[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DPM2ZVH85W9EM4MPW2QXQ2":3,"skill-same:01M6DPM2ZVH85W9EM4MPW2QXQ2":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":23,"publishedAt":41,"linkOnly":42,"markdownContent":43,"markdownBody":44,"frontMatter":45,"refName":47,"commitSha":48,"skillDirectory":5,"forksCount":14,"repositoryHtmlUrl":49,"repositoryHomepageUrl":6,"ownerHtmlUrl":50,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":51,"install":52,"resources":65},"01M6DPM2ZVH85W9EM4MPW2QXQ2","patents-search",null,"Search global patents with natural language queries. Prior art, patent landscapes, and innovation tracking via Valyu.","huamu668\u002Fclawhub-openclaw-medical","huamu668","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F202473531?v=4","01M6DK1V7D7VP9PJ06Z1VXVK13","huamu","01M6DK1VBYG1BX5FT154AFZHAS",0,"MIT","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Fpatents-search\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"patents search","search","semantic-search","innovation-tracking","intellectual-property","prior-art","patent-search","patents","semantic","natural language","language","queries","Art","innovation","patent","global","tracking","2026-11-10 10:12:30",false,"---\nname: patents-search\ndescription: Search global patents with natural language queries. Prior art, patent landscapes, and innovation tracking via Valyu.\nkeywords:\n  - patents\n  - patent-search\n  - prior-art\n  - intellectual-property\n  - innovation-tracking\n  - semantic-search\nlicense: MIT\n---\n\n\n# Patents Search\n\nSearch the complete global patent database using natural language queries powered by Valyu's semantic search API.\n\n## Why This Skill is Powerful\n\n- **No API Parameter Parsing**: Just pass natural language queries directly - no need to construct complex search parameters\n- **Semantic Search**: Understands the meaning of your query, not just keyword matching\n- **Full-Text Access**: Returns complete patent information including claims, descriptions, and technical details\n- **Image Links**: Includes patent diagrams and figures when available\n- **Comprehensive Coverage**: Access to global patent data across jurisdictions\n\n## Requirements\n\n1. Node.js 18+ (uses built-in fetch)\n2. Valyu API key from https:\u002F\u002Fplatform.valyu.ai ($10 free credits)\n\n## CRITICAL: Script Path Resolution\n\nThe `scripts\u002Fsearch` commands in this documentation are relative to this skill's installation directory.\n\nBefore running any command, locate the script using:\n\n```bash\nPATENTS_SCRIPT=$(find ~\u002F.claude\u002Fplugins\u002Fcache -name \"search\" -path \"*\u002Fpatents-search\u002F*\u002Fscripts\u002F*\" -type f 2>\u002Fdev\u002Fnull | head -1)\n```\n\nThen use the full path for all commands:\n```bash\n$PATENTS_SCRIPT \"CRISPR gene editing methods\" 15\n```\n\n## API Key Setup Flow\n\nWhen you run a search and receive `\"setup_required\": true`, follow this flow:\n\n1. **Ask the user for their API key:**\n   \"To search patents, I need your Valyu API key. Get one free ($10 credits) at https:\u002F\u002Fplatform.valyu.ai\"\n\n2. **Once the user provides the key, run:**\n   ```bash\n   scripts\u002Fsearch setup \u003Capi-key>\n   ```\n\n3. **Retry the original search.**\n\n## When to Use This Skill\n\n- Prior art searching and patent landscaping\n- Technology trend analysis\n- Competitor innovation tracking\n- Patent freedom-to-operate analysis\n- Patent claim analysis and interpretation\n- Patent filing strategy research\n## Output Format\n\n```json\n{\n  \"success\": true,\n  \"type\": \"patents_search\",\n  \"query\": \"CRISPR gene editing methods\",\n  \"result_count\": 10,\n  \"results\": [\n    {\n      \"title\": \"Patent Title\",\n      \"url\": \"https:\u002F\u002Fpatents.google.com\u002F...\",\n      \"content\": \"Patent claims, description, technical details...