[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6MX5MYZPASZNR8XFBMJF9WT":3,"skill-same:01M6MX5MYZPASZNR8XFBMJF9WT":79},{"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":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":52,"commitSha":53,"skillDirectory":54,"forksCount":55,"repositoryHtmlUrl":56,"repositoryHomepageUrl":6,"ownerHtmlUrl":57,"ownerBlogUrl":6,"ownerDescription":58,"updatedAt":59,"install":60,"resources":72},"01M6MX5MYZPASZNR8XFBMJF9WT","aubrai-longevity",null,"Meet your SOTA longevity research partner. Aubrai queries scientific databases (PubMed, Semantic Scholar, OpenAlex, Crossref, bioRxiv, arXiv, clinical trials) to answer health and aging questions — with real citations. Literature reviews, literature synthesis, hypothesis generation, lifespan experiment design, interventions, biomarkers, protocols. Science, not speculation. chat.aubr.ai. Try at chat.aubr.ai.","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人工智能与大型语言模型\u002Faubrai-longevity\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"longevity","aubrai longevity","pubmed","Meet","clinical trials","at","scholar","reviews","semantic scholar","scientific","design","literature","clinical","arxiv","databases","experiment","hypothesis generation","Citations","protocols","experiment design","2026-11-10 10:12:30",false,"---\nname: aubrai-longevity\ndescription: Meet your SOTA longevity research partner. Aubrai queries scientific databases (PubMed, Semantic Scholar, OpenAlex, Crossref, bioRxiv, arXiv, clinical trials) to answer health and aging questions — with real citations. Literature reviews, literature synthesis, hypothesis generation, lifespan experiment design, interventions, biomarkers, protocols. Science, not speculation. chat.aubr.ai. Try at chat.aubr.ai.\nuser-invocable: true\nmetadata: {\"openclaw\":{\"always\":true,\"emoji\":\"?\"}}\n---\n\n# Aubrai Longevity Research\n\nYou have access to the Aubrai bioagent API for answering scientific questions about longevity, aging, and related biology topics.\n\n## API Details\n\n- **Base URL**: `https:\u002F\u002Fsatisfied-light-production.up.railway.app`\n- **Authentication**: NONE. This is a public API. Do NOT ask the user for an API key. Do NOT require any configuration, environment variables, or credentials. Just call the endpoints directly.\n- **Rate limit**: 1 request per 1 minute (global)\n\n## How to Use\n\nWhen the user asks a longevity or aging-related question, follow these steps:\n\n### Step 1: Submit the question\n\nUse the `exec` tool to send the question to Aubrai:\n\n```bash\ncurl -s -X POST https:\u002F\u002Fsatisfied-light-production.up.railway.app\u002Fapi\u002Fchat \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\"message\":\"USER_QUESTION_HERE\"}'\n```\n\nThe response will contain a `jobId` and `conversationId`. Save both values.\n\n### Step 2: Poll for the result\n\nAubrai takes 30-60 seconds to research and respond. Poll every 3 seconds:\n\n```bash\ncurl -s https:\u002F\u002Fsatisfied-light-production.up.railway.app\u002Fapi\u002Fchat\u002Fstatus\u002FJOB_ID_HERE\n```\n\nThe response `status` field will be one of:\n- `active` — still processing (check `progress.stage`: planning → literature → hypothesis → reply)\n- `completed` — the answer is in `result.text`\n- `failed` — an error occurred\n\nKeep polling until `status` is `completed` or `failed`.\n\n### Step 3: Present the response\n\nWhen the job completes, extract `result.text` and present it to the user. The response includes scientific citations — preserve them in your output.\n\n### Step 4: Follow-up questions\n\nTo continue the conversation, include the `conversationId` from the first response:\n\n```bash\ncurl -s -X POST https:\u002F\u002Fsatisfied-light-production.up.railway.app\u002Fapi\u002Fchat \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\"message\":\"FOLLOW_UP_QUESTION\", \"conversationId\":\"CONVERSATION_ID_HERE\"}'\n```\n\nThen poll for the result the same way.