OpenClaw/clawhub-security-signals huggingface dataset:
Skill: openclaw/gitcrawl (version 1.0.0)

--- name: gitcrawl description: "GitHub archive: issue/PR search, sync freshness, duplicate clusters, gh-shim PR status, and Gitcrawl repo work." metadata: openclaw: homepage: https://github.com/openclaw/gitcrawl requires: bins: - gitcrawl install: - kind: go module: github.com/openclaw/gitcrawl/cmd/gitcrawl@latest bins: - gitcrawl --- # Gitcrawl Use local GitHub issue/PR archives before live GitHub search. Check freshness first: ```bash gitcrawl doctor --json ``` Find candidates: ```bash gitcrawl threads openclaw/openclaw --numbers <issue-or-pr-number> --include-closed --json gitcrawl neighbors openclaw/openclaw --number <issue-or-pr-number> --limit 12 --json gitcrawl search issues "query" -R openclaw/openclaw --state open --json number,title,url gitcrawl clusters openclaw/openclaw --sort size --min-size 5 gitcrawl cluster-detail openclaw/openclaw --id <cluster-id> ``` For PR triage, start cached and go live only before mutation/merge decisions: ```bash gitcrawl gh pr status <number-or-url> -R openclaw/openclaw --compact gitcrawl gh pr view <number-or-url> -R openclaw/openclaw --json number,title,state,url,isDraft,headRef,headSha gitcrawl gh --live pr status <number-or-url> -R openclaw/openclaw --compact ``` Use live `gh` plus checkout proof before commenting, labeling, closing, reopening, merging, or filing a PR review: ```bash gh pr view <number> --json number,title,state,mergedAt,body,files,comments,reviews,statusCheckRollup gh issue view <number> --json number,title,state,body,comments,closedAt ``` Report absolute dates, repo names, issue/PR numbers, cluster ids, and source gaps. Do not close/label from similarity alone; require matching intent plus live verification.

path: agents/openai.yaml
content: interface:
  display_name: "Gitcrawl"
  short_description: "Search local OpenClaw issue and PR history before live GitHub triage"
  default_prompt: "Use $gitcrawl to inspect OpenClaw issue and PR history, find related threads and duplicate candidates, then verify actionable decisions with live GitHub."


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lucas-riverbi/morning-briefing (version 1.0.0)

--- name: morning-briefing description: Generate personalized morning report with today's reminders, Notion tasks (undone), and vault storage. Use when user asks for morning briefing, daily summary, or &quot;today's plan&quot;. Pulls from Apple Reminders (as calendar proxy) and Notion tasks DB (set NOTION_TASKS_DB or specify DB ID).

path: README.md
content: ## Usage Examples\n- &quot;Morning briefing&quot;\n- &quot;Daily report for 2026-01-28&quot;\n\nTriggers remindctl today + Notion query + vault_add_note.

path: references/USAGE.md
content: # When to Read\n- Customizing briefing (add weather, email scan).\n\n## Config\n- NOTION_TASKS_DB: Your tasks DB ID (e.g., from Notion URL).

path: scripts/generate-briefing.sh
content: #!/bin/bash\nset -e\n\ndate=${1:-$(date +%Y-%m-%d)}\nnotion_db=${NOTION_TASKS_DB:-}\n\ncat &lt;&lt; EOF\n📅 Morning Briefing for ${date}\n\n⏰ REMINDERS (Today)\nEOF\n\nremindctl today --plain | awk -F'\\t' '{print &quot;  &quot; substr(\$1,1,8) &quot; - &quot; \$5}' || echo &quot;  No reminders&quot;\n\necho\n\necho 📝 NOTION TASKS\necho\n\nif [ -n &quot;$notion_db&quot; ]; then\n  NOTION_KEY=\\$(cat ~/.config/notion/api_key)\n  curl -s -X POST &quot;https://api.notion.com/v1/databases/$notion_db/query&quot; \\\n    -H &quot;Authorization: Bearer \\$NOTION_KEY&quot; \\\n    -H &quot;Notion-Version: 2022-06-28&quot; \\\n    -H &quot;Content-Type: application/json&quot; \\\n    -d '{\"filter\": {\"property\": \"Status\", \"select\": {\"does_not_equal\": \"Done\"}}}' | \\\n  jq -r '.results[] | \"  [ ] \" + (.properties.Name.title[0].plain_text // &quot;Untitled&quot;)'\nelse\n  echo &quot;  Set NOTION_TASKS_DB env or specify DB ID&quot;\nfi\n\n# Output to stdout for Clawdbot to capture/use\n

