[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6PZ8KRDFTHXMPP9VY4WDZ08":3,"skill-same:01M6PZ8KRDFTHXMPP9VY4WDZ08":106},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":36,"publishedAt":55,"linkOnly":56,"markdownContent":57,"markdownBody":58,"frontMatter":59,"refName":72,"commitSha":73,"skillDirectory":74,"forksCount":75,"repositoryHtmlUrl":76,"repositoryHomepageUrl":6,"ownerHtmlUrl":77,"ownerBlogUrl":6,"ownerDescription":78,"updatedAt":79,"install":80,"resources":93},"01M6PZ8KRDFTHXMPP9VY4WDZ08","supermetrics",null,"Official Supermetrics skill. Query marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn. Requires API key.","Kernel8901\u002Fai-agent-skills-classification","Kernel8901","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F72647553?v=4","01M6KV388J2H5PNC8D8P940BJD","01M6KV38CS5B3AY63RKZB410YM",7,"MIT","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F市场营销与销售\u002Fsupermetrics-openclawd\u002FSKILL.md",[17,22,25,28,33],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":26,"categoryName":27,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":29,"categoryName":30,"taxonomyType":31,"taxonomyTypeDesc":32},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",{"categoryNo":34,"categoryName":35,"taxonomyType":31,"taxonomyTypeDesc":32},"01JBSEEDCAT000000000000035","市场营销",[5,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54],"api","meta ads","facebook","query","google ads","campaign","linkedin","ads","marketing","google","google analytics","Meta","data","metrics","report","official","analytics","performance","2026-11-10 10:12:30",false,"---\nname: supermetrics\ndescription: \"Official Supermetrics skill. Query marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn. Requires API key.\"\nversion: 1.0.1\ntriggers:\n  - marketing data\n  - supermetrics\n  - analytics\n  - ads performance\n  - campaign metrics\n  - google analytics\n  - meta ads\n  - facebook ads\n  - google ads\n  - linkedin ads\n  - marketing report\nauthor: supermetrics\ntags: [marketing, analytics, supermetrics, api, data]\nrequires:\n  env:\n    - SUPERMETRICS_API_KEY\n---\n\n# Supermetrics Marketing Data\n\nQuery marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn.\n\n## Usage\n\nImport the helper module:\n\n```python\nfrom supermetrics import (\n    discover_sources,\n    discover_accounts,\n    discover_fields,\n    query_data,\n    get_results,\n    get_today,\n    search,\n    health,\n)\n```\n\n## Functions\n\n### discover_sources()\n\nList all available marketing platforms.\n\n```python\nresult = discover_sources()\nfor src in result['data']['sources']:\n    print(f\"{src['id']}: {src['name']}\")\n```\n\n### discover_accounts(ds_id)\n\nGet connected accounts for a data source.\n\n**Common data source IDs:**\n| ID | Platform |\n|----|----------|\n| FA | Meta Ads (Facebook) |\n| AW | Google Ads |\n| GAWA | Google Analytics |\n| GA4 | Google Analytics 4 |\n| LI | LinkedIn Ads |\n| AC | Microsoft Advertising (Bing) |\n\n```python\nresult = discover_accounts(\"GAWA\")\nfor acc in result['data']['accounts']:\n    print(f\"{acc['account_id']}: {acc['account_name']}\")\n```\n\n### discover_fields(ds_id, field_type=None)\n\nGet available metrics and dimensions.\n\n```python\n# Get all fields\nresult = discover_fields(\"GAWA\")\n\n# Get only metrics\nresult = discover_fields(\"GAWA\", \"metric\")\n\n# Get only dimensions\nresult = discover_fields(\"GAWA\", \"dimension\")\n```\n\n### query_data(...)\n\nExecute a marketing data query. Returns schedule_id for async retrieval.