\n\n## Important Notes\n\n- Responses take 30-60 seconds — inform the user that research is in progress\n- The API is rate limited to 1 request per 1 minute globally\n- If you get a 429 response, tell the user to wait and show the `retryAfterSeconds` value\n- This skill is best for scientific questions about: aging, longevity, healthspan, lifespan, senolytics, telomeres, mitochondrial function, caloric restriction, rapamycin, NAD+, and related topics\n\n## Example\n\nUser asks: \"What are the main causes of aging?\"\n\n1. Submit: `curl -s -X POST ...\u002Fapi\u002Fchat -H \"Content-Type: application\u002Fjson\" -d '{\"message\":\"What are the main causes of aging?\"}'`\n2. Get `jobId` from response\n3. Poll: `curl -s ...\u002Fapi\u002Fchat\u002Fstatus\u002F{jobId}` every 3 seconds\n4. When `status` is `completed`, present `result.text` to the user\n","# Aubrai Longevity Research\n\nYou have access to the Aubrai bioagent API for answering scientific questions about longevity, aging, and related biology topics.\n\n## API Details\n\n- **Base URL**: `https:\u002F\u002Fsatisfied-light-production.up.railway.app`\n- **Authentication**: NONE. This is a public API. Do NOT ask the user for an API key. Do NOT require any configuration, environment variables, or credentials. Just call the endpoints directly.\n- **Rate limit**: 1 request per 1 minute (global)\n\n## How to Use\n\nWhen the user asks a longevity or aging-related question, follow these steps:\n\n### Step 1: Submit the question\n\nUse the `exec` tool to send the question to Aubrai:\n\n```bash\ncurl -s -X POST https:\u002F\u002Fsatisfied-light-production.up.railway.app\u002Fapi\u002Fchat \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\"message\":\"USER_QUESTION_HERE\"}'\n```\n\nThe response will contain a `jobId` and `conversationId`. Save both values.\n\n### Step 2: Poll for the result\n\nAubrai takes 30-60 seconds to research and respond. Poll every 3 seconds:\n\n```bash\ncurl -s https:\u002F\u002Fsatisfied-light-production.up.railway.app\u002Fapi\u002Fchat\u002Fstatus\u002FJOB_ID_HERE\n```\n\nThe response `status` field will be one of:\n- `active` — still processing (check `progress.stage`: planning → literature → hypothesis → reply)\n- `completed` — the answer is in `result.text`\n- `failed` — an error occurred\n\nKeep polling until `status` is `completed` or `failed`.\n\n### Step 3: Present the response\n\nWhen the job completes, extract `result.text` and present it to the user. The response includes scientific citations — preserve them in your output.\n\n### Step 4: Follow-up questions\n\nTo continue the conversation, include the `conversationId` from the first response:\n\n```bash\ncurl -s -X POST https:\u002F\u002Fsatisfied-light-production.up.railway.app\u002Fapi\u002Fchat \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\"message\":\"FOLLOW_UP_QUESTION\", \"conversationId\":\"CONVERSATION_ID_HERE\"}'\n```\n\nThen poll for the result the same way.\n\n## Important Notes\n\n- Responses take 30-60 seconds — inform the user that research is in progress\n- The API is rate limited to 1 request per 1 minute globally\n- If you get a 429 response, tell the user to wait and show the `retryAfterSeconds` value\n- This skill is best for scientific questions about: aging, longevity, healthspan, lifespan, senolytics, telomeres, mitochondrial function, caloric restriction, rapamycin, NAD+, and related topics\n\n## Example\n\nUser asks: \"What are the main causes of aging?\"\n\n1. Submit: `curl -s -X POST ...\u002Fapi\u002Fchat -H \"Content-Type: application\u002Fjson\" -d '{\"message\":\"What are the main causes of aging?\"}'`\n2. Get `jobId` from response\n3. Poll: `curl -s ...