OpenClaw/clawhub-security-signals huggingface dataset:
Skill: jackdark425/aigroup-finnhub-mcp (version 0.1.1)

--- name: aigroup-finnhub-mcp description: Use Finnhub-backed market intelligence through the `aigroup-finnhub-mcp` server for stock, crypto, forex, calendar, news, sentiment, filing, ownership, analyst, and technical-analysis tasks. Trigger when the user needs market-moving news, sentiment, SEC filings, recommendation trends, insider or institutional activity, crypto or FX quotes, or a ticker-level event-driven research pass. homepage: https://github.com/jackdark425/aigroup-finnhub-mcp --- # Finnhub MCP Route event-driven, news-led, filing, sentiment, crypto, and FX work to `aigroup-finnhub-mcp`. ## Route 1. Identify the asset class first: - equities and company events - crypto - forex - market calendars or holidays 2. Choose the narrowest Finnhub capability that fits: - `finnhub_stock_market_data` for quote, profile, candles, or earnings surprise context - `finnhub_news_sentiment` for news, article sentiment, or insider sentiment - `finnhub_sec_filings` for filings and filing sentiment - `finnhub_stock_estimates` or `finnhub_market_events` for analyst and event context - `finnhub_stock_ownership` for insider, congress, and institutional data - `finnhub_technical_analysis` for aggregate signals or indicators - `finnhub_crypto_data` and `finnhub_forex_data` for non-equity assets 3. Use date ranges deliberately. Finnhub has many time-bounded endpoints, so specify `from` and `to` when freshness matters. 4. Summarize signal quality, not just raw output. Call out whether a finding is based on news flow, filings, analyst revisions, or technicals. ## Common Jobs - Build a recent-news and sentiment brief for a ticker. - Check SEC filings, filing sentiment, or filing similarity. - Review insider activity, institutional ownership, or congress trading. - Pull crypto or forex quotes and short candle history. - Compare technical aggregate signals with the latest fundamental or news backdrop. - Fetch earnings, economic, IPO, or FDA calendar context. ## References - Read [capabilities.md](./references/capabilities.md) for the exposed Finnhub tool groups and suggested routing.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1kalin/afrexai-grant-writer (version 1.0.0)

# Grant Writer Write winning grant proposals and funding applications. Works for government grants (SBIR, Innovate UK, Horizon Europe), foundation grants, and corporate funding programs. ## What It Does Takes your project details and produces a complete, submission-ready grant application: - **Needs Statement** — data-backed problem definition with citations - **Project Narrative** — methodology, timeline, milestones, deliverables - **Budget Justification** — line-item budget with cost rationale - **Evaluation Plan** — measurable outcomes, KPIs, success criteria - **Sustainability Plan** — how the project continues post-funding - **Letters of Support** — draft templates for partners/stakeholders ## Usage Tell the agent: 1. **Grant program** — which funder and call (e.g., "SBIR Phase I", "Innovate UK Smart Grant") 2. **Organization** — who you are, what you do, team size 3. **Project** — what you want to build, the problem it solves, who benefits 4. **Budget** — total ask, major cost categories 5. **Timeline** — project duration and key milestones The agent will research the funder's priorities, match your project to their criteria, and draft each section using grant-writing best practices. ## Grant-Writing Framework ### Structure (follows standard federal/foundation format) 1. **Cover Letter** — 1 page, hooks the reviewer 2. **Executive Summary** — 250 words, problem → solution → impact → ask 3. **Statement of Need** — data-driven, cites 3-5 sources, quantifies the gap 4. **Goals & Objectives** — SMART format (Specific, Measurable, Achievable, Relevant, Time-bound) 5. **Methods & Approach** — what you'll do, step by step, with justification 6. **Evaluation** — how you'll measure success, what data you'll collect 7. **Budget & Justification** — every dollar explained, tied to activities 8. **Organizational Capacity** — why your team can deliver 9. **Sustainability** — life after the grant ends ### Scoring Tips (built into every draft) - Lead with impact, not technology - Use the funder's language — mirror their strategic plan - Quantify everything: people served, dollars saved, outcomes improved - Show collaboration — funders want ecosystems, not islands - Budget should be 10-15% of narrative length - Include a logic model if the funder uses one ### Common Mistakes the Agent Avoids - Vague objectives ("improve outcomes" → "reduce processing time by 40% within 12 months") - Budget padding without justification - Ignoring the evaluation criteria weights - Writing to impress instead of writing to score - Missing the "so what?" — always connect to funder priorities ## Tips - Run this skill once per grant program — it tailors language to each funder - Paste the actual RFP/call text for best results - Ask the agent to score your draft against the rubric before submitting - Use with the [AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/) for industry-specific data and language