\n\n```python\nresult = query_data(\n    ds_id=\"GAWA\",\n    ds_accounts=\"123456789\",\n    fields=[\"date\", \"sessions\", \"pageviews\", \"users\"],\n    date_range_type=\"last_7_days\"\n)\nschedule_id = result['data']['schedule_id']\n```\n\n**Parameters:**\n- `ds_id` (required): Data source ID\n- `ds_accounts` (required): Account ID(s) from discover_accounts()\n- `fields` (required): Field ID(s) from discover_fields()\n- `date_range_type`: `last_7_days`, `last_30_days`, `last_3_months`, `custom`\n- `start_date`, `end_date`: For custom date range (YYYY-MM-DD)\n- `filters`: Filter expression (e.g., `\"country == United States\"`)\n- `timezone`: IANA timezone (e.g., `\"America\u002FNew_York\"`)\n\n**Filter operators:**\n- `==`, `!=` - equals, not equals\n- `>`, `>=`, `\u003C`, `\u003C=` - comparisons\n- `=@`, `!@` - contains, does not contain\n- `=~`, `!~` - regex match\n\n### get_results(schedule_id)\n\nRetrieve query results.\n\n```python\nresult = get_results(schedule_id)\nfor row in result['data']['data']:\n    print(row)\n```\n\n### get_today()\n\nGet current UTC date for date calculations.\n\n```python\nresult = get_today()\nprint(result['data']['date'])  # \"2026-02-03\"\n```\n\n### search(query)\n\nSearch across Supermetrics resources for guidance and suggestions.\n\n```python\nresult = search(\"facebook ads metrics\")\nprint(result['data'])\n```\n\n### health()\n\nCheck Supermetrics server health status.\n\n```python\nresult = health()\nprint(result['data']['status'])  # \"healthy\"\n```\n\n## Workflow Example\n\n```python\nfrom supermetrics import (\n    discover_accounts,\n    discover_fields,\n    query_data,\n    get_results,\n)\n\n# 1. Find accounts\naccounts = discover_accounts(\"GAWA\")\naccount_id = accounts['data']['accounts'][0]['account_id']\n\n# 2. See available fields\nfields = discover_fields(\"GAWA\", \"metric\")\nprint([f['id'] for f in fields['data']['metrics'][:5]])\n\n# 3. Query data\nquery = query_data(\n    ds_id=\"GAWA\",\n    ds_accounts=account_id,\n    fields=[\"date\", \"sessions\", \"users\", \"pageviews\"],\n    date_range_type=\"last_7_days\"\n)\n\n# 4. Get results\ndata = get_results(query['data']['schedule_id'])\nfor row in data['data']['data']:\n    print(row)\n```\n\n## Response Format\n\nAll functions return:\n\n```python\n{\"success\": True, \"data\": {...}}  # Success\n{\"success\": False, \"error\": \"...\"}  # Error\n```\n","# Supermetrics Marketing Data\n\nQuery marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn.\n\n## Usage\n\nImport the helper module:\n\n```python\nfrom supermetrics import (\n    discover_sources,\n    discover_accounts,\n    discover_fields,\n    query_data,\n    get_results,\n    get_today,\n    search,\n    health,\n)\n```\n\n## Functions\n\n### discover_sources()\n\nList all available marketing platforms.\n\n```python\nresult = discover_sources()\nfor src in result['data']['sources']:\n    print(f\"{src['id']}: {src['name']}\")\n```\n\n### discover_accounts(ds_id)\n\nGet connected accounts for a data source.\n\n**Common data source IDs:**\n| ID | Platform |\n|----|----------|\n| FA | Meta Ads (Facebook) |\n| AW | Google Ads |\n| GAWA | Google Analytics |\n| GA4 | Google Analytics 4 |\n| LI | LinkedIn Ads |\n| AC | Microsoft Advertising (Bing) |\n\n```python\nresult = discover_accounts(\"GAWA\")\nfor acc in result['data']['accounts']:\n    print(f\"{acc['account_id']}: {acc['account_name']}\")\n```\n\n### discover_fields(ds_id, field_type=None)\n\nGet available metrics and dimensions.\n\n```python\n# Get all fields\nresult = discover_fields(\"GAWA\")\n\n# Get only metrics\nresult = discover_fields(\"GAWA\", \"metric\")\n\n# Get only dimensions\nresult = discover_fields(\"GAWA\", \"dimension\")\n```\n\n### query_data(...)\n\nExecute a marketing data query. Returns schedule_id for async retrieval.\n\n```python\nresult = query_data(\n    ds_id=\"GAWA\",\n    ds_accounts=\"123456789\",\n    fields=[\"date\", \"sessions\", \"pageviews\", \"users\"],\n    date_range_type=\"last_7_days\"\n)\nschedule_id = result['data']['schedule_id']\n```\n\n**Parameters:**\n- `ds_id` (required): Data source ID\n- `ds_accounts` (required): Account ID(s) from discover_accounts()\n- `fields` (required): Field ID(s) from discover_fields()\n- `date_range_type`: `last_7_days`, `last_30_days`, `last_3_months`, `custom`\n- `start_date`, `end_date`: For custom date range (YYYY-MM-DD)\n- `filters`: Filter expression (e.g., `\"country == United States\"`)\n- `timezone`: IANA timezone (e.g., `\"America\u002FNew_York\"`)\n\n**Filter operators:**\n- `==`, `!