\",\n      \"source\": \"patents\",\n      \"relevance_score\": 0.95,\n      \"images\": [\"https:\u002F\u002Fexample.com\u002Fdiagram.png\"]\n    }\n  ],\n  \"cost\": 0.025\n}\n```\n\n## Processing Results\n\n### With jq\n\n```bash\n# Get patent titles\nscripts\u002Fsearch \"query\" 10 | jq -r '.results[].title'\n\n# Get URLs\nscripts\u002Fsearch \"query\" 10 | jq -r '.results[].url'\n\n# Extract full content\nscripts\u002Fsearch \"query\" 10 | jq -r '.results[].content'\n```\n\n## Common Use Cases\n\n### Prior Art Search\n\n```bash\n# Find prior art\nscripts\u002Fsearch \"lithium ion battery electrode materials\" 50\n```\n\n### Competitive Intelligence\n\n```bash\n# Search competitor patents\nscripts\u002Fsearch \"CAR-T cell therapy manufacturing methods\" 20\n```\n\n### Technology Landscape\n\n```bash\n# Find technology trends\nscripts\u002Fsearch \"quantum computing error correction patents\" 15\n```\n\n### Freedom to Operate\n\n```bash\n# Search for blocking patents\nscripts\u002Fsearch \"mRNA vaccine delivery systems\" 25\n```\n\n\n## Error Handling\n\nAll commands return JSON with `success` field:\n\n```json\n{\n  \"success\": false,\n  \"error\": \"Error message\"\n}\n```\n\nExit codes:\n- `0` - Success\n- `1` - Error (check JSON for details)\n\n## API Endpoint\n\n- Base URL: `https:\u002F\u002Fapi.valyu.ai\u002Fv1`\n- Endpoint: `\u002Fsearch`\n- Authentication: X-API-Key header\n\n## Architecture\n\n```\nscripts\u002F\n├── search          # Bash wrapper\n└── search.mjs      # Node.js CLI\n```\n\nDirect API calls using Node.js built-in `fetch()`, zero external dependencies.\n\n## Adding to Your Project\n\nIf you're building an AI project and want to integrate Patents Search directly into your application, use the Valyu SDK:\n\n### Python Integration\n\n```python\nfrom valyu import Valyu\n\nclient = Valyu(api_key=\"your-api-key\")\n\nresponse = client.search(\n    query=\"your search query here\",\n    included_sources=[\"valyu\u002Fvalyu-patents\"],\n    max_results=20\n)\n\nfor result in response[\"results\"]:\n    print(f\"Title: {result['title']}\")\n    print(f\"URL: {result['url']}\")\n    print(f\"Content: {result['content'][:500]}...\")\n```\n\n### TypeScript Integration\n\n```typescript\nimport { Valyu } from \"valyu-js\";\n\nconst client = new Valyu(\"your-api-key\");\n\nconst response = await client.search({\n  query: \"your search query here\",\n  includedSources: [\"valyu\u002Fvalyu-patents\"],\n  maxResults: 20\n});\n\nresponse.results.forEach((result) => {\n  console.log(`Title: ${result.title}`);\n  console.log(`URL: ${result.url}`);\n  console.log(`Content: ${result.content.substring(0, 500)}...`);\n});\n```\n\nSee the [Valyu docs](https:\u002F\u002Fdocs.valyu.ai) for full integration examples and SDK reference.\n","# Patents Search\n\nSearch the complete global patent database using natural language queries powered by Valyu's semantic search API.\n\n## Why This Skill is Powerful\n\n- **No API Parameter Parsing**: Just pass natural language queries directly - no need to construct complex search parameters\n- **Semantic Search**: Understands the meaning of your query, not just keyword matching\n- **Full-Text Access**: Returns complete patent information including claims, descriptions, and technical details\n- **Image Links**: Includes patent diagrams and figures when available\n- **Comprehensive Coverage**: Access to global patent data across jurisdictions\n\n## Requirements\n\n1. Node.js 18+ (uses built-in fetch)\n2. Valyu API key from https:\u002F\u002Fplatform.valyu.ai ($10 free credits)\n\n## CRITICAL: Script Path Resolution\n\nThe `scripts\u002Fsearch` commands in this documentation are relative to this skill's installation directory.