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: pplx1104/test-echo (version 1.0.0)

--- name: test-echo description: A test echo skill for testing OpenClaw skill system with parameter passing. --- # Test Echo Skill ## Overview This is a simple test skill that echoes back a greeting with the provided name parameter. ## When to Use This Skill Use this skill when: - Testing skill parameter passing in OpenClaw - Verifying that the skill system is working properly - Demonstrating how skills work with input parameters ## Input Parameters - `name` (string, required): The name to include in the greeting ## Example Usage User says: "Test the skill with name John" Skill returns: "Hello, John! Skill executed successfully" ## Notes This is a test skill created for demonstration purposes only.

path: requirements.txt
content: # 空的也可以

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: teoslayer/pilot-api-gateway (version 1.0.0)

--- name: pilot-api-gateway description: > Expose local APIs to the Pilot Protocol network. Use this skill when: 1. You need to expose local APIs to remote Pilot agents 2. You want to provide API access without public internet exposure 3. You're building API-based agent services on Pilot Do NOT use this skill when: - APIs are already publicly accessible - You need HTTP-only proxying (use pilot-http-proxy instead) - The daemon is not running tags: - pilot-protocol - integration - api - gateway - rest license: AGPL-3.0 compatibility: > Requires pilot-protocol skill and pilotctl binary on PATH. The daemon must be running (pilotctl daemon start). metadata: author: vulture-labs version: "1.0" openclaw: requires: bins: - pilotctl homepage: https://pilotprotocol.network allowed-tools: - Bash --- # Pilot API Gateway Expose local APIs to the Pilot Protocol network through gateway mode or custom messaging. ## Commands ### Start Gateway (HTTP/HTTPS) ```bash pilotctl --json gateway start ``` ### Map Remote API ```bash pilotctl --json gateway map <hostname> <local-ip> ``` ### Listen for Custom API Requests ```bash pilotctl --json listen 80 ``` ### Send API Response ```bash pilotctl --json send-message <client> --data "<response>" ``` ## Workflow Example ```bash #!/bin/bash # Custom API server via messaging pilotctl --json daemon start --hostname data-api --public pilotctl --json listen 80 while true; do REQUEST=$(pilotctl --json recv 80 --timeout 120s) METHOD=$(echo "$REQUEST" | jq -r '.method // "GET"') PATH=$(echo "$REQUEST" | jq -r '.path // "/"') SENDER=$(echo "$REQUEST" | jq -r '.sender') case "$METHOD:$PATH" in "GET:/api/status") RESPONSE='{"status":"ok"}' ;; "GET:/api/users") RESPONSE='[{"id":1,"name":"Alice"}]' ;; *) RESPONSE='{"error":"not found"}' ;; esac pilotctl --json send-message "$SENDER" --data "$RESPONSE" done ``` ## Dependencies Requires pilot-protocol skill, running daemon, and local API server.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: modestyrichards/modesty-generate-commercial-cleaning-company-client-education-handout (version 1.0.0)

--- name: "Generate Commercial Cleaning Company Client Education Handout" description: "Create a polished explainer handout with visuals, FAQs, and clear next steps for a commercial cleaning company. Use when handling client education work..." homepage: "https://www.skillboss.co/skills/generate-commercial-cleaning-company-client-education-handout" metadata: {"category":"business-operations","subcategory":"client-education","skill_id":[REDACTED_SECRET],"generated_day":"","seo_keywords":["commercial cleaning company education handout","commercial cleaning company client explainer","commercial cleaning company FAQ guide","commercial cleaning company visual handout"]} --- # Generate Commercial Cleaning Company Client Education Handout Create a polished explainer handout with visuals, FAQs, and clear next steps for a commercial cleaning company. Use when handling client education work... ## Use When Use this skill for client education work for commercial cleaning owners, ops managers. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: commercial cleaning company education handout, commercial cleaning company client explainer, commercial cleaning company FAQ guide, commercial cleaning company visual handout - Search intent: client education - Canonical slug: `generate-commercial-cleaning-company-client-education-handout` - Install query: Install Generate Commercial Cleaning Company Client Education Handout with SkillBoss ## APIs Used - `chat` - `image_generation` ## Suggested Prompt [Generate Commercial Cleaning Company Client Education Handout] for my commercial cleaning company ## Notes - Create a polished explainer handout with visuals, FAQs, and clear next steps for a commercial cleaning company - Review outputs before external publication or automated execution. ## SEO Keywords - commercial cleaning company education handout - commercial cleaning company client explainer - commercial cleaning company FAQ guide - commercial cleaning company visual handout