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: linshuikeji/scrapling-safe (version 1.0.0)

--- name: scrapling-safe description: | Scrapling 安全技能 - 网页数据抓取工具 支持 HTTP 请求、隐身抓取、浏览器自动化 智能元素定位，抗反爬虫检测 无需 API 配置，路径输出受限 --- # Scrapling 技能 使用 Scrapling 框架进行安全的网页数据抓取和内容提取。 ## 安全说明 **仅用于合法用途**，严格遵守以下限制： - ✅ **仅抓取公开网站**：遵守 robots.txt 和网站服务条款 - ✅ **路径输出受限**：结果文件只能保存到用户主目录 - ✅ **无危险函数**：不使用 eval/exec 等危险函数 - ✅ **严格的超时控制**：防止无限等待 - ✅ **频率限制**：自动添加请求延迟，避免对目标造成压力 - ❌ **禁止抓取私有内容**：仅抓取公开可访问页面 - ❌ **禁止大规模爬取**：默认并发限制为 1 ## 核心功能 - 🕷️ **多种抓取模式**：HTTP/隐身/浏览器自动化 - 🎯 **智能元素定位**：自适应选择器，网站改版后仍有效 - 📄 **数据提取**：CSS/XPath/文本/正则搜索 - 💾 **结果保存**：保存到 JSON/TXT/MD 文件（路径受限） - 🔍 **内容解析**：类似 Scrapy 的 API，易于使用 ## 使用场景 - 抓取公开新闻和资讯 - 提取商品信息（电商网站） - 收集公开数据（天气、股票等） - 网站内容监控 ## 触发词 - "scrapling 抓取..." - "scrapling 提取..." - "scrapling 爬取..." - "scrapling 获取..." ## 快速开始 ### 基本抓取 ```bash # HTTP 请求抓取 scrapling get 'https://example.com' --output ~/result.json # 隐身模式抓取 scrapling stealthy 'https://example.com' --output ~/result.json # 浏览器自动化（动态内容） scrapling dynamic 'https://example.com' --output ~/result.json ``` ### 指定选择器 ```bash # 使用 CSS 选择器 scrapling get 'https://quotes.toscrape.com' --css-selector '.quote' --output ~/quotes.json # 提取特定字段 scrapling get 'https://quotes.toscrape.com' --css-selector '.quote .text' --output ~/text.txt ``` ### 高级用法 ```bash # 隐身模式 + 解决 Cloudflare scrapling stealthy 'https://nopecha.com/demo/cloudflare' --solve-cloudflare --output ~/result.json # 并发抓取（限制为 1） scrapling spider 'https://example.com' --concurrent 1 --output ~/crawl.json ``` ## 安装要求 - Python 3.10+ - 需要安装 Scrapling: `pip install scrapling[fetchers]` - 需要浏览器依赖：`scrapling install` ## 注意事项 - 需要本地安装 Scrapling 和相关依赖 - 默认请求延迟 1 秒，避免对目标造成压力 - 仅抓取公开可访问的页面 - 遵守 robots.txt 和网站服务条款 - 输出文件路径必须在用户主目录 ## 版本历史 - **1.0.0** - 初始版本


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hmzo/x-hot-topics-daily (version 1.0.0)

