[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M73FM7B8TTGS9TAVGQMSQSDX":3,"skill-same:01M73FM7B8TTGS9TAVGQMSQSDX":49},{"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":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":25,"commitSha":26,"skillDirectory":27,"forksCount":28,"repositoryHtmlUrl":29,"repositoryHomepageUrl":30,"ownerHtmlUrl":31,"ownerBlogUrl":32,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M73FM7B8TTGS9TAVGQMSQSDX","uspto-database",null,"USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.","Horonomos-laps\u002FYana-AI","Horonomos-laps","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F355299122?v=4","01M76B3QPXE88ET2SQPDPVATZT"," Horonomos-laps","01M72ZQRJPCYPSSWT4D00VJR2A",13,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fscientific-db-uspto-database\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: uspto-database\ndescription: USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.\norigin: community\n---\n\n# USPTO Database\n\nUse this skill when a task needs official United States patent or trademark\nrecords from USPTO systems.\n\n## When to Use\n\n- Searching granted patents or pre-grant publications.\n- Checking patent application status, file-wrapper data, assignments, or\n  public prosecution history.\n- Looking up trademark status, documents, or assignment history.\n- Building reproducible prior-art, portfolio, or IP landscape research logs.\n- Comparing USPTO records with secondary tools such as Google Patents,\n  Lens.org, Semantic Scholar, or company patent pages.\n\nDo not use this skill to give legal advice. Treat it as a data-gathering and\nrecord-verification workflow.\n\n## Source Selection\n\nPrefer official USPTO or USPTO-supported surfaces first:\n\n- Open Data Portal (ODP): current home for migrated USPTO datasets and APIs.\n- Patent File Wrapper: public patent application bibliographic data and file\n  wrapper records.\n- PatentSearch API: PatentsView search API for granted patents and pre-grant\n  publication datasets.\n- TSDR Data API: trademark status and document retrieval.\n- Patent and Trademark Assignment Search: ownership transfer records.\n- PTAB data in ODP: Patent Trial and Appeal Board proceedings.\n\nUse secondary sources only as convenience indexes. When the answer matters,\ncross-check the official record.\n\n## Authentication and Secrets\n\nMany USPTO API flows require an API key. Store keys in environment variables or\na secret manager, never in committed files or pasted transcripts.\n\nCommon environment names:\n\n```bash\nexport USPTO_API_KEY=\"...\"\nexport PATENTSVIEW_API_KEY=\"...\"\n```\n\nFor PatentSearch, send the key with the `X-Api-Key` header. For TSDR, follow\nthe current USPTO API Manager instructions and rate-limit guidance.\n\n## PatentSearch Workflow\n\nUse PatentSearch for broad patent and pre-grant publication search when the\nquestion is about trends, inventors, assignees, classifications, dates, or\nportfolio slices.\n\nWorkflow:\n\n1. Identify the endpoint from the current PatentSearch reference or Swagger UI.\n2. Build a JSON query with explicit filters.\n3. Request only the fields needed for the analysis.\n4. Sort and paginate deterministically.\n5. Record the endpoint, query body, date, data currency note, and result count.\n\nPython request skeleton:\n\n```python\nimport os\nimport requests\n\nAPI_KEY = os.environ[\"PATENTSVIEW_API_KEY\"]\nBASE = \"https:\u002F\u002Fsearch.patentsview.org\u002Fapi\u002Fv1\"\n\npayload = {\n    \"q\": {\n        \"_and\": [\n            {\"patent_date\": {\"_gte\": \"2024-01-01\"}},\n            {\"assignees.assignee_organization\": {\"_text_any\": [\"Google\", \"Alphabet\"]}},\n        ]\n    },\n    \"f\": [\"patent_id\", \"patent_title\", \"patent_date\"],\n    \"s\": [{\"patent_date\": \"desc\"}],\n    \"o\": {\"per_page\": 100, \"page\": 1},\n}\n\nresponse = requests.post(\n    f\"{BASE}\u002Fpatent\u002F\",\n    headers={\"X-Api-Key\": API_KEY, \"Content-Type\": \"application\u002Fjson\"},\n    json=payload,\n    timeout=30,\n)\nresponse.raise_for_status()\nprint(response.json())\n```\n\nBefore reusing a query, verify current endpoint names, field paths, request\nparameters, and API-key availability in the live PatentSearch docs.\n\n## Trademark\u002FTSDR Workflow\n\nUse TSDR when the task needs trademark case status, documents, images, owner\nhistory, or prosecution events.\n\nWorkflow:\n\n1. Normalize the serial number or registration number.\n2. Check the current TSDR API instructions and required API-key header.\n3. Fetch status first, then documents only if needed.\n4. Respect the lower rate limit for PDF, ZIP, and multi-case downloads.\n5. Capture retrieval date and serial\u002Fregistration identifier in the output.\n\nFor large trademark pulls, prefer documented bulk-data flows rather than\nscreen-scraping public pages.\n\n## File Wrapper and Prosecution History\n\nFor application status, transaction history, and prosecution documents:\n\n- Start with ODP Patent File Wrapper search.