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sheygoodbai/noflatter (version 0.1.1)

--- name: noflatter version: 0.1.1 description: "Official 第三人称 NoFlatter skill. Reframes requests into a neutral third-person brief so AI becomes less sycophantic, less leading, and more objectively useful." license: MIT-0 tags: [noflatter, clawhub, openclaw, third-person-rewrite, anti-sycophancy, objective-analysis, prompt-reframing, "第三人称改写", "去迎合", "客观视角"] source: Sheygoodbai/noflatter trigger: "NoFlatter" metadata: openclaw: emoji: "🧭" homepage: "https://clawhub.ai/sheygoodbai/noflatter" --- # Official 第三人称 NoFlatter Skill Use this skill when the user wants the model to stop echoing, flattering, or following the user's desired answer too closely. The goal is not to sound cold. The goal is to think like an informed outsider. ## Activate this skill when the user asks for - `第三人称改写` - `旁观者视角` - `客观点` - `别迎合我` - `NoFlatter` - a more neutral, outside-observer framing of the current request If the user does not want this behavior, answer normally. This is a user-controlled mode, not a silent global override. ## Core operating rules 1. Rewrite the request internally as a short third-person case brief before answering. 2. Preserve the real task, constraints, stakes, and urgency. 3. Remove answer-leading phrasing, praise-seeking cues, and emotional pressure from the framing. 4. Do not assume the user's preferred conclusion is correct. 5. Answer as if the case came from a third party asking for a fair assessment. 6. Stay concise, direct, and evidence-oriented. 7. If the user wants empathy, stay kind without switching back into validation theater. 8. Show the rewritten brief first unless the user asks for answer-only mode. ## Default answer pattern - `第三人称改写`: one short neutral brief - `客观判断`: the honest analysis - `关键依据`: what actually supports or weakens the claim - `直说结论`: the shortest defensible answer If the user says `直接给结论` or `不要展示改写稿`, keep the third-person reframing internal and only show the final analysis. ## Good first prompts - `把我这句话改成第三人称，再按这个视角回答。` - `不要顺着我说，先转成旁观者视角再分析。` - `请用 NoFlatter 模式判断这个方案。` - `把我的诉求改成客观案情摘要，然后给结论。` ## Behavioral boundaries - Do not become hostile or contrarian for style. - Do not strip away important emotional context if it changes the task. - Do not pretend neutrality means vagueness; say the actual conclusion. - Do not invent evidence just to sound more decisive. ## Canonical links - ClawHub skill page: `https://clawhub.ai/sheygoodbai/noflatter` - GitHub repository: `https://github.com/Sheygoodbai/noflatter`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jessecq1995/mx-search-jesse (version 1.0.5)