\n\nBefore running any command, locate the script using:\n\n```bash\nPATENTS_SCRIPT=$(find ~\u002F.claude\u002Fplugins\u002Fcache -name \"search\" -path \"*\u002Fpatents-search\u002F*\u002Fscripts\u002F*\" -type f 2>\u002Fdev\u002Fnull | head -1)\n```\n\nThen use the full path for all commands:\n```bash\n$PATENTS_SCRIPT \"CRISPR gene editing methods\" 15\n```\n\n## API Key Setup Flow\n\nWhen you run a search and receive `\"setup_required\": true`, follow this flow:\n\n1. **Ask the user for their API key:**\n   \"To search patents, I need your Valyu API key. Get one free ($10 credits) at https:\u002F\u002Fplatform.valyu.ai\"\n\n2. **Once the user provides the key, run:**\n   ```bash\n   scripts\u002Fsearch setup \u003Capi-key>\n   ```\n\n3. **Retry the original search.**\n\n## When to Use This Skill\n\n- Prior art searching and patent landscaping\n- Technology trend analysis\n- Competitor innovation tracking\n- Patent freedom-to-operate analysis\n- Patent claim analysis and interpretation\n- Patent filing strategy research\n## Output Format\n\n```json\n{\n  \"success\": true,\n  \"type\": \"patents_search\",\n  \"query\": \"CRISPR gene editing methods\",\n  \"result_count\": 10,\n  \"results\": [\n    {\n      \"title\": \"Patent Title\",\n      \"url\": \"https:\u002F\u002Fpatents.google.com\u002F...\",\n      \"content\": \"Patent claims, description, technical details...\",\n      \"source\": \"patents\",\n      \"relevance_score\": 0.95,\n      \"images\": [\"https:\u002F\u002Fexample.com\u002Fdiagram.png\"]\n    }\n  ],\n  \"cost\": 0.025\n}\n```\n\n## Processing Results\n\n### With jq\n\n```bash\n# Get patent titles\nscripts\u002Fsearch \"query\" 10 | jq -r '.results[].title'\n\n# Get URLs\nscripts\u002Fsearch \"query\" 10 | jq -r '.results[].url'\n\n# Extract full content\nscripts\u002Fsearch \"query\" 10 | jq -r '.results[].content'\n```\n\n## Common Use Cases\n\n### Prior Art Search\n\n```bash\n# Find prior art\nscripts\u002Fsearch \"lithium ion battery electrode materials\" 50\n```\n\n### Competitive Intelligence\n\n```bash\n# Search competitor patents\nscripts\u002Fsearch \"CAR-T cell therapy manufacturing methods\" 20\n```\n\n### Technology Landscape\n\n```bash\n# Find technology trends\nscripts\u002Fsearch \"quantum computing error correction patents\" 15\n```\n\n### Freedom to Operate\n\n```bash\n# Search for blocking patents\nscripts\u002Fsearch \"mRNA vaccine delivery systems\" 25\n```\n\n\n## Error Handling\n\nAll commands return JSON with `success` field:\n\n```json\n{\n  \"success\": false,\n  \"error\": \"Error message\"\n}\n```\n\nExit codes:\n- `0` - Success\n- `1` - Error (check JSON for details)\n\n## API Endpoint\n\n- Base URL: `https:\u002F\u002Fapi.valyu.ai\u002Fv1`\n- Endpoint: `\u002Fsearch`\n- Authentication: X-API-Key header\n\n## Architecture\n\n```\nscripts\u002F\n├── search          # Bash wrapper\n└── search.mjs      # Node.js CLI\n```\n\nDirect API calls using Node.js built-in `fetch()`, zero external dependencies.\n\n## Adding to Your Project\n\nIf you're building an AI project and want to integrate Patents Search directly into your application, use the Valyu SDK:\n\n### Python Integration\n\n```python\nfrom valyu import Valyu\n\nclient = Valyu(api_key=\"your-api-key\")\n\nresponse = client.search(\n    query=\"your search query here\",\n    included_sources=[\"valyu\u002Fvalyu-patents\"],\n    max_results=20\n)\n\nfor result in response[\"results\"]:\n    print(f\"Title: {result['title']}\")\n    print(f\"URL: {result['url']}\")\n    print(f\"Content: {result['content'][:500]}...\")\n```\n\n### TypeScript Integration\n\n```typescript\nimport { Valyu } from \"valyu-js\";\n\nconst client = new Valyu(\"your-api-key\");\n\nconst response = await client.search({\n  query: \"your search query here\",\n  includedSources: [\"valyu\u002Fvalyu-patents\"],\n  maxResults: 20\n});\n\nresponse.results.forEach((result) => {\n  console.log(`Title: ${result.title}`);\n  console.log(`URL: ${result.url}`);\n  console.log(`Content: ${result.content.substring(0, 500)}...`);\n});\n```\n\nSee the [Valyu docs](https:\u002F\u002Fdocs.valyu.ai) for full integration examples and SDK reference.