[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AF9VPZPPMZ8TSPF2Z85JJE":3,"skill-same:01M6AF9VPZPPMZ8TSPF2Z85JJE":98},{"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":28,"publishedAt":51,"linkOnly":52,"markdownContent":53,"markdownBody":54,"frontMatter":55,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":61,"ownerHtmlUrl":62,"ownerBlogUrl":63,"ownerDescription":64,"updatedAt":65,"install":66,"resources":79},"01M6AF9VPZPPMZ8TSPF2Z85JJE","adaptyv",null,"Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33332,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[5,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50],"experiment","Protein","sequences","when","sequence","for","activity","solublempnn","expression","platform","computational","proteins","testing","api","Tools","Optimization","cloud","validation","status","experiments","workflows","design","2026-11-10 10:12:30",false,"---\nname: adaptyv\ndescription: Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.\n---\n\n# Adaptyv\n\nAdaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein sequences via API or web interface and receive experimental results in approximately 21 days.\n\n## Quick Start\n\n### Authentication Setup\n\nAdaptyv requires API authentication. Set up your credentials:\n\n1. Contact support@adaptyvbio.com to request API access (platform is in alpha\u002Fbeta)\n2. Receive your API access token\n3. Set environment variable:\n\n```bash\nexport ADAPTYV_API_KEY=\"your_api_key_here\"\n```\n\nOr create a `.env` file:\n\n```\nADAPTYV_API_KEY=your_api_key_here\n```\n\n### Installation\n\nInstall the required package using uv:\n\n```bash\nuv pip install requests python-dotenv\n```\n\n### Basic Usage\n\nSubmit protein sequences for testing:\n\n```python\nimport os\nimport requests\nfrom dotenv import load_dotenv\n\nload_dotenv()\n\napi_key = os.getenv(\"ADAPTYV_API_KEY\")\nbase_url = \"https:\u002F\u002Fkq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws\"\n\nheaders = {\n    \"Authorization\": f\"Bearer {api_key}\",\n    \"Content-Type\": \"application\u002Fjson\"\n}\n\n# Submit experiment\nresponse = requests.post(\n    f\"{base_url}\u002Fexperiments\",\n    headers=headers,\n    json={\n        \"sequences\": \">protein1\\nMKVLWALLGLLGAA...\",\n        \"experiment_type\": \"binding\",\n        \"webhook_url\": \"https:\u002F\u002Fyour-webhook.com\u002Fcallback\"\n    }\n)\n\nexperiment_id = response.json()[\"experiment_id\"]\n```\n\n## Available Experiment Types\n\nAdaptyv supports multiple assay types:\n\n- **Binding assays** - Test protein-target interactions using biolayer interferometry\n- **Expression testing** - Measure protein expression levels\n- **Thermostability** - Characterize protein thermal stability\n- **Enzyme activity** - Assess enzymatic function\n\nSee `reference\u002Fexperiments.md` for detailed information on each experiment type and workflows.\n\n## Protein Sequence Optimization\n\nBefore submitting sequences, optimize them for better expression and stability:\n\n**Common issues to address:**\n- Unpaired cysteines that create unwanted disulfides\n- Excessive hydrophobic regions causing aggregation\n- Poor solubility predictions\n\n**Recommended tools:**\n- NetSolP \u002F SoluProt - Initial solubility filtering\n- SolubleMPNN - Sequence redesign for improved solubility\n- ESM - Sequence likelihood scoring\n- ipTM - Interface stability assessment\n- pSAE - Hydrophobic exposure quantification\n\nSee `reference\u002Fprotein_optimization.md` for detailed optimization workflows and tool usage.\n\n## API Reference\n\nFor complete API documentation including all endpoints, request\u002Fresponse formats, and authentication details, see `reference\u002Fapi_reference.md`.\n\n## Examples\n\nFor concrete code examples covering common use cases (experiment submission, status tracking, result retrieval, batch processing), see `reference\u002Fexamples.md`.\n\n## Important Notes\n\n- Platform is currently in alpha\u002Fbeta phase with features subject to change\n- Not all platform features are available via API yet\n- Results typically delivered in ~21 days\n- Contact support@adaptyvbio.com for access requests or questions\n- Suitable for high-throughput AI-driven protein design workflows\n","# Adaptyv\n\nAdaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein sequences via API or web interface and receive experimental results in approximately 21 days.\n\n## Quick Start\n\n### Authentication Setup\n\nAdaptyv requires API authentication. Set up your credentials:\n\n1. Contact support@adaptyvbio.com to request API access (platform is in alpha\u002Fbeta)\n2. Receive your API access token\n3. Set environment variable:\n\n```bash\nexport ADAPTYV_API_KEY=\"your_api_key_here\"\n```\n\nOr create a `.env` file:\n\n```\nADAPTYV_API_KEY=your_api_key_here\n```\n\n### Installation\n\nInstall the required package using uv:\n\n```bash\nuv pip install requests python-dotenv\n```\n\n### Basic Usage\n\nSubmit protein sequences for testing:\n\n```python\nimport os\nimport requests\nfrom dotenv import load_dotenv\n\nload_dotenv()\n\napi_key = os.getenv(\"ADAPTYV_API_KEY\")\nbase_url = \"https:\u002F\u002Fkq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws\"\n\nheaders = {\n    \"Authorization\": f\"Bearer {api_key}\",\n    \"Content-Type\": \"application\u002Fjson\"\n}\n\n# Submit experiment\nresponse = requests.post(\n    f\"{base_url}\u002Fexperiments\",\n    headers=headers,\n    json={\n        \"sequences\": \">protein1\\nMKVLWALLGLLGAA...