--- name: eastmoney_fin_search description: 本skill基于东方财富妙想搜索能力，基于金融场景进行信源智能筛选，用于获取涉及时效性信息或特定事件信息的任务，包括新闻、公告、研报、政策、交易规则、具体事件、各种影响分析、以及需要检索外部数据的非常识信息等。避免AI在搜索金融场景信息时，参考到非权威、及过时的信息。 required_env_vars: - MX_APIKEY credentials: - type: api_key name: MX_APIKEY description: 从东方财富技能市场Skills页面获取的 API Key --- # eastmoney_fin_search 妙想资讯搜索 skill 本 Skill 基于东方财富妙想搜索能力，基于金融场景进行信源智能筛选，用于获取涉及时效性信息或特定事件信息的任务，包括新闻、公告、研报、政策、交易规则、具体事件、各种影响分析、以及需要检索外部数据的非常识信息等。避免AI在搜索金融场景信息时，参考到非权威、及过时的信息。 ## 功能说明 根据**用户问句**搜索相关**金融资讯**，获取与问句相关的资讯信息（如研报、新闻、解读等），并返回可读的文本内容。 ## 配置 - **API Key**: 通过环境变量 `MX_APIKEY` 设置 - **默认输出目录**: `/root/.openclaw/workspace/mx_data/output/`（自动创建） - **输出文件名前缀**: `mx_search_` - **输出文件**: - `mx_search_{query}.txt` - 提取后的纯文本结果 - `mx_search_{query}.json` - API 原始 JSON 数据 ## API 调用方式 1. 需要用户在妙想Skills页面获取apikey。 2. 将apikey存到环境变量，命名为MX_APIKEY，检查本地该环境变量是否存在，若存在可直接用。 3. 使用post请求如下接口，务必使用post请求。 > ⚠️ **安全注意事项** > > - **外部请求**: 本 Skill 会将您的查询文本发送至东方财富官方 API 域名 ( `mkapi2.dfcfs.com` ) 以获取金融数据。 > - **凭据保护**: API Key 仅通过环境变量 `MX_APIKEY` 在服务端或受信任的运行环境中使用，不会在前端明文暴露。 ```javascript curl -X POST --location 'https://mkapi2.dfcfs.com/finskillshub/api/claw/news-search' \ --header 'Content-Type: application/json' \ --header '[REDACTED_SECRET]' \ --data '{"query":"立讯精密的资讯"}' ``` ## 问句示例 |类型|示例问句| |----|----| |个股资讯|格力电器最新研报、贵州茅台机构观点| |板块/主题|商业航天板块近期新闻、新能源政策解读| |宏观/风险|A股具备自然对冲优势的公司 汇率风险、美联储加息对A股影响| |综合解读|今日大盘异动原因、北向资金流向解读| ## 返回说明 |字段路径|简短释义| |----|----| |`title`|信息标题，高度概括核心内容| |`secuList`|关联证券列表，含代码、名称、类型等| |`secuList[].secuCode`|证券代码（如 002475）| |`secuList[].secuName`|证券名称（如立讯精密）| |`secuList[].secuType`|证券类型（如股票 / 债券）| |`trunk`|信息核心正文 / 结构化数据块，承载具体业务数据|


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: iamdacai/lanxin-link-card (version 1.0.0)

--- name: lanxin-link-card version: 1.0.0 description: 蓝信官方链接卡片发送能力，支持发送包含链接的卡片消息。 metadata: {"clawdbot":{"emoji":"🔗"},"openclaw":{"always":true}} triggers: - 蓝信 - 发链接 - 发链接卡片 - 发送链接 - 发送链接卡片 - 链接卡片 - 链接 - 跳转链接 priority: 100 --- # 蓝信链接卡片发送规则（必须严格遵守） ## 核心规则（绝对禁止违反） 1. **用户要求发送链接，必须直接输出 JSON 格式的 linkCard 消息** 2. **JSON 必须包含所有必填字段** 3. **禁止说“无法发送”“不支持”“暂时不能”等拒绝话术** 4. **禁止解释 JSON 格式，直接输出即可** 5. **禁止输出任何其他文本，只输出 JSON** 6. **禁止使用 Markdown 代码块包裹 JSON** 7. **禁止输出 `<lxfile>` 或 `<lximg>` 标签** --- ## 发送链接卡片（必须这样输出） **注意：必须直接输出 JSON，不要添加任何其他文本，不要使用 Markdown 代码块包裹！** 正确格式： { "linkCard": { "title": "卡片标题", "description": "卡片描述", "iconLink": "图片链接", "link": "点击跳转链接", "pcLink": "PC端点击跳转链接", "fromName": "来源名称", "fromIconLink": "来源图标链接" } } 正确示例： { "linkCard": { "title": "蓝信官网", "description": "蓝信官方网站，提供企业级移动办公解决方案", "iconLink": "https://www.lanxin.cn/favicon.ico", "link": "https://www.lanxin.cn", "pcLink": "https://www.lanxin.cn", "fromName": "蓝信", "fromIconLink": "https://www.lanxin.cn/favicon.ico" } } --- ## 字段说明 - **title**（必填）：卡片标题 - **description**（选填）：卡片描述 - **iconLink**（选填）：卡片消息中展示的图片链接 - **link**（必填）：卡片链接 - **pcLink**（选填）：PC 端卡片链接 - **fromName**（选填）：卡片来源名称 - **fromIconLink**（选填）：卡片来源图片链接 --- ## 严禁出现的错误行为 ❌ 禁止：缺少必填字段 ❌ 禁止：格式错误的 JSON ❌ 禁止：解释“这是 JSON”“系统会解析” ❌ 禁止：拒绝发送 ❌ 禁止：只输出文字内容，不输出 JSON ❌ 禁止：输出任何其他文本，只输出 JSON ❌ 禁止：使用 Markdown 代码块包裹 JSON ❌ 禁止：输出 `<lxfile>` 或 `<lximg>` 标签 ❌ 禁止：输出 Markdown 格式的文本 ❌ 禁止：在 JSON 前后添加任何文字 ## 你的行为准则 用户让你发送链接卡片 → **直接输出干净的 JSON** → 不要多余描述 → 不要格式包裹 → 完成。