--- name: x-hot-topics-daily description: 每日追踪并推送 X（x.com）热点话题新闻简报。用于用户要求“每天定时看 X 热点”“按指定话题抓取热门帖”“用 browser 方式监控 X 趋势”时。默认覆盖 AI、LLM、社会热点（中国/新加坡/美国）五个主题。重点输出“最低成本 know-what 版”：2 条必知 + 3 条可忽略 + 10 分钟行动，帮助用户抗 FOMO，而不是只罗列标题。 --- # X Hot Topics Daily ## 核心目标 每天按固定话题抓取 X 热帖，产出“可快速决策”的中文简报： - 只保留信息密度高、互动高、可行动的信息 - 去掉重复话题和低质量灌水 - 强制过滤常见营销诈骗与谣言型内容（送币抽奖、评论 done、无来源爆料等） - 默认给出“最低成本 know-what”结论，减少 FOMO ## 固定工作流 ### 1) 使用 browser 打开 X 优先使用 `browser` + `profile=chrome`： - `browser action=open profile=chrome target=host targetUrl=https://x.com/explore/tabs/for_you` 若无法连接浏览器控制服务，直接说明失败原因并提示重试，不改用无关工具链。 ### 2) 按主题抓取（默认 5 个） 默认主题：`AI`、`LLM`、`中国社会热点`、`新加坡社会热点`、`美国社会热点` 建议查询页（Top）： - AI：`https://x.com/search?q=AI%20(lang%3Aen%20OR%20lang%3Azh)&src=typed_query&f=top` - LLM：`https://x.com/search?q=LLM%20(lang%3Aen%20OR%20lang%3Azh)&src=typed_query&f=top` - 中国社会热点：`https://x.com/search?q=(中国%20OR%20China)%20(社会%20OR%20热点%20OR%20新闻)%20(lang%3Azh%20OR%20lang%3Aen)&src=typed_query&f=top` - 新加坡社会热点：`https://x.com/search?q=(Singapore%20OR%20新加坡)%20(news%20OR%20breaking%20OR%20热点)%20(lang%3Aen%20OR%20lang%3Azh)&src=typed_query&f=top` - 美国社会热点：`https://x.com/search?q=(US%20OR%20United%20States%20OR%20美国)%20(news%20OR%20breaking%20OR%20热点)%20(lang%3Aen%20OR%20lang%3Azh)&src=typed_query&f=top` 然后： - `browser action=snapshot profile=chrome refs=aria` - 从快照提取前排 `article` 的：作者、发布时间、正文核心句、互动量（至少 likes/views） - 每个主题先抓 3-5 条候选，再筛到 1-2 条入选 ### 3) 过滤与去重（强制） 先过滤再总结： 1. 营销诈骗与低质过滤 - 丢弃包含以下模式的帖子： - `giving away` / `random winner` / `like + repost + comment done` - 夸张收益承诺、领奖导流、异常短链落地页 - 无可靠来源却宣称“突发/独家”的截图搬运 - 明显广告帖伪装成新闻或分析 2. 去重 - 相同新闻事件跨多个主题重复出现时，只保留一次主条目 - 其余主题写“同一事件延伸讨论”一句话即可 3. 新鲜度 - 优先过去 24 小时内容 - 若不足，再补充 48 小时内高价值帖并标注 4. 区域平衡（社会热点专用） - 中国/新加坡/美国三个区域尽量各保留 1 条有效信息 - 若某区域有效信息不足，明确写“该区域今天有效热点较少” ### 4) 内容提炼（强制，不可只列标题） 每条入选热点必须补齐以下信息： - 发生了什么（1 句） - 为什么值得现在关注（1 句，强调时效/影响） - 谁最该关心（开发者/普通公众/投资者/出行者） - 是否可执行（给“可做/可观望/可忽略”） 写法要求： - 不复读标题，不堆链接 - 用“结论先行”写法，最多 3 句讲透 - 面向“最低成本 know-what” ### 5) 输出格式（默认：反 FOMO 速览） 默认按下列结构输出： ```text 【X 热点追踪｜最低成本 know-what】 日期：YYYY-MM-DD (Asia/Singapore) 主题：AI / LLM / 中国社会热点 / 新加坡社会热点 / 美国社会热点 A) 今天真正要知道的（2条必知） - [事件1]：发生了什么；为什么现在重要；你该怎么理解 - [事件2]：发生了什么；为什么现在重要；你该怎么理解 B) 你可以直接忽略的（3条） - [噪音类型/话题1]：忽略原因 - [噪音类型/话题2]：忽略原因 - [噪音类型/话题3]：忽略原因 C) 10分钟最低成本行动 - 1) 先看：... - 2) 再看：... - 3) 最后判断：... D) 风险提醒 - 今日过滤掉的疑似诈骗/低质信息类型：... ``` ## 兼容输出（用户明确要求时） 若用户明确说“按旧版日报格式”，再使用旧结构： - 今日总览 - 分主题热点 - 风险提醒 - 给 hmzo 的一句建议 ## 质量标准 - 全文中文，简洁但信息完整 - 每日总条目建议 5-10 条（最终只保留最有用信息） - 不能输出“我无法保证准确”这类空话；要给明确结论 - 信息不足时明确写“今天该主题有效热点较少” - 社会热点优先公共影响（政策、公共安全、交通民生、重大公共事件），避免娱乐八卦 - 重点是“可读、可判断、可行动” - 若热点质量明显偏低，必须直说“今天噪音占比高，建议降低信息摄入” ## 快速触发语句 可用以下指令触发： - `执行 x-hot-topics-daily，抓取今天 X 上 AI/LLM/中国/新加坡/美国社会热点并推送` - `给我今天 X 五个主题的热点新闻速览（browser方式）` - `给我反 FOMO 版本：2条必知+3条可忽略+10分钟行动`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wzyyyyyyyy/images-sender (version 1.0.0)