\",\n        \"experiment_type\": \"binding\",\n        \"webhook_url\": \"https:\u002F\u002Fyour-webhook.com\u002Fcallback\"\n    }\n)\n\nexperiment_id = response.json()[\"experiment_id\"]\n```\n\n## Available Experiment Types\n\nAdaptyv supports multiple assay types:\n\n- **Binding assays** - Test protein-target interactions using biolayer interferometry\n- **Expression testing** - Measure protein expression levels\n- **Thermostability** - Characterize protein thermal stability\n- **Enzyme activity** - Assess enzymatic function\n\nSee `reference\u002Fexperiments.md` for detailed information on each experiment type and workflows.\n\n## Protein Sequence Optimization\n\nBefore submitting sequences, optimize them for better expression and stability:\n\n**Common issues to address:**\n- Unpaired cysteines that create unwanted disulfides\n- Excessive hydrophobic regions causing aggregation\n- Poor solubility predictions\n\n**Recommended tools:**\n- NetSolP \u002F SoluProt - Initial solubility filtering\n- SolubleMPNN - Sequence redesign for improved solubility\n- ESM - Sequence likelihood scoring\n- ipTM - Interface stability assessment\n- pSAE - Hydrophobic exposure quantification\n\nSee `reference\u002Fprotein_optimization.md` for detailed optimization workflows and tool usage.\n\n## API Reference\n\nFor complete API documentation including all endpoints, request\u002Fresponse formats, and authentication details, see `reference\u002Fapi_reference.md`.\n\n## Examples\n\nFor concrete code examples covering common use cases (experiment submission, status tracking, result retrieval, batch processing), see `reference\u002Fexamples.md`.\n\n## Important Notes\n\n- Platform is currently in alpha\u002Fbeta phase with features subject to change\n- Not all platform features are available via API yet\n- Results typically delivered in ~21 days\n- Contact support@adaptyvbio.com for access requests or questions\n- Suitable for high-throughput AI-driven protein design workflows\n",{"name":5,"description":7},"main","2b749c82b5d11fac39d9a6e021ce3f5b8a541bd1","cli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv",3911,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates","https:\u002F\u002Faitmpl.com","https:\u002F\u002Fgithub.com\u002Fdavila7","https:\u002F\u002Fdanielavila.me","Building AI dev tools with LLMs","2026-11-11 21:38:31",{"source":8,"skillName":5,"commands":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add davila7\u002Fclaude-code-templates --skill adaptyv",{"tool":72,"command":73},"bunx","bunx skills add davila7\u002Fclaude-code-templates --skill adaptyv",{"tool":75,"command":76},"pnpm","pnpm dlx skills add davila7\u002Fclaude-code-templates --skill adaptyv","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002FSKILL.md",true,[80,86,90,94],{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"reference\u002Fapi_reference.md","REFERENCE","参考文档",6665,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002Freference\u002Fapi_reference.md",{"path":87,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":88,"sourceHtmlUrl":89},"reference\u002Fexamples.md",23091,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002Freference\u002Fexamples.md",{"path":91,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":92,"sourceHtmlUrl":93},"reference\u002Fexperiments.md",9947,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002Freference\u002Fexperiments.md",{"path":95,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":96,"sourceHtmlUrl":97},"reference\u002Fprotein_optimization.md",17861,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002Freference\u002Fprotein_optimization.md",[99,127,154,183,217,240],{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":108,"publishedAt":51},"01M70NHBTQ8BV0A2SCAZXEPHCX","wealthville-pool-scoring","Score DeFi liquidity pools before providing liquidity. Returns a 0-100 pool score and an Enter\u002FHold\u002FExit\u002FReduce\u002FAvoid verdict with calibrated confidence for ~68,800 Solana pools and 575 EVM pools, plus a public miss-inclusive track record. Use when asked whether a pool is worth LPing into, which pools look best right now, or how accurate the scores have actually been.