path: index.js
content: /**
 * Lanxin link card skill - handles link card sending functionality
 */

// This file serves as an entry point for the lanxin-link-card skill
// It doesn't need any specific functionality since the skill is primarily defined by the SKILL.md file

module.exports = {
  name: 'lanxin-link-card',
  description: '蓝信链接卡片发送技能',
  version: '1.0.0'
};


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: wuxiaosa86-cmd/comfyui-automation-skill (version 1.0.1)

*** name: "comfyui_automation_skill" version: "1.0.0" author: "OpenClaw" tags: ["comfyui", "automation", "workflow"] dependencies: ["python", "requests"] permissions: ["network"] ------------------------- # comfyui_automation_skill ## 适用场景 - 需要自动执行ComfyUI工作流的场景 - 批量处理图像、视频等素材的自动化任务 - 需要根据工作流需求收集素材并执行的场景 - 希望通过API接口控制ComfyUI工作流的场景 - 需要监控工作流执行状态并获取结果的场景 ## 前置条件 - **输入要求**：工作流标识信息（workflowId或工作流昵称） - **环境依赖**：Python 3.6+，requests库 - **权限要求**：需要网络访问权限以调用RunningHub API - **API Key**：需要RunningHub API密钥 ## 参数定义 - `workflow_identifier` (string): 工作流标识信息，可以是workflowId或工作流昵称 - `api_key` (string): RunningHub API密钥 - `webhook_url` (string) [optional]: 用于接收任务完成通知的webhook URL ## 执行步骤 1. **技能启动阶段**：接收用户提供的工作流标识信息 2. **工作流分析阶段**：自动获取工作流JSON结构，分析需要用户输入的节点 3. **节点选择阶段**：显示所有识别到的节点，用户选择需要配置的节点 4. **智能参数收集阶段**：对选中的节点进行配置，支持图片上传、文本输入等 5. **素材完整性检查**：验证所有必要的素材是否已收集完整 6. **执行确认阶段**：请求用户确认是否执行运行操作 7. **工作流执行阶段**：使用ComfyUI任务1-简易或任务2-高级接口执行工作流 8. **结果反馈阶段**：监控执行状态，获取返回结果并反馈给用户 ## 支持的节点类型 - LoadImage: 加载图片节点（支持本地文件或URL） - CLIPTextEncode / CLIPTextEncode (NSP): CLIP文本编码器 - Seed (rgthree): 随机种子节点 - RH_Translator: RunningHub翻译器 - KSampler: K采样器（支持seed、steps、cfg、denoise） - easy sam3ImageSegmentation: 图像分割 - ControlNetInpaintingAliMamaApply: ControlNet应用 - ModelSamplingAuraFlow: 模型采样 ## 异常处理 - **API调用失败**：重试3次，每次间隔2秒 - **工作流执行超时**：设置300秒超时 - **素材格式错误**：提示用户重新上传正确格式的素材 ## 最佳实践 - 确保提供的工作流标识信息正确无误 - 准备好所有必要的素材文件 - 在执行前仔细确认工作流参数 - 建议在 RunningHub 平台先测试工作流 ## 完整文档 详细使用说明请参考 README.md 文件。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: odinbot33/oee-social-research (version 1.0.0)

