[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FS5DPAB3Z1M9C9SYWNRX6K":3,"skill-same:01M6FS5DPAB3Z1M9C9SYWNRX6K":74},{"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":17,"publishedAt":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M6FS5DPAB3Z1M9C9SYWNRX6K","intellectia-stock-screener",null,"Get stock screener list data from Intellectia API (no auth) and summarize results.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fintellectiaai\u002Fintellectia-stock-screener\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"stock","screener","intellectia stock screener","summarize","python","auth","data","api","python3","curl","list","results","install","get","requests","2026-11-10 10:12:30",false,"---\nname: intellectia-stock-screener\ndescription: Get stock screener list data from Intellectia API (no auth) and summarize results.\nmetadata: {\"openclaw\":{\"requires\":{\"bins\":[\"curl\",\"python3\"]},\"install\":[{\"id\":\"python\",\"kind\":\"pip\",\"package\":\"requests\",\"bins\":[],\"label\":\"Install requests (pip)\"}]}}\n---\n\n# Intellectia Stock Screener\n\nBase URL: `https:\u002F\u002Fapi.intellectia.ai`\n\n## Endpoint\n\n- `GET \u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list`\n\nFull URL:\n- `https:\u002F\u002Fapi.intellectia.ai\u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list`\n\n## Query parameters\n\n- `symbol_type` (int): Asset type `0=stock 1=etf 2=crypto`\n- `period_type` (int): Period `0=day 1=week 2=month`\n- `trend_type` (int): Trend `0=bullish 1=bearish`\n- `profit_asc` (bool): Sort by profit ascending (`true` = small → large)\n- `market_cap` (int): Market cap filter\n  - `0=any`\n  - `1=micro \u003C300M`\n  - `2=small 300M-2B`\n  - `3=mid 2B-10B`\n  - `4=large 10B-200B`\n  - `5=mega >200B`\n- `price` (int): Price filter\n  - `0=any`\n  - `1=\u003C5`\n  - `2=\u003C50`\n  - `3=>5`\n  - `4=>50`\n  - `5=5-50`\n- `page` (int): Page number (example: 1)\n- `size` (int): Page size (example: 20)\n\n## Response (200)\n\nExample response (shape):\n\n```json\n{\n  \"ret\": 0,\n  \"msg\": \"\",\n  \"data\": {\n    \"list\": [\n      {\n        \"code\": \"BKD.N\",\n        \"symbol\": \"BKD\",\n        \"symbol_type\": 0,\n        \"name\": \"Brookdale Senior Living Inc\",\n        \"logo\": \"https:\u002F\u002Fintellectia-public-documents.s3.amazonaws.com\u002Fimage\u002Flogo\u002FBKD_logo.png\",\n        \"pre_close\": 14.5,\n        \"price\": 15,\n        \"change_ratio\": 3.45,\n        \"timestamp\": \"1769749200\",\n        \"simiar_num\": 10,\n        \"probability\": 80,\n        \"profit\": 5.27,\n        \"klines\": [{ \"close\": 15, \"timestamp\": \"1769749200\" }],\n        \"trend_list\": [\n          {\n            \"symbol\": \"BKD\",\n            \"symbol_type\": 0,\n            \"is_main\": true,\n            \"list\": [{ \"change_ratio\": 5.27, \"timestamp\": \"1730260800\", \"close\": 16 }]\n          }\n        ],\n        \"update_time\": \"1769806800\"\n      }\n    ],\n    \"total\": 3,\n    \"detail\": {\n      \"cover_url\": \"https:\u002F\u002Fd159e3ysga2l0q.cloudfront.net\u002Fimage\u002Fcover_image\u002Fstock-1.png\",\n      \"name\": \"Stocks Bullish Tomorrow\",\n      \"screener_type\": 1011,\n      \"params\": \"{}\",\n      \"desc\": \"...