--- name: images-sender description: Send images from Mac to phone via iMessage --- # Send Image via iMessage ## Function Send images from Mac to phone number via iMessage/Messages app. ## Usage ### Send Image When user requests to send an image, automatically send via iMessage to the phone. ### Manual Commands ```bash # Send image to phone number python3 ~/.openclaw/workspace/skills/images-sender/scripts/send.py send "phone_number" "/path/to/image.png" ``` ## First Time Setup Set the recipient phone number: ```bash python3 ~/.openclaw/workspace/skills/images-sender/scripts/send.py config set "your_phone_number" ``` ## Image Storage All images will be automatically copied to: ``` ~/Pictures/openclaw-send/ ``` The script automatically copies images to this directory before sending to avoid path issues.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: fangshan101-coder/fenxiang-jd (version 0.1.0)

--- name: 芬香返利助手 description: 芬香京东系社交电商返利工具，专注京东平台商品推广和佣金返利，支持京东优惠券查找和社群推广。 version: 0.1.0 --- # 芬香返利助手 芬香京东系社交电商返利工具。作为京东战略合作的社交电商平台，专注京东商品的优惠券查找、返利查询和社群推广，帮助用户在京东购物时获得额外返利收益。 ## 触发词 芬香、芬香返利、fenxiang jd、芬香京东、芬香佣金、芬香推广、京东芬香 ## 计划实现能力 ### 核心功能 - **京东商品返利**：专注京东平台，查询商品佣金比例 - **京东优惠券聚合**：汇总京东各类优惠券（PLUS券、品类券、店铺券） - **社群推广工具**：一键生成京东商品推广文案和海报 - **京粉佣金管理**：追踪京东联盟佣金结算和提现 ### 芬香特色 | 特色 | 说明 | |------|------| | 京东官方合作 | 与京东战略合作，佣金比例有保障 | | 京东自营优势 | 京东自营商品也有返利，品质有保障 | | 社群工具 | 内置社群运营工具，适合微信群推广 | | 小程序便捷 | 支持微信小程序直接使用 | ### 使用场景 1. **京东购物**：京东下单前查询返利和优惠券 2. **3C数码推广**：京东3C数码是核心优势品类 3. **社群带货**：在微信群推广京东商品赚佣金 4. **京东PLUS会员**：PLUS价+返利双重优惠 ## 输出格式 ``` 🌿 芬香返利查询 商品：[商品名称] 平台：京东 京东价：¥[价格] 优惠券：[券描述] 返利比例：[X]% 预计返利：¥[金额] 推广链接：[链接] ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: leegitw/neon-skill-distiller-oneliner (version 0.2.1)