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fweb-data\u002Fwealthville-pool-scoring\u002FSKILL.md",[105],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[109,110,111,112,113,34,114,115,116,32,117,118,119,120,121,122,123,124,125,126],"scoring","pool","wealthville pool scoring","liquidity","which","exit","now","use","reduce","with","record","track","verdict","evm","solana","how","public","look",{"skillNo":128,"name":129,"nameZh":6,"description":130,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":131,"categories":132,"keywords":134,"publishedAt":51},"01M70MB6VR8ERJ4EM8D5KHBMEV","technical-debt-auditor","Scans a codebase and produces a quantified technical debt report with a prioritized remediation plan. Analyzes dead code, TODO\u002FFIXME\u002FHACK markers, dependency staleness, complexity hotspots, code duplication signals, test coverage gaps, unused exports, and outdated patterns. Use this skill when the user asks to audit their codebase for tech debt, wants a health check of their code quality, says things like \"where should I focus refactoring\", \"find code smells\", \"audit my codebase\", \"what technical debt do we have\", \"prioritize cleanup work\", or asks about code quality metrics. Also trigger when the user mentions \"code rot\", \"legacy cleanup\", \"refactoring priorities\", or wants to understand the overall health of a project before a major effort. Trigger even if the user doesn't say \"technical debt\" explicitly — any request to systematically assess code quality and identify improvement priorities belongs here.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Ftechnical-debt-auditor\u002FSKILL.md",[133],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},[135,136,137,138,139,140,141,142,143,144,145,32,146,147,148,149,150,151,152,153],"technical debt","debt","technical","technical debt auditor","auditor","coverage","complexity","markers","project","cleanup","unused","code","todo","work","plan","focus","signals","audit","dependency",{"skillNo":155,"name":156,"nameZh":6,"description":157,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":158,"categories":159,"keywords":165,"publishedAt":51},"01M70KPYH9QNHCNME5GJQGE22K","readonly-sql-guard","Make an agent's database access provably read-only. Use when an agent runs caller-supplied SQL against a production\u002FERP\u002Fanalytics database (a \"query\" MCP tool, text-to-SQL, an admin console), or when reviewing DB-access code for write\u002FDDL\u002Fside-effect\u002Ftransaction-escape risks. Checks what a statement CALLS, not just its shape.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdatabase\u002Freadonly-sql-guard\u002FSKILL.md",[160,161,162],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":163,"categoryName":164,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000033","数据分析师",[166,167,168,169,170,171,172,34,173,174,175,176,177,178,179,116,180,181,32,182],"readonly","guard","sql guard","sql","readonly sql guard","erp","effect","read-only","db","just","tool","calls","only","MCP","access","database","query",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":187,"licenseFileUrl":188,"sourceHtmlUrl":189,"categories":190,"keywords":194,"publishedAt":51},"01M6AFY6F7CC2BBZP1QD6VTNVC","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[191],{"categoryNo":192,"categoryName":193,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[195,196,197,198,199,200,201,202,203,204,205,206,43,207,208,209,210,211,212,213,214,215,34,216],"artifacts builder","web","web artifacts builder","artifacts","builder","state","routing","state management","component","css","frontend","ui","file","components","shadcn","react","Tailwind","suite","jsx","html","single-file","ui components",{"skillNo":218,"name":219,"nameZh":6,"description":220,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":187,"licenseFileUrl":221,"sourceHtmlUrl":222,"categories":223,"keywords":228,"publishedAt":51},"01M6AFWF33SFV9Z3SF4PEEE4BF","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FSKILL.md",[224,227],{"categoryNo":225,"categoryName":226,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":192,"categoryName":193,"taxonomyType":21,"taxonomyTypeDesc":22},[229,41,230,231,232,196,233,205,206,234,235,236,237,34,238,118,239],"webapp testing","webapp","browser","playwright","applications","debugging","toolkit","logs","screenshots","local","behavior",{"skillNo":241,"name":242,"nameZh":6,"description":243,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":187,"licenseFileUrl":244,"sourceHtmlUrl":245,"categories":246,"keywords":254,"publishedAt":51},"01M6AF67Q67JJJ5V51JR2P52KA","discernment-nudge","After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FSKILL.md",[247,250,251],{"categoryNo":248,"categoryName":249,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":252,"categoryName":253,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000036","内容创作者",[255,256,257,258,259,260,261,262,198,263,207,146,264,265,266,267,268,178,269,32,270,271,272,273,274,124,275],"discernment nudge","nudge","interpretation","help","run","reasoning","data","writing","lookup","content","review","conversation","short","up","invoke","you","analysis","claims","argument","assemble","recommendations"]