\"\n    }\n  }\n}\n```\n\n### Field reference\n\nTop-level:\n- `ret` (int): Status code (typically `0` means success)\n- `msg` (string): Message (empty string when OK)\n- `data` (object): Payload\n\n`data`:\n- `data.list` (array): Result rows\n- `data.total` (int): Total number of rows\n- `data.detail` (object): Screener metadata\n\nEach item in `data.list`:\n- `code` (string): Full instrument code (may include exchange suffix, e.g. `BKD.N`)\n- `symbol` (string): Ticker symbol (e.g. `BKD`)\n- `symbol_type` (int): Asset type (`0=stock 1=etf 2=crypto`)\n- `name` (string): Display name\n- `logo` (string): Logo URL\n- `pre_close` (number): Previous close price\n- `price` (number): Current price\n- `change_ratio` (number): Percent change vs previous close\n- `timestamp` (string): Quote timestamp (Unix seconds)\n- `simiar_num` (int): Similarity count (as returned by API; spelling kept as-is)\n- `probability` (int): Model confidence (0-100)\n- `profit` (number): Predicted\u002Fexpected return (as returned by API)\n- `klines` (array): Price series\n  - `klines[].close` (number): Close price\n  - `klines[].timestamp` (string): Unix seconds\n- `trend_list` (array): Trend comparison series\n  - `trend_list[].symbol` (string): Symbol for the series (may be empty for non-main series)\n  - `trend_list[].symbol_type` (int): Asset type\n  - `trend_list[].is_main` (bool): Whether this is the main series\n  - `trend_list[].list` (array): Time points\n    - `trend_list[].list[].change_ratio` (number): Percent change at that point\n    - `trend_list[].list[].timestamp` (string): Unix seconds\n    - `trend_list[].list[].close` (number): Close price at that point\n- `update_time` (string): Last update time (Unix seconds)\n\n`data.detail`:\n- `cover_url` (string): Cover image URL\n- `name` (string): Screener title\n- `screener_type` (int): Screener type ID\n- `params` (string): Serialized params (often JSON string)\n- `desc` (string): Screener description\n- `num` (int, optional): As returned by API (may be absent)\n\n## Examples\n\n### cURL\n\n```bash\ncurl -sS \"https:\u002F\u002Fapi.intellectia.ai\u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list?symbol_type=0&period_type=0&trend_type=0&profit_asc=false&market_cap=0&price=0&page=1&size=20\"\n```\n\n### Python (requests)\n\n```bash\npython3 - \u003C\u003C'PY'\nimport requests\n\nbase_url = \"https:\u002F\u002Fapi.intellectia.ai\"\nparams = {\n  \"symbol_type\": 0,\n  \"period_type\": 0,\n  \"trend_type\": 0,\n  \"profit_asc\": False,\n  \"market_cap\": 0,\n  \"price\": 0,\n  \"page\": 1,\n  \"size\": 20,\n}\n\nr = requests.get(f\"{base_url}\u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list\", params=params, timeout=30)\nr.raise_for_status()\npayload = r.json()\n\nprint(\"ret:\", payload.get(\"ret\"))\nprint(\"msg:\", payload.get(\"msg\"))\ndata = payload.get(\"data\") or {}\nrows = data.get(\"list\") or []\nprint(\"total:\", data.get(\"total\"))\nfor row in rows[:10]:\n  print(row.get(\"symbol\"), row.get(\"price\"), row.get(\"change_ratio\"), row.get(\"probability\"), row.get(\"profit\"))\nPY\n```\n\n## Notes\n\n- No authentication required.\n- If you see rate limits, reduce `size` and add backoff\u002Fretry in client code.\n","# Intellectia Stock Screener\n\nBase URL: `https:\u002F\u002Fapi.intellectia.ai`\n\n## Endpoint\n\n- `GET \u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list`\n\nFull URL:\n- `https:\u002F\u002Fapi.intellectia.ai\u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list`\n\n## Query parameters\n\n- `symbol_type` (int): Asset type `0=stock 1=etf 2=crypto`\n- `period_type` (int): Period `0=day 1=week 2=month`\n- `trend_type` (int): Trend `0=bullish 1=bearish`\n- `profit_asc` (bool): Sort by profit ascending (`true` = small → large)\n- `market_cap` (int): Market cap filter\n  - `0=any`\n  - `1=micro \u003C300M`\n  - `2=small 300M-2B`\n  - `3=mid 2B-10B`\n  - `4=large 10B-200B`\n  - `5=mega >200B`\n- `price` (int): Price filter\n  - `0=any`\n  - `1=\u003C5`\n  - `2=\u003C50`\n  - `3=>5`\n  - `4=>50`\n  - `5=5-50`\n- `page` (int): Page number (example: 1)\n- `size` (int): Page size (example: 20)\n\n## Response (200)\n\nExample response (shape):\n\n```json\n{\n  \"ret\": 0,\n  \"msg\": \"\",\n  \"data\": {\n    \"list\": [\n      {\n        \"code\": \"BKD.N\",\n        \"symbol\": \"BKD\",\n        \"symbol_type\": 0,\n        \"name\": \"Brookdale Senior Living Inc\",\n        \"logo\": \"https:\u002F\u002Fintellectia-public-documents.s3.amazonaws.com\u002Fimage\u002Flogo\u002FBKD_logo.png\",\n        \"pre_close\": 14.5,\n        \"price\": 15,\n        \"change_ratio\": 3.45,\n        \"timestamp\": \"1769749200\",\n        \"simiar_num\": 10,\n        \"probability\": 80,\n        \"profit\": 5.27,\n        \"klines\": [{ \"close\": 15, \"timestamp\": \"1769749200\" }],\n        \"trend_list\": [\n          {\n            \"symbol\": \"BKD\",\n            \"symbol_type\": 0,\n            \"is_main\": true,\n            \"list\": [{ \"change_ratio\": 5.27, \"timestamp\": \"1730260800\", \"close\": 16 }]\n          }\n        ],\n        \"update_time\": \"1769806800\"\n      }\n    ],\n    \"total\": 3,\n    \"detail\": {\n      \"cover_url\": \"https:\u002F\u002Fd159e3ysga2l0q.cloudfront.net\u002Fimage\u002Fcover_image\u002Fstock-1.png\",\n      \"name\": \"Stocks Bullish Tomorrow\",\n      \"screener_type\": 1011,\n      \"params\": \"{}\",\n      \"desc\": \"...\"\n    }\n  }\n}\n```\n\n### Field reference\n\nTop-level:\n- `ret` (int): Status code (typically `0` means success)\n- `msg` (string): Message (empty string when OK)\n- `data` (object): Payload\n\n`data`:\n- `data.list` (array): Result rows\n- `data.total` (int): Total number of rows\n- `data.detail` (object): Screener metadata\n\nEach item in `data.list`:\n- `code` (string): Full instrument code (may include exchange suffix, e.g. `BKD.N`)\n- `symbol` (string): Ticker symbol (e.g. `BKD`)\n- `symbol_type` (int): Asset type (`0=stock 1=etf 2=crypto`)\n- `name` (string): Display name\n- `logo` (string): Logo URL\n- `pre_close` (number): Previous close price\n- `price` (number): Current price\n- `change_ratio` (number): Percent change vs previous close\n- `timestamp` (string): Quote timestamp (Unix seconds)\n- `simiar_num` (int): Similarity count (as returned by API; spelling kept as-is)\n- `probability` (int): Model confidence (0-100)\n- `profit` (number): Predicted\u002Fexpected return (as returned by API)\n- `klines` (array): Price series\n  - `klines[].close` (number): Close price\n  - `klines[].timestamp` (string): Unix seconds\n- `trend_list` (array): Trend comparison series\n  - `trend_list[].symbol` (string): Symbol for the series (may be empty for non-main series)\n  - `trend_list[].symbol_type` (int): Asset type\n  - `trend_list[].is_main` (bool): Whether this is the main series\n  - `trend_list[].list` (array): Time points\n    - `trend_list[].list[].change_ratio` (number): Percent change at that point\n    - `trend_list[].list[].timestamp` (string): Unix seconds\n    - `trend_list[].list[].close` (number): Close price at that point\n- `update_time` (string): Last update time (Unix seconds)\n\n`data.detail`:\n- `cover_url` (string): Cover image URL\n- `name` (string): Screener title\n- `screener_type` (int): Screener type ID\n- `params` (string): Serialized params (often JSON string)\n- `desc` (string): Screener description\n- `num` (int, optional): As returned by API (may be absent)\n\n## Examples\n\n### cURL\n\n```bash\ncurl -sS \"https:\u002F\u002Fapi.intellectia.ai\u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list?symbol_type=0&period_type=0&trend_type=0&profit_asc=false&market_cap=0&price=0&page=1&size=20\"\n```\n\n### Python (requests)\n\n```bash\npython3 - \u003C\u003C'PY'\nimport requests\n\nbase_url = \"https:\u002F\u002Fapi.intellectia.ai\"\nparams = {\n  \"symbol_type\": 0,\n  \"period_type\": 0,\n  \"trend_type\": 0,\n  \"profit_asc\": False,\n  \"market_cap\": 0,\n  \"price\": 0,\n  \"page\": 1,\n  \"size\": 20,\n}\n\nr = requests.get(f\"{base_url}\u002Fgateway\u002Fv1\u002Fstock\u002Fscreener-list\", params=params, timeout=30)\nr.raise_for_status()\npayload = r.json()\n\nprint(\"ret:\", payload.get(\"ret\"))\nprint(\"msg:\", payload.get(\"msg\"))\ndata = payload.get(\"data\") or {}\nrows = data.get(\"list\") or []\nprint(\"total:\", data.get(\"total\"))\nfor row in rows[:10]:\n  print(row.get(\"symbol\"), row.get(\"price\"), row.get(\"change_ratio\"), row.get(\"probability\"), row.get(\"profit\"))\nPY\n```\n\n## Notes\n\n- No authentication required.\n- If you see rate limits, reduce `size` and add backoff\u002Fretry in client code.\n",{"name":5,"metadata":38,"description":7},{"openclaw":39},{"install":40,"requires":45},[41],{"id":22,"bins":42,"kind":43,"label":44,"package":32},[],"pip","Install requests (pip)",{"bins":46},[27,26],"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Fintellectiaai\u002Fintellectia-stock-screener",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add kbarbel640-del\u002Fskills --skill intellectia-stock-screener",{"tool":60,"command":61},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill intellectia-stock-screener",{"tool":63,"command":64},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill intellectia-stock-screener","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fintellectiaai\u002Fintellectia-stock-screener\u002FSKILL.md",true,[68],{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"_meta.json","REFERENCE","参考文档",299,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fintellectiaai\u002Fintellectia-stock-screener\u002F_meta.json",[75,105,134,155,161,180],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":79,"categories":80,"keywords":86,"publishedAt":33},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[81],{"categoryNo":82,"categoryName":83,"taxonomyType":84,"taxonomyTypeDesc":85},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[87,88,25,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104],"crowd prompting","prompting","with","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","https","content","ai agents",{"skillNo":106,"name":107,"nameZh":6,"description":108,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":116,"publishedAt":33},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[111],{"categoryNo":112,"categoryName":113,"taxonomyType":114,"taxonomyTypeDesc":115},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[117,25,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,93,133],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking","use",{"skillNo":135,"name":136,"nameZh":6,"description":137,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":138,"categories":139,"keywords":143,"publishedAt":33},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. 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Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[186,187],{"categoryNo":112,"categoryName":113,"taxonomyType":114,"taxonomyTypeDesc":115},{"categoryNo":188,"categoryName":189,"taxonomyType":84,"taxonomyTypeDesc":85},"01JBSEEDCAT000000000000037","律师与法务",[191,192,193,194,89,195,196,47,197,152,198,199,200,201,202,102,203,204,205],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]