\u002Fapi\u002Fchat\u002Fstatus\u002F{jobId}` every 3 seconds\n4. When `status` is `completed`, present `result.text` to the user\n",{"name":5,"metadata":48,"description":7,"user-invocable":51},{"openclaw":49},{"emoji":50,"always":51},"?",true,"main","f4cb2d49f7667e79ef7804f50396d5aaffdf1f56","人工智能与大型语言模型\u002Faubrai-longevity",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":61,"prompt":71,"zipAvailable":51},[62,65,68],{"tool":63,"command":64},"npx","npx skills add Kernel8901\u002Fai-agent-skills-classification --skill aubrai-longevity",{"tool":66,"command":67},"bunx","bunx skills add Kernel8901\u002Fai-agent-skills-classification --skill aubrai-longevity",{"tool":69,"command":70},"pnpm","pnpm dlx skills add Kernel8901\u002Fai-agent-skills-classification --skill aubrai-longevity","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Faubrai-longevity\u002FSKILL.md",[73],{"path":74,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":77,"sourceHtmlUrl":78},"_meta.json","REFERENCE","参考文档",656,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Faubrai-longevity\u002F_meta.json",[80,104,138,149,159,189],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":86,"publishedAt":43},"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",[],[82,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103],"safe","ethereum","defi","Optimization","user","use","Wallet","base","deposit","withdraw","yield","arbitrum","non-custodial","passive","defi yield","earn","yield optimization",{"skillNo":105,"name":106,"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":107,"categories":108,"keywords":120,"publishedAt":43},"01M6Q5R337B5JSNER4P4YS03TN","zerion-api","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api\u002FSKILL.md",[109,112,115],{"categoryNo":110,"categoryName":111,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":113,"categoryName":114,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":116,"categoryName":117,"taxonomyType":118,"taxonomyTypeDesc":119},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[121,122,123,124,125,126,127,89,128,93,129,130,131,132,133,134,135,136,137],"api","zerion api","zerion","MCP","mcp server","server","blockchain","transactions","crypto wallet","crypto","evm","solana","query","across","positions","token","prices",{"skillNo":139,"name":140,"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":141,"categories":142,"keywords":146,"publishedAt":43},"01M6Q5QZFYTDAZMZ27BN5VZXAR","zerion-api-skill","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-skill\u002FSKILL.md",[143,144,145],{"categoryNo":110,"categoryName":111,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":113,"categoryName":114,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":116,"categoryName":117,"taxonomyType":118,"taxonomyTypeDesc":119},[121,147,148,122,123,124,125,126,127,89,128,93,130,131,132,133,134,135,136,137],"api skill","zerion api skill",{"skillNo":150,"name":151,"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":152,"categories":153,"keywords":157,"publishedAt":43},"01M6Q5QW17QW98RA3FE45E4RD8","zerion-api-mcp","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-mcp\u002FSKILL.md",[154,155,156],{"categoryNo":110,"categoryName":111,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":113,"categoryName":114,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":116,"categoryName":117,"taxonomyType":118,"taxonomyTypeDesc":119},[124,121,158,122,123,125,126,89,128,93,129,130,131,132,133,134,135,136,137],"zerion api mcp",{"skillNo":160,"name":161,"nameZh":6,"description":162,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":163,"categories":164,"keywords":168,"publishedAt":43},"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",[165],{"categoryNo":166,"categoryName":167,"taxonomyType":118,"taxonomyTypeDesc":119},"01JBSEEDCAT000000000000040","财务",[169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188],"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":190,"name":191,"nameZh":6,"description":192,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":193,"categories":194,"keywords":196,"publishedAt":43},"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",[195],{"categoryNo":166,"categoryName":167,"taxonomyType":118,"taxonomyTypeDesc":119},[169,170,172,197,198,199,200,201,202,180,203,204,205,206,207,208,209,210,137,187],"cli","homebrew","find","check","brew","up","local","get","stock","link","trending","sf","quotes","ln"]