=` - equals, not equals\n- `>`, `>=`, `\u003C`, `\u003C=` - comparisons\n- `=@`, `!@` - contains, does not contain\n- `=~`, `!~` - regex match\n\n### get_results(schedule_id)\n\nRetrieve query results.\n\n```python\nresult = get_results(schedule_id)\nfor row in result['data']['data']:\n    print(row)\n```\n\n### get_today()\n\nGet current UTC date for date calculations.\n\n```python\nresult = get_today()\nprint(result['data']['date'])  # \"2026-02-03\"\n```\n\n### search(query)\n\nSearch across Supermetrics resources for guidance and suggestions.\n\n```python\nresult = search(\"facebook ads metrics\")\nprint(result['data'])\n```\n\n### health()\n\nCheck Supermetrics server health status.\n\n```python\nresult = health()\nprint(result['data']['status'])  # \"healthy\"\n```\n\n## Workflow Example\n\n```python\nfrom supermetrics import (\n    discover_accounts,\n    discover_fields,\n    query_data,\n    get_results,\n)\n\n# 1. Find accounts\naccounts = discover_accounts(\"GAWA\")\naccount_id = accounts['data']['accounts'][0]['account_id']\n\n# 2. See available fields\nfields = discover_fields(\"GAWA\", \"metric\")\nprint([f['id'] for f in fields['data']['metrics'][:5]])\n\n# 3. Query data\nquery = query_data(\n    ds_id=\"GAWA\",\n    ds_accounts=account_id,\n    fields=[\"date\", \"sessions\", \"users\", \"pageviews\"],\n    date_range_type=\"last_7_days\"\n)\n\n# 4. Get results\ndata = get_results(query['data']['schedule_id'])\nfor row in data['data']['data']:\n    print(row)\n```\n\n## Response Format\n\nAll functions return:\n\n```python\n{\"success\": True, \"data\": {...}}  # Success\n{\"success\": False, \"error\": \"...\"}  # Error\n```\n",{"name":5,"tags":60,"author":5,"version":61,"requires":62,"triggers":65,"description":7},[45,53,5,37,49],"1.0.1",{"env":63},[64],"SUPERMETRICS_API_KEY",[66,5,53,67,68,47,38,69,41,70,71],"marketing data","ads performance","campaign metrics","facebook ads","linkedin ads","marketing report","main","f4cb2d49f7667e79ef7804f50396d5aaffdf1f56","市场营销与销售\u002Fsupermetrics-openclawd",1,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification","https:\u002F\u002Fgithub.com\u002FKernel8901","a little little little dobe in life but science geek","2026-04-05 16:43:56",{"source":8,"skillName":5,"commands":81,"prompt":91,"zipAvailable":92},[82,85,88],{"tool":83,"command":84},"npx","npx skills add Kernel8901\u002Fai-agent-skills-classification --skill supermetrics",{"tool":86,"command":87},"bunx","bunx skills add Kernel8901\u002Fai-agent-skills-classification --skill supermetrics",{"tool":89,"command":90},"pnpm","pnpm dlx skills add Kernel8901\u002Fai-agent-skills-classification --skill supermetrics","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F市场营销与销售\u002Fsupermetrics-openclawd\u002FSKILL.md",true,[94,100],{"path":95,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":98,"sourceHtmlUrl":99},"_meta.json","REFERENCE","参考文档",471,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F市场营销与销售\u002Fsupermetrics-openclawd\u002F_meta.json",{"path":101,"resourceType":102,"resourceTypeDesc":103,"sizeBytes":104,"sourceHtmlUrl":105},"supermetrics.py","SCRIPT","脚本",7072,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F市场营销与销售\u002Fsupermetrics-openclawd\u002Fsupermetrics.py",[107,131,159,170,180,210],{"skillNo":108,"name":109,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":111,"categories":112,"keywords":113,"publishedAt":55},"01M6Q5R6WZ06RRB9RQTW54B34B","zyfai","Earn yield on any Ethereum wallet on Base, Arbitrum, and Plasma. Use when a user wants passive DeFi yield on their funds. Deploys a non-custodial subaccount (Safe) linked to their EOA, enables automated yield optimization, and lets them deposit\u002Fwithdraw anytime.