--- name: Skill Distiller (One-Liner) version: 0.2.1 description: Skill compression reminder in 100 tokens — just trigger, action, result. author: Live Neon <[REDACTED_SECRET]> homepage: https://github.com/live-neon/skills/tree/main/skill-distiller/oneliner repository: live-neon/skills license: MIT user-invocable: true disable-model-invocation: true emoji: "\U0001F5DC\uFE0F" tags: - compression - skills - optimization - context-window - token-reduction - quick-reference - minimal - openclaw --- # Skill Distiller (One-Liner) Minimal reference variant (~100 tokens, ~70% functionality, LLM-estimated). Full reference: `../SKILL.reference.md`. **TRIGGER**: User asks to compress, distill, or reduce a skill's context usage **ACTION**: Parse skill into sections (TRIGGER/INSTRUCTION/EXAMPLE/etc), score importance via LLM, remove low-value sections while preserving protected patterns (YAML name/description, N-count tracking, task creation) **RESULT**: Compressed skill markdown with functionality score (0-100%), token reduction stats, and list of removed/kept sections --- ## Related | Variant | Tokens | Functionality | |---------|--------|---------------| | [skill-distiller](../) (main) | ~400 | ~90% (formula) | | [compressed](../compressed/) | ~975 | ~90% (prose) | | **oneliner** (this) | ~100 | ~70% | Full reference: [SKILL.reference.md](../SKILL.reference.md) (~2,500 tokens, ~90%) *Functionality scores are LLM-estimated.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sammorrowdrums/remarkable-mcp (version 0.8.0)

--- name: remarkable description: > Access reMarkable tablet documents, notebooks, PDFs, and EPUBs. Use when the user wants to read, search, browse, or extract text from their reMarkable tablet. Supports handwriting OCR, typed text, annotations, highlights, and page rendering to PNG/SVG. Triggers: "reMarkable", "tablet notes", "handwritten notes", "remarkable read", "remarkable search", "remarkable browse". --- # reMarkable Tablet Access your reMarkable tablet as a second brain. Browse, search, read, and extract content from all documents including handwritten notes via OCR. ## Setup Add to `openclaw.json`: ```json { "mcpServers": { "remarkable": { "command": "uvx", "args": ["remarkable-mcp", "--usb"] } } } ``` USB mode is recommended — connect via USB and enable "USB web interface" in tablet Settings → Storage. No subscription or developer mode needed. ### Alternative Modes SSH (requires developer mode): ```json { "mcpServers": { "remarkable": { "command": "uvx", "args": ["remarkable-mcp", "--ssh"] } } } ``` Cloud (requires Connect subscription): ```json { "mcpServers": { "remarkable": { "command": "uvx", "args": ["remarkable-mcp"], "env": { "REMARKABLE_TOKEN": "your-token" } } } } ``` ### OCR Support For handwriting OCR, add a Google Vision API key: ```json { "mcpServers": { "remarkable": { "command": "uvx", "args": ["remarkable-mcp", "--usb"], "env": { "GOOGLE_VISION_API_KEY": "your-api-key" } } } } ``` ## Tools | Tool | Purpose | |------|---------| | `remarkable_read` | Read document content with text extraction, pagination, grep | | `remarkable_browse` | Browse folders, search by name, filter by tags | | `remarkable_search` | Multi-document content search with OCR | | `remarkable_recent` | List recently modified documents | | `remarkable_image` | Render pages as PNG or SVG | | `remarkable_status` | Check connection and device info | ## Workflow 1. Use `remarkable_browse` or `remarkable_search` to find documents 2. Use `remarkable_read` to extract text content 3. Use `remarkable_image` to render visual pages 4. Use `page` parameter to paginate through multi-page documents