\n",{"name":5,"license":15,"keywords":46,"description":7},[31,30,29,28,27,26],"main","d3998984163a67a891ee8397e35adf79b14e872d","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical","https:\u002F\u002Fgithub.com\u002Fhuamu668","2026-03-12 11:49:42",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add huamu668\u002Fclawhub-openclaw-medical --skill patents-search",{"tool":58,"command":59},"bunx","bunx skills add huamu668\u002Fclawhub-openclaw-medical --skill patents-search",{"tool":61,"command":62},"pnpm","pnpm dlx skills add huamu668\u002Fclawhub-openclaw-medical --skill patents-search","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Fpatents-search\u002FSKILL.md",true,[],[67,87,116,136,149,176],{"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":73,"publishedAt":41},"01M6DR3JGAEX5G5FR7TK3D8NS8","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Fzarr-python\u002FSKILL.md",[],[74,75,76,77,78,79,80,81,82,83,84,85,86],"python","zarr python","storage","scientific computing","numpy","arrays","pipelines","parallel","dask","cloud","gcs","s3","integration",{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":96,"publishedAt":41},"01M6DR101MEDE5XT2ZZ5VBEAA5","vaex","Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV\u002FHDF5\u002FArrow\u002FParquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Fvaex\u002FSKILL.md",[93],{"categoryNo":94,"categoryName":95,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化",[89,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115],"machine learning","in memory","learning","csv","visualization","create","core","ml","big data","memory","visualizations","fit","statistics","do","build","files","use","operations","work",{"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":41},"01M6DQVMB0GBKF2W44FKXVD1P7","torch-geometric","Graph Neural Networks (PyG). Node\u002Fgraph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Ftorch-geometric\u002FSKILL.md",[],[123,99,124,125,126,127,128,129,130,131,132,133,134,135],"torch geometric","node","Neural","link","gat","molecular","graphs","deep","networks","graph","neural networks","deep learning","classification",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":142,"publishedAt":41},"01M6DQH2GZPZKEQ140GRCJ9746","tiledbvcf","Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF\u002FBCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Ftiledbvcf\u002FSKILL.md",[],[138,143,144,145,35,146,147,81,148,76],"data","genomics","sample","ingestion","export","capabilities",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":161,"publishedAt":41},"01M6DQD9G958EM6NHJ994D0SK1","solublempnn","Solubility-optimized protein sequence design using SolubleMPNN. Use this skill when: (1) Designing for E. coli expression, (2) Optimizing solubility of designed proteins, (3) Reducing aggregation propensity, (4) Need high-yield expression, (5) Avoiding inclusion body formation.\nFor standard design, use proteinmpnn. For ligand-aware design, use ligandmpnn.","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Fsolublempnn\u002FSKILL.md",[155,156],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":157,"categoryName":158,"taxonomyType":159,"taxonomyTypeDesc":160},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[151,162,163,113,164,165,166,167,168,169,170,171,172,173,174,175],"inclusion","yield","modal","Tools","aggregation","design","proteins","solubility","proteinmpnn","ligandmpnn","ligand-aware","inverse-folding","expression","sequence-design",{"skillNo":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":180,"licenseFileUrl":6,"sourceHtmlUrl":181,"categories":182,"keywords":183,"publishedAt":41},"01M6DQ8W91A93MGGCEEW949HBC","scvelo","RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced\u002Fspliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy\u002FscVI-tools for trajectory inference.","BSD-3-Clause","https:\u002F\u002Fgithub.com\u002Fhuamu668\u002Fclawhub-openclaw-medical\u002Fblob\u002Fmain\u002Fscvelo\u002FSKILL.md",[],[178,184,185,186,187,188,189,190,191,192,193,165,143,194,195],"RNA","single-cell","infer","cell","transitions","time","compute","velocity","scanpy","analysis","state","inference"]