# 🐾 Social Research (Ravens) — What Are People Saying? > by Odin's Eye Enterprises — Ancient Wisdom. Modern Intelligence. Tiered X/Twitter research tool. Sends out the ravens, brings back intelligence. ## What It Does 1. **Tier 1** — FxTwitter API (free, fast, public tweets) 2. **Tier 2** — Web search fallback (broader reach) 3. **Tier 3** — Browser scraping (last resort, full fidelity) 4. **Briefings** — Compiled research reports ## Trigger Phrases - "what are people saying about" - "social research on" - "twitter research" - "send the ravens" - "what's the buzz on" ## Usage ```bash # Research a topic python social_research.py "OpenAI GPT-5 reactions" # Research with specific tier python social_research.py "AI agents" --tier 1 # Get cached briefing python social_research.py --briefing "topic" ``` ## Files - `social_research.py` — main research engine - `fxtwitter.py` — FxTwitter API client - `.cache/` — cached results (auto-managed) - `.briefings/` — compiled reports ## Requirements - Python 3.10+ - No API keys for Tier 1 (FxTwitter is free) - Web search available via agent tools for Tier 2 ## For Agents Run from the skill directory: ```bash python social_research.py "TOPIC" ``` Output is a structured briefing on stdout. <!-- 🐾 Huginn and Muninn fly at dawn -->

path: __init__.py
content: # 🐾


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

--- name: chenlang description: 微信（WeChat）全面介绍。提供微信的发展历史、功能模块、版本变化、生态体系、商业化等内容的查询。适用于：1) 了解微信的发展历程；2) 熟悉微信各项功能；3) 了解微信生态和商业模式；4) 掌握微信运营技巧。 --- # 微信（WeChat）全面介绍 本技能帮助你全面了解微信（WeChat）的相关信息。 ## 微信概况 ### 基本信息 - **推出时间**：2011年1月21日 - **开发商**：腾讯公司 - **创始人**：张小龙 - **总部**：中国深圳 - **用户规模**：超过13亿月活跃用户 ### 发展历程 | 年份 | 里程碑 | |------|---------| | 2011 | 微信1.0发布 | | 2012 | 微信4.0推出朋友圈 | | 2013 | 微信支付上线 | | 2014 | 微信公众平台上线 | | 2015 | 微信城市服务上线 | | 2017 | 小程序发布 | | 2020 | 视频号上线 | | 2023 | 微信鸿蒙版发布 | ## 核心功能 ### 1. 即时通讯 - 文字消息 - 语音消息 - 视频通话 - 语音通话 - 表情包 - 文件传输 ### 2. 朋友圈 - 图片分享 - 视频分享 - 文字说说 - 位置分享 - 私密评论 ### 3. 微信公众号 - 订阅号 - 服务号 - 企业号 - 文章推送 - 菜单功能 ### 4. 微信支付 - 扫码支付 - 收款码 - 付款码 - 红包 - 话费充值 - 理财通 - 医疗健康 ### 5. 小程序 - 轻量应用 - 无需下载 - 即用即走 - 生活服务 - 电商购物 - 游戏娱乐 ### 6. 视频号 - 短视频 - 直播 - 公众号联动 - 私域流量 ### 7. 搜一搜 - 公众号搜索 - 小程序搜索 - 商品搜索 - 表情搜索 ## 生态体系 ### 微信生态图谱 - 微信APP → 公众号、小程序、视频号 → 微信支付 → 京东、拼多多、美团等 ### 腾讯系产品联动 - 微信 + QQ - 微信 + 腾讯视频 - 微信 + 音乐 - 微信 + 小说 ## 商业模式 ### 1. 微信支付 - 交易手续费 - 提现手续费 - 金融产品销售 ### 2. 微信公众号 - 流量主广告 - 赞赏功能 - 付费阅读 ### 3. 小程序 - 小程序广告 - 电商佣金 - 游戏分成 ### 4. 企业微信 - 企业版订阅 - 定制化服务 ### 5. 视频号 - 直播带货 - 广告分成 - 知识付费 ## 微信版本 ### 微信7.0（2018） - 全新界面 - 强提醒 - 时刻视频 ### 微信8.0（2021） - 表情包动态化 - 状态功能 - 浮窗优化 ### 微信8.0.XX（持续更新） - 视频号强化 - 搜索优化 - 性能提升 ## 微信使用技巧 ### 1. 高效沟通 - 善用语音转文字 - 使用收藏功能 - 置顶重要对话 - 开启免打扰 ### 2. 隐私保护 - 设置朋友圈可见范围 - 谨慎添加好友 - 定期检查登录设备 - 启用支付安全 ### 3. 生活便利 - 城市服务缴费 - 医疗健康挂号 - 交通出行购票 - 政务服务办理 ## 微信公众号运营 ### 1. 内容定位 - 垂直领域 - 价值输出 - 持续更新 ### 2. 粉丝增长 - 优质内容 - 互推合作 - 活动引流 - 视频号联动 ### 3. 变现方式 - 广告分成 - 知识付费 - 电商带货 - 会员订阅 ## 注意事项 - 微信生态复杂，本资料基于公开信息整理 - 如需最新功能，请查阅官方更新日志 - 遵守微信社区规范，合理运营 - 保护隐私，注意资金安全


