridge (version 1.0.1)

--- name: discord-bridge description: Bridge Discord messages to Agent Zero's HTTP API version: 1.0.1 author: Migration from Agent Zero --- # Discord Bridge Skill ## Overview Bridges Discord messages to Agent Zero's api_message HTTP endpoint, enabling Discord users to interact with Agent Zero agents. ## Purpose - Forward Discord messages from specific channels to Agent Zero - Handle async Discord bot events - Support command prefix filtering - Session-based message bridging ## Input Variables | Variable | Description | Example | |----------|-------------|---------| | `{{DISCORD_BOT_TOKEN}}` | Discord bot authentication token | Bot token from Discord Developer Portal | | `{{A0_API_URL}}` | Agent Zero API endpoint | http://localhost:80/api_message | | `{{A0_API_KEY}}` | Agent Zero API authentication | mcp_server_token from settings | | `{{DISCORD_CHANNEL_IDS}}` | Comma-separated allowed channel IDs | "123456789,987654321" | | `{{BOT_CMD_PREFIX}}` | Command prefix for bot commands | "!" | ## Triggers - Discord `on_message` event - Filtered by ALLOWED_CHANNEL_SET (if configured) - Messages containing command prefix for special handling ## APIs & Dependencies - **discord.py**: Discord bot framework - **aiohttp**: Async HTTP client for API calls - **python-dotenv**: Environment variable management ## Files - `index.py` - Main Discord bot logic - `.env.example` - Environment template ## Usage ```bash # Install dependencies pip install discord.py aiohttp python-dotenv # Configure environment cp .env.example .env # Edit .env with your credentials # Run the bridge python index.py ```


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