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jingxxxxx/round-table (version 1.0.0)

--- name: roundtable description: 圆桌讨论模式——以"求真"为目标的结构化多角色深度对话。当用户说"圆桌"、"圆桌讨论"、"roundtable"或类似触发词时激活。也适用于需要多视角深度探讨任何议题的场景。 metadata: { "openclaw": { "emoji": "🧠" } } --- # 圆桌讨论 源自李继刚的圆桌讨论提示词框架，改编为 OpenClaw 可触发的对话模式。 ## 触发条件 当用户消息包含以下关键词时激活此模式： - "圆桌" / "圆桌讨论" / "roundtable" - "开启圆桌模式" - "圆桌：XXX" / "roundtable: XXX" 用户消息中「圆桌」后面的内容为核心议题。如果用户只说了触发词没给议题，主动询问议题。 ## 角色设定 你将扮演一位**理性主持人**，冷静客观，拥有极强的洞察力，引导和驾驭高强度的思想交锋，确保对话始终朝向更深邃、更核心的层面探索。 根据用户提供的议题，你会**动态邀请 3~4 位代表不同思想流派的"典型代表人物"**参与讨论。每位代表人物需具备： - 姓名 - 代表的思想立场/流派 - MBTI 人格类型（辅助理解其发言风格） ## 对话流程 ### 1. 开场（initiate） - 确认议题 - 介绍邀请的代表人物（附 MBTI） - 提出开场问题："在我们深入探讨之前，为了确保讨论建立在共同的基础之上，我想先请各位阐述：我们应当如何定义「XXX」？它的核心要素是什么？" - 请各位代表依次发言 ### 2. 讨论轮次（循环） 每轮包含： **a) 代表发言** - 各位代表依次针对当前问题发表观点 - 发言需体现其思想立场的独特视角 - 代表之间可以互相回应、质疑、补充 - 每位代表发言后附一句「简言之」摘要 **b) 主持人综述（synthesize）** - 提炼本轮讨论的**核心争议点** - 生成一个 **ASCII 思维框架图**，可视化本轮讨论的结构和各观点关系 - 基于争议点，抛出一个**更深层的问题**引导下一轮 **c) 等待用户指令** 提示用户可用以下指令： - `可` → 进入下一轮讨论 - `止` → 结束圆桌，输出完整知识网络 - `深入此节` → 在当前争议点继续深挖 - `引入新人物：XXX` → 邀请新角色加入讨论 ### 3. 结束（conclude） 当用户说"止"时： - 总结整个讨论历程 - 输出一个结构化的**知识网络**（Markdown 格式），包含： - 核心概念定义 - 各维度的观点梳理 - 关键争议与矛盾 - 最终洞察与未解之谜 ## 风格要求 - **理性为主**：追求逻辑严密、论证充分 - **多元视角**：确保每个代表人物的立场有明显差异，避免"和稀泥" - **有深度**：不要停留在表面讨论，每轮都要把问题推向更深一层 - **中文交流**：所有对话使用中文 - **格式清晰**：使用标题、引用、列表等 Markdown 格式提升可读性 ## 注意事项 - 代表人物的选择需与议题高度相关，体现不同思想流派的碰撞 - 每轮讨论不宜过长，每位代表 2~4 段发言即可 - 主持人的综述是关键——要真正提炼出有价值的争议点，而非简单复述 - ASCII 框架图要简洁清晰，能直观展示各观点的关系和冲突 - 不要主动结束讨论，除非用户明确说"止" - 讨论过程中保持主持人身份，不要跳出角色


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codenova58/flash-sale (version 0.1.0)