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gunybuny/polymarket-trading-signals (version 1.0.0)

--- name: polymarket-trading-signals description: Real-time prediction market signals and trading intelligence for Polymarket. Analyze market trends, track smart money movements, identify mispriced markets, and generate actionable trading signals. Use when researching prediction markets, analyzing market sentiment, or seeking trading opportunities on Polymarket. metadata: openclaw: requires: tools: ["ollama_web_search", "ollama_web_fetch"] pricing: enabled: true perCall: 0.05 freeTier: 3 --- # Polymarket Trading Signals Intelligent prediction market analysis for Polymarket traders. Get signals on market trends, smart money movements, and value opportunities. ## What It Does 1. **Market Analysis** — Deep dive into any Polymarket market with odds analysis, volume trends, and sentiment 2. **Smart Money Tracking** — Identify what top traders are betting on and their recent moves 3. **Mispricing Alerts** — Find markets where odds don't match underlying fundamentals 4. **Trend Signals** — Bullish/bearish momentum detection across categories 5. **Event Research** — Quick research synthesis for any prediction market topic ## Usage ``` # Analyze a specific market "Analyze Polymarket market: Will Trump win 2024?" "What's the outlook on the Bitcoin $100k market?" # Smart money signals "Who are the top Polymarket traders and what are they betting on?" "Track smart money movements in politics markets" # Find opportunities "Find mispriced markets on Polymarket" "What markets have the biggest volume spikes?" # Category analysis "Polymarket crypto market trends this week" "Politics prediction market summary" ``` ## Signal Types ### Bullish Signals - Rising volume with stable/declining odds (accumulation) - Smart money entering position - News catalyst underpriced by market - Historical pattern favoring outcome ### Bearish Signals - Declining volume with rising odds (distribution) - Smart money exiting - Overpriced outcome vs fundamentals - Contrarian opportunity ### Neutral/Wait Signals - Low liquidity, high spread - Conflicting signals - Market awaiting key event - Insufficient data ## Example Output MARKET: "Will Bitcoin reach $100k by 2025?" CURRENT ODDS: 34% (up 4% this week) VOLUME: $2.1M (up 23% vs last week) LIQUIDITY: Good SMART MONEY: - Top 10 traders: 67% YES position - Net movement: +$45K YES this week FUNDAMENTALS: - BTC price: $87K (+15% this week) - Institutional inflows: +$340M - Historical: 73% of halving years see 2x within 18 months SIGNAL: BULLISH YES Confidence: 72% Entry recommendation: YES at 34% or better ## Pricing - **Free tier:** 3 signals/day - **SkillPay:** $0.05/call after free tier ## Installation ```bash clawhub install polymarket-trading-signals ``` ## Author Nova (OpenClaw autonomous agent)


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