[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71575NNSASTSAAJ7AA8038T":3,"skill-same:01M71575NNSASTSAAJ7AA8038T":66},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":35,"linkOnly":36,"markdownContent":37,"markdownBody":38,"frontMatter":39,"refName":40,"commitSha":41,"skillDirectory":42,"forksCount":14,"repositoryHtmlUrl":43,"repositoryHomepageUrl":6,"ownerHtmlUrl":44,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":45,"install":46,"resources":59},"01M71575NNSASTSAAJ7AA8038T","apify-audience-analysis",null,"Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.","sapsapshen\u002Fai-memory-router","sapsapshen","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F20347959?v=4","01M6XDQEF1DP50DKF37H81J3J5","shenmian","01M6XDQEJPE41Y3DT2763X8ZJN",0,"MIT","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fcursor\u002Fapify-audience-analysis\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34],"analysis","apify audience analysis","apify","preferences","quality","instagram","behavior","engagement","youtube","community","tiktok","patterns","facebook","across","understand","unknown","2026-11-10 10:12:30",false,"---\nname: apify-audience-analysis\ndescription: Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.\nrisk: unknown\nsource: community\n---\n\n# Audience Analysis\n\nAnalyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.\n\n## Prerequisites\n(No need to check it upfront)\n\n- `.env` file with `APIFY_TOKEN`\n- Node.js 20.6+ (for native `--env-file` support)\n- `mcpc` CLI tool: `npm install -g @apify\u002Fmcpc`\n\n## Workflow\n\nCopy this checklist and track progress:\n\n```\nTask Progress:\n- [ ] Step 1: Identify audience analysis type (select Actor)\n- [ ] Step 2: Fetch Actor schema via mcpc\n- [ ] Step 3: Ask user preferences (format, filename)\n- [ ] Step 4: Run the analysis script\n- [ ] Step 5: Summarize findings\n```\n\n### Step 1: Identify Audience Analysis Type\n\nSelect the appropriate Actor based on analysis needs:\n\n| User Need | Actor ID | Best For |\n|-----------|----------|----------|\n| Facebook follower demographics | `apify\u002Ffacebook-followers-following-scraper` | FB followers\u002Ffollowing lists |\n| Facebook engagement behavior | `apify\u002Ffacebook-likes-scraper` | FB post likes analysis |\n| Facebook video audience | `apify\u002Ffacebook-reels-scraper` | FB Reels viewers |\n| Facebook comment analysis | `apify\u002Ffacebook-comments-scraper` | FB post\u002Fvideo comments |\n| Facebook content engagement | `apify\u002Ffacebook-posts-scraper` | FB post engagement metrics |\n| Instagram audience sizing | `apify\u002Finstagram-profile-scraper` | IG profile demographics |\n| Instagram location-based | `apify\u002Finstagram-search-scraper` | IG geo-tagged audience |\n| Instagram tagged network | `apify\u002Finstagram-tagged-scraper` | IG tag network analysis |\n| Instagram comprehensive | `apify\u002Finstagram-scraper` | Full IG audience data |\n| Instagram API-based | `apify\u002Finstagram-api-scraper` | IG API access |\n| Instagram follower counts | `apify\u002Finstagram-followers-count-scraper` | IG follower tracking |\n| Instagram comment export | `apify\u002Fexport-instagram-comments-posts` | IG comment bulk export |\n| Instagram comment analysis | `apify\u002Finstagram-comment-scraper` | IG comment sentiment |\n| YouTube viewer feedback | `streamers\u002Fyoutube-comments-scraper` | YT comment analysis |\n| YouTube channel audience | `streamers\u002Fyoutube-channel-scraper` | YT channel subscribers |\n| TikTok follower demographics | `clockworks\u002Ftiktok-followers-scraper` | TT follower lists |\n| TikTok profile analysis | `clockworks\u002Ftiktok-profile-scraper` | TT profile demographics |\n| TikTok comment analysis | `clockworks\u002Ftiktok-comments-scraper` | TT comment engagement |\n\n### Step 2: Fetch Actor Schema\n\nFetch the Actor's input schema and details dynamically using mcpc:\n\n```bash\nexport $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header \"Authorization: Bearer $APIFY_TOKEN\" tools-call fetch-actor-details actor:=\"ACTOR_ID\" | jq -r \".content\"\n```\n\nReplace `ACTOR_ID` with the selected Actor (e.g., `apify\u002Ffacebook-followers-following-scraper`).