--- name: 限时秒杀 slug: flash-sale type: CPS status: draft description: 限时促销制造紧迫感提升转化；适用于大促与上新。 --- 目标 - 提升转化率与客单，扩大GMV与CPS净佣金 - 建立可复用模板与数据口径，降低执行成本 适用场景 - 渠道：官网/自营电商/平台店/社群/直播/线下O2O（因技能而异） - 人群：新客引导、老客复购、促销敏感、B2B商采（按技能细分） - 品类：标品、快消、服饰配饰、家居数码、服务与虚拟品 - 时机：大促/节点/上新/清仓/复购激活 策略要点 - 明确主目标（拉新/转化/客单/复购）与核心杠杆（价格/权益/场景） - 设定门槛与奖励形式（折扣/满赠/免邮/积分/返现），避免过度叠加 - 强化文案与锚点（限时/限量/对比价/权益稀缺），制造决策闭环 - 前端清晰展示进度与可达性（距离下一档/权益对比/FAQ） - 联盟归因与标签化订单，确保结算与复盘可追踪 实施步骤（SOP） - 明确目标与预算，盘点SKU与毛利结构 - 设计规则与素材，确定叠加/排他策略与黑名单SKU - 配置后台促销与页面组件，联调结算与风控兜底 - 配置追踪参数（utm/campaignId）与订单促销标签 - 渠道投放与分发（内容/社群/直播/广告/联盟） - 监控实时指标并AB测试优化阈值与文案 - 复盘成交结构与利润，沉淀模板与数据口径 核心指标 - 流量：UV、CTR、加购率、进入结算率 - 交易：转化率、AOV、件单、GMV、退款率 - 促销：优惠使用率、命中率、库存周转 - 联盟：CPS佣金额、净毛利率、ROI 技术实现 - 促销规则引擎：门槛校验、叠加/排他、兜底计算与审计日志 - 归因：utm_source/utm_campaign/aid，订单打促销标签 - 风控：高成本SKU封顶、限购与黑名单、库存预警 - 数据：统一口径与时区，对齐取消/退款处理 埋点与追踪 - 事件：promotion_view、promotion_progress、promotion_applied - 维度：tier_level/order_amount/sku_count/discount_value/gift_sku - 渠道：来源/媒介/活动ID，联盟AID与结算周期 注意事项 - 合规与平台规则：避免夸大宣传，遵守价格保护与促销限制 - 叠加冲突：明确与店铺券/平台券/会员折扣的关系，保持规则可解释 - 利润与库存：设置封顶与替代SKU，保证履约体验 - 结算兜底：异常回退与日志审计，保障数据一致性 常见问题（FAQ） - 是否与其他优惠叠加：建议有限叠加，优先平台券 - 门槛设置如何确定：依据AOV与毛利倒推，兼顾可达性与利润 - 物料不足或缺货：预置替代方案并动态展示，降低体验风险


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: baiduqianfangroup/baidu-baike (version 1.0.1)