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzyfai-sdk\u002FSKILL.md",[],[109,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130],"safe","ethereum","defi","Optimization","user","use","Wallet","base","deposit","withdraw","yield","arbitrum","non-custodial","passive","defi yield","earn","yield optimization",{"skillNo":132,"name":133,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":134,"categories":135,"keywords":143,"publishedAt":55},"01M6Q5R337B5JSNER4P4YS03TN","zerion-api","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api\u002FSKILL.md",[136,137,140],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":138,"categoryName":139,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":141,"categoryName":142,"taxonomyType":31,"taxonomyTypeDesc":32},"01JBSEEDCAT000000000000030","开发工程师",[37,144,145,146,147,148,149,116,150,120,151,152,153,154,40,155,156,157,158],"zerion api","zerion","MCP","mcp server","server","blockchain","transactions","crypto wallet","crypto","evm","solana","across","positions","token","prices",{"skillNo":160,"name":161,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":167,"publishedAt":55},"01M6Q5QZFYTDAZMZ27BN5VZXAR","zerion-api-skill","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-skill\u002FSKILL.md",[164,165,166],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":138,"categoryName":139,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":141,"categoryName":142,"taxonomyType":31,"taxonomyTypeDesc":32},[37,168,169,144,145,146,147,148,149,116,150,120,152,153,154,40,155,156,157,158],"api skill","zerion api skill",{"skillNo":171,"name":172,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":178,"publishedAt":55},"01M6Q5QW17QW98RA3FE45E4RD8","zerion-api-mcp","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-mcp\u002FSKILL.md",[175,176,177],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":138,"categoryName":139,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":141,"categoryName":142,"taxonomyType":31,"taxonomyTypeDesc":32},[146,37,179,144,145,147,148,116,150,120,151,152,153,154,40,155,156,157,158],"zerion api mcp",{"skillNo":181,"name":182,"nameZh":6,"description":183,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":184,"categories":185,"keywords":189,"publishedAt":55},"01M6Q5QQYZB7A501BDEQWKGSJT","yahoo-finance-forex","Fetches real-time FOREX news and market data from Yahoo Finance for major currency pairs (EUR\u002FUSD, GBP\u002FUSD, USD\u002FJPY, etc.). Analyzes sentiment and provides trading context.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fyahoo-finance-forex\u002FSKILL.md",[186],{"categoryNo":187,"categoryName":188,"taxonomyType":31,"taxonomyTypeDesc":32},"01JBSEEDCAT000000000000040","财务",[190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209],"finance","yahoo finance","forex","yahoo","yahoo finance forex","github","https","sentiment","real-time","python3","install","Market","usd","news","time","currency","gbp","pip","market data","for",{"skillNo":211,"name":212,"nameZh":6,"description":213,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":214,"categories":215,"keywords":217,"publishedAt":55},"01M6Q5QM6VS84WZVM7BKXXPF32","yahoo-finance","This skill should be used when the user asks to \"get stock prices\", \"check stock quotes\", \"look up earnings\", \"get financial data\", \"find trending stocks\", or needs stock market data from Yahoo Finance.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fyahoo-finance-cli\u002FSKILL.md",[216],{"categoryNo":187,"categoryName":188,"taxonomyType":31,"taxonomyTypeDesc":32},[190,191,193,218,219,220,221,222,223,201,224,225,226,227,228,229,230,231,158,208],"cli","homebrew","find","check","brew","up","local","get","stock","link","trending","sf","quotes","ln"]