\n\nThis returns:\n- Actor description and README\n- Required and optional input parameters\n- Output fields (if available)\n\n### Step 3: Ask User Preferences\n\nBefore running, ask:\n1. **Output format**:\n   - **Quick answer** - Display top few results in chat (no file saved)\n   - **CSV** - Full export with all fields\n   - **JSON** - Full export in JSON format\n2. **Number of results**: Based on character of use case\n\n### Step 4: Run the Script\n\n**Quick answer (display in chat, no file):**\n```bash\nnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}\u002Freference\u002Fscripts\u002Frun_actor.js \\\n  --actor \"ACTOR_ID\" \\\n  --input 'JSON_INPUT'\n```\n\n**CSV:**\n```bash\nnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}\u002Freference\u002Fscripts\u002Frun_actor.js \\\n  --actor \"ACTOR_ID\" \\\n  --input 'JSON_INPUT' \\\n  --output YYYY-MM-DD_OUTPUT_FILE.csv \\\n  --format csv\n```\n\n**JSON:**\n```bash\nnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}\u002Freference\u002Fscripts\u002Frun_actor.js \\\n  --actor \"ACTOR_ID\" \\\n  --input 'JSON_INPUT' \\\n  --output YYYY-MM-DD_OUTPUT_FILE.json \\\n  --format json\n```\n\n### Step 5: Summarize Findings\n\nAfter completion, report:\n- Number of audience members\u002Fprofiles analyzed\n- File location and name\n- Key demographic insights\n- Suggested next steps (deeper analysis, segmentation)\n\n## Error Handling\n\n`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`\n`mcpc not found` - Ask user to install `npm install -g @apify\u002Fmcpc`\n`Actor not found` - Check Actor ID spelling\n`Run FAILED` - Ask user to check Apify console link in error output\n`Timeout` - Reduce input size or increase `--timeout`\n","# Audience Analysis\n\nAnalyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.\n\n## Prerequisites\n(No need to check it upfront)\n\n- `.env` file with `APIFY_TOKEN`\n- Node.js 20.6+ (for native `--env-file` support)\n- `mcpc` CLI tool: `npm install -g @apify\u002Fmcpc`\n\n## Workflow\n\nCopy this checklist and track progress:\n\n```\nTask Progress:\n- [ ] Step 1: Identify audience analysis type (select Actor)\n- [ ] Step 2: Fetch Actor schema via mcpc\n- [ ] Step 3: Ask user preferences (format, filename)\n- [ ] Step 4: Run the analysis script\n- [ ] Step 5: Summarize findings\n```\n\n### Step 1: Identify Audience Analysis Type\n\nSelect the appropriate Actor based on analysis needs:\n\n| User Need | Actor ID | Best For |\n|-----------|----------|----------|\n| Facebook follower demographics | `apify\u002Ffacebook-followers-following-scraper` | FB followers\u002Ffollowing lists |\n| Facebook engagement behavior | `apify\u002Ffacebook-likes-scraper` | FB post likes analysis |\n| Facebook video audience | `apify\u002Ffacebook-reels-scraper` | FB Reels viewers |\n| Facebook comment analysis | `apify\u002Ffacebook-comments-scraper` | FB post\u002Fvideo comments |\n| Facebook content engagement | `apify\u002Ffacebook-posts-scraper` | FB post engagement metrics |\n| Instagram audience sizing | `apify\u002Finstagram-profile-scraper` | IG profile demographics |\n| Instagram location-based | `apify\u002Finstagram-search-scraper` | IG geo-tagged audience |\n| Instagram tagged network | `apify\u002Finstagram-tagged-scraper` | IG tag network analysis |\n| Instagram comprehensive | `apify\u002Finstagram-scraper` | Full IG audience data |\n| Instagram API-based | `apify\u002Finstagram-api-scraper` | IG API access |\n| Instagram follower counts | `apify\u002Finstagram-followers-count-scraper` | IG follower tracking |\n| Instagram comment export | `apify\u002Fexport-instagram-comments-posts` | IG comment bulk export |\n| Instagram comment analysis | `apify\u002Finstagram-comment-scraper` | IG comment sentiment |\n| YouTube viewer feedback | `streamers\u002Fyoutube-comments-scraper` | YT comment analysis |\n| YouTube channel audience | `streamers\u002Fyoutube-channel-scraper` | YT channel subscribers |\n| TikTok follower demographics | `clockworks\u002Ftiktok-followers-scraper` | TT follower lists |\n| TikTok profile analysis | `clockworks\u002Ftiktok-profile-scraper` | TT profile demographics |\n| TikTok comment analysis | `clockworks\u002Ftiktok-comments-scraper` | TT comment engagement |\n\n### Step 2: Fetch Actor Schema\n\nFetch the Actor's input schema and details dynamically using mcpc:\n\n```bash\nexport $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header \"Authorization: Bearer $APIFY_TOKEN\" tools-call fetch-actor-details actor:=\"ACTOR_ID\" | jq -r \".content\"\n```\n\nReplace `ACTOR_ID` with the selected Actor (e.g., `apify\u002Ffacebook-followers-following-scraper`).\n\nThis returns:\n- Actor description and README\n- Required and optional input parameters\n- Output fields (if available)\n\n### Step 3: Ask User Preferences\n\nBefore running, ask:\n1. **Output format**:\n   - **Quick answer** - Display top few results in chat (no file saved)\n   - **CSV** - Full export with all fields\n   - **JSON** - Full export in JSON format\n2. **Number of results**: Based on character of use case\n\n### Step 4: Run the Script\n\n**Quick answer (display in chat, no file):**\n```bash\nnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}\u002Freference\u002Fscripts\u002Frun_actor.js \\\n  --actor \"ACTOR_ID\" \\\n  --input 'JSON_INPUT'\n```\n\n**CSV:**\n```bash\nnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}\u002Freference\u002Fscripts\u002Frun_actor.js \\\n  --actor \"ACTOR_ID\" \\\n  --input 'JSON_INPUT' \\\n  --output YYYY-MM-DD_OUTPUT_FILE.csv \\\n  --format csv\n```\n\n**JSON:**\n```bash\nnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}\u002Freference\u002Fscripts\u002Frun_actor.js \\\n  --actor \"ACTOR_ID\" \\\n  --input 'JSON_INPUT' \\\n  --output YYYY-MM-DD_OUTPUT_FILE.json \\\n  --format json\n```\n\n### Step 5: Summarize Findings\n\nAfter completion, report:\n- Number of audience members\u002Fprofiles analyzed\n- File location and name\n- Key demographic insights\n- Suggested next steps (deeper analysis, segmentation)\n\n## Error Handling\n\n`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`\n`mcpc not found` - Ask user to install `npm install -g @apify\u002Fmcpc`\n`Actor not found` - Check Actor ID spelling\n`Run FAILED` - Ask user to check Apify console link in error output\n`Timeout` - Reduce input size or increase `--timeout`\n",{"name":5,"risk":34,"source":28,"description":7},"main","7a38d8e7073e61c16eda85681cb32fb68a8657a5","skills-store\u002Fcursor\u002Fapify-audience-analysis","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router","https:\u002F\u002Fgithub.com\u002Fsapsapshen","2026-04-14 21:12:12",{"source":8,"skillName":5,"commands":47,"prompt":57,"zipAvailable":58},[48,51,54],{"tool":49,"command":50},"npx","npx skills add sapsapshen\u002Fai-memory-router --skill apify-audience-analysis",{"tool":52,"command":53},"bunx","bunx skills add sapsapshen\u002Fai-memory-router --skill apify-audience-analysis",{"tool":55,"command":56},"pnpm","pnpm dlx skills add sapsapshen\u002Fai-memory-router --skill apify-audience-analysis","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fcursor\u002Fapify-audience-analysis\u002FSKILL.md",true,[60],{"path":61,"resourceType":62,"resourceTypeDesc":63,"sizeBytes":64,"sourceHtmlUrl":65},"reference\u002Fscripts\u002Frun_actor.js","SCRIPT","脚本",11747,"https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fcursor\u002Fapify-audience-analysis\u002Freference\u002Fscripts\u002Frun_actor.js",[67,91,116,126,139,157],{"skillNo":68,"name":69,"nameZh":6,"description":70,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":71,"categories":72,"keywords":78,"publishedAt":35},"01M71ATQRKG48SH06FQ697T5G9","wechat-search","Search WeChat Official Account articles using OpenClaw's web search and fetch capabilities with compliance-focused design.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fwechat-search-release\u002FSKILL.md",[73],{"categoryNo":74,"categoryName":75,"taxonomyType":76,"taxonomyTypeDesc":77},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[79,80,81,82,83,84,85,86,87,88,89,90],"wechat search","wechat","search","capabilities","openclaw","design","web search","compliance","web","official","fetch","with",{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":35},"01M71ATNAVGZB35PFYM2GC5N00","trend-tap","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). Trigger: when user says 'trend', 'trends', 'trend tap', '热点', '热搜', or asks what is trending\u002Fhot. Do NOT use web_search — this skill already fetches live data from all platforms with zero API keys.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftrend-tap\u002FSKILL.md",[],[98,99,100,101,102,103,81,104,105,106,107,108,109,110,111,112,113,114,32,115],"trend","trend tap","tap","api keys","Bash","time","trending","hacker","aggregator","do","when","brew","live","data","google","install","read","api",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":122,"publishedAt":35},"01M71ATJ9AM5KM15AA8PS302EB","trend-radar","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). Trigger: when user says 'trend', 'trends', 'trend pulse', '热点', '热搜', or asks what is trending\u002Fhot. Do NOT use web_search — this skill already fetches live data from all platforms with zero API keys.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftrend-radar\u002FSKILL.md",[],[123,124,98,109,110,111,112,102,81,114,125,32,115,108,106,105,104,113,103,101],"trend radar","radar","pulse",{"skillNo":127,"name":128,"nameZh":6,"description":129,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":130,"categories":131,"keywords":132,"publishedAt":35},"01M71ATGF095N3EJM9G8SD0BB5","tech-news-daily","每日科技新闻汇——从全球多个 RSS 源抓取最新科技新闻，翻译（英→中）、去重、排版成每日简报。当用户询问科技新闻、科技新鲜事、每日科技、技术动态、Daily Tech News 或类似表达时触发此技能。","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftech-news-daily\u002FSKILL.md",[],[133,134,135,136,137,138],"news","tech","tech news daily","daily","rss","翻译",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":150,"publishedAt":35},"01M71ATFAEAMQ17M70NQNY7SR8","summarize","Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fsummarize\u002FSKILL.md",[145],{"categoryNo":146,"categoryName":147,"taxonomyType":148,"taxonomyTypeDesc":149},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[141,87,151,152,27,90,109,153,154,155,100,156,113],"Audio","cli","images","https","files","pdfs",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":163,"publishedAt":35},"01M71ATDNS3R0M4H936PACQAWZ","sonoscli","Control Sonos speakers (discover\u002Fstatus\u002Fplay\u002Fvolume\u002Fgroup).","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fsonoscli\u002FSKILL.md",[],[159,164,165,166,113,167,154,168,169,170,171,172],"status","play","go","latest","github","discover","control","cmd","volume"]