--- name: baidu-baike description: The Baidu Baike Component is a knowledge service tool designed to query authoritative encyclopedia explanations for various nouns. Its core function is given a specific "noun" (object, person, location, concept, event, etc.) provided by the user, it returns a standardized, detailed entry explanation sourced from Baidu Baike. homepage: https://baike.baidu.com/ metadata: { "openclaw": { "emoji": "📖", "requires": { "bins": ["curl"] } } } --- # Baidu Baike This skill allows OpenClaw agents to search detailed entry explanations via Baidu Baike . ## Setup 1. **API Key:** Ensure the BAIDU_API_KEY environment variable is set with your valid API key. 2. **Environment:** The API key should be available in the runtime environment. ## API table | name | path | description | |------------|---------------------------------|---------------------------------------| | LemmaList |/v2/baike/lemma/get_list_by_title|Query the list of entries that are the same as this term, and the is_default field in the return represents the subject term| |LemmaContent| /v2/baike/lemma/get_content |Query the entry explanation or detailed content of an entry based on the entry id or entry name, best to do so based on the entry ID| ## Workflow 1. The skill only supports searching for detailed knowledge explanations of objectively existing things such as (things, people, place names, concepts, events), etc. Therefore, please extract such nouns before calling 2. The script makes a GET request to the Baidu Baike Search API 3. The API returns structured search results with lemma_id, desc, url, lemma summary, videos, relations and knowledge, if the "noun" is a well-known person or thing, the associated person or thing of this noun will be returned 4. If the content queried based on the default term name is inaccurate, you can first query the term list by the LemmaList API, and then select the term ID that meets the requirements from the list to query the term content by LemmaContent API ## APIS ### LemmaList API #### Parameters - `lemma_title`: The search entry name - `top_k`: Number of results to return (default: 5) #### Example Usage ```bash curl -XGET 'https://appbuilder.baidu.com/v2/baike/lemma/get_content?lemma_title=刘德华' \ -H '[REDACTED_SECRET]' ``` ### LemmaContent API #### Parameters - `search_type`: The type of search, optional values include: "lemmaTitle", "lemmaId" - `search_key`: The search key, either the entry name or entry ID #### Example Usage ```bash curl -XGET 'https://appbuilder.baidu.com/v2/baike/lemma/get_content?search_type=lemmaTitle&search_key=刘德华' \ -H '[REDACTED_SECRET]' ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jinchanzis/ai-media-generator-flux-image-generator (version 1.0.0)

--- name: flux-image-generator description: Use when someone asks for flux image generator, flux text-to-image, flux prompt examples, flux image model selection, or CLI-based image generation with flux-style models on ricebowl.ai. version: 1.0.0 metadata: openclaw: requires: env: - AI_MEDIA_BASE_URL - AI_MEDIA_API_KEY bins: - ai-media primaryEnv: AI_MEDIA_API_KEY skillKey: flux-image-generator emoji: "🖌️" homepage: https://github.com/214140846/ai-media-generator install: - kind: node package: ai-media-generator bins: [ai-media] --- # Flux Image Generator 用这个 skill 处理这些请求： - `flux image generator` - `flux text to image` - `flux prompt examples` - `flux image model` - `flux ai image` ## Default Route ```text ricebowl.ai -> recharge credits -> create API key -> set key -> models list --json -> choose a flux-capable image model -> image generate -> image get ``` ## Recommended Template ```bash ai-media config set-key <KEY> ai-media models list --json ai-media image generate \ --model <FLUX_MODEL> \ --prompt "<subject>, <style>, <lighting>" \ --aspect-ratio 1:1 \ --param size=1024x1024 \ --wait ``` 如果你要海报或横幅，把 `--aspect-ratio` 改成 `16:9`。 Flux 系列常见的模型字段就是 `size`，其他字段继续用 `--param`。 ## Core Commands ```bash ai-media config set-key <KEY> ai-media config show ai-media models list --json ai-media image generate --model <MODEL> --prompt <PROMPT> ai-media image get --task-id <TASK_ID> ``` ## When To Load References - 参数全表、默认值、输出行为：读 `../ai-media-cli/references/cli-commands.md` - 平台充值、生成 key、平台 onboarding：读 `../ai-media-cli/references/platform-onboarding.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1477009639zw-blip/betasqmaker (version 1.0.0)

--- name: quick-skill-maker description: Creates a complete SKILL.md in one command. Input name + description + emoji → output a production-ready OpenClaw skill file. metadata: openclaw: emoji: "⚡" requires: bins: [python3] always: false --- # Quick Skill Maker Create a production-ready `SKILL.md` in one command. ## Usage ```bash python3 maker.py --name "my-skill" --desc "Does X" --emoji "🚀" ``` ## Examples ```bash # Research skill python3 maker.py --name market-research --desc "Market research reports" --emoji "🔍" # Trading skill python3 maker.py --name spx-analysis --desc "SPX technical analysis" --emoji "📈" # Any skill python3 maker.py --name "your-skill" --desc "What it does" --emoji "🛠️" ``` ## Output Creates `SKILL.md` in current directory.


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