\n- Use exact identifiers when available: application number, publication number,\n  patent number, or party name.\n- Record whether the record is a granted patent, pre-grant publication, or\n  pending application.\n- Cross-check document dates and status against the record detail page before\n  citing them.\n\n## Assignment Workflow\n\nFor patent or trademark ownership:\n\n1. Search official assignment data by patent\u002Fapplication\u002Fregistration number,\n   assignor, assignee, or reel\u002Fframe when available.\n2. Record conveyance text, execution date, recordation date, and parties.\n3. Distinguish assignment records from current legal ownership conclusions.\n4. If ownership is material, flag the result for attorney or subject-matter\n   review.\n\n## Reproducible Output\n\nEvery USPTO research pass should include a log table:\n\n```markdown\n| Source | Date searched | Identifier\u002Fquery | Filters | Results | Notes |\n| --- | --- | --- | --- | ---: | --- |\n| PatentSearch | 2026-05-11 | `assignee=Alphabet AND date>=2024` | patent endpoint | 118 | API docs checked before run |\n| TSDR | 2026-05-11 | `serial=90000000` | status only | 1 | API-key flow, no document bulk pull |\n```\n\nFor final writeups, separate:\n\n- official record facts\n- inferred analysis\n- secondary-source convenience matches\n- unresolved gaps or records that require legal review\n\n## Review Checklist\n\n- Did you use an official USPTO or USPTO-supported source first?\n- Did you verify current endpoint and field names before running code?\n- Are API keys kept out of files, shell history, and output logs?\n- Does the query log include the date searched and exact request shape?\n- Are rate limits respected?\n- Are legal conclusions avoided or explicitly escalated?\n- Are secondary sources labeled as secondary?\n\n## References\n\n- [USPTO APIs catalog](https:\u002F\u002Fdeveloper.uspto.gov\u002Fapi-catalog)\n- [USPTO Open Data Portal](https:\u002F\u002Fdata.uspto.gov\u002F)\n- [PatentSearch API reference](https:\u002F\u002Fsearch.patentsview.org\u002Fdocs\u002Fdocs\u002FSearch%20API\u002FSearchAPIReference\u002F)\n- [PatentSearch API updates](https:\u002F\u002Fsearch.patentsview.org\u002Fdocs\u002F)\n- [TSDR API bulk download FAQ](https:\u002F\u002Fdeveloper.uspto.gov\u002Ffaq\u002Ftsdr-api-bulk-download)\n","# USPTO Database\n\nUse this skill when a task needs official United States patent or trademark\nrecords from USPTO systems.\n\n## When to Use\n\n- Searching granted patents or pre-grant publications.\n- Checking patent application status, file-wrapper data, assignments, or\n  public prosecution history.\n- Looking up trademark status, documents, or assignment history.\n- Building reproducible prior-art, portfolio, or IP landscape research logs.\n- Comparing USPTO records with secondary tools such as Google Patents,\n  Lens.org, Semantic Scholar, or company patent pages.\n\nDo not use this skill to give legal advice. Treat it as a data-gathering and\nrecord-verification workflow.\n\n## Source Selection\n\nPrefer official USPTO or USPTO-supported surfaces first:\n\n- Open Data Portal (ODP): current home for migrated USPTO datasets and APIs.\n- Patent File Wrapper: public patent application bibliographic data and file\n  wrapper records.\n- PatentSearch API: PatentsView search API for granted patents and pre-grant\n  publication datasets.\n- TSDR Data API: trademark status and document retrieval.\n- Patent and Trademark Assignment Search: ownership transfer records.\n- PTAB data in ODP: Patent Trial and Appeal Board proceedings.\n\nUse secondary sources only as convenience indexes. When the answer matters,\ncross-check the official record.\n\n## Authentication and Secrets\n\nMany USPTO API flows require an API key. Store keys in environment variables or\na secret manager, never in committed files or pasted transcripts.\n\nCommon environment names:\n\n```bash\nexport USPTO_API_KEY=\"...\"\nexport PATENTSVIEW_API_KEY=\"...\"\n```\n\nFor PatentSearch, send the key with the `X-Api-Key` header. For TSDR, follow\nthe current USPTO API Manager instructions and rate-limit guidance.\n\n## PatentSearch Workflow\n\nUse PatentSearch for broad patent and pre-grant publication search when the\nquestion is about trends, inventors, assignees, classifications, dates, or\nportfolio slices.\n\nWorkflow:\n\n1. Identify the endpoint from the current PatentSearch reference or Swagger UI.\n2. Build a JSON query with explicit filters.\n3. Request only the fields needed for the analysis.\n4. Sort and paginate deterministically.\n5. Record the endpoint, query body, date, data currency note, and result count.\n\nPython request skeleton:\n\n```python\nimport os\nimport requests\n\nAPI_KEY = os.environ[\"PATENTSVIEW_API_KEY\"]\nBASE = \"https:\u002F\u002Fsearch.patentsview.org\u002Fapi\u002Fv1\"\n\npayload = {\n    \"q\": {\n        \"_and\": [\n            {\"patent_date\": {\"_gte\": \"2024-01-01\"}},\n            {\"assignees.assignee_organization\": {\"_text_any\": [\"Google\", \"Alphabet\"]}},\n        ]\n    },\n    \"f\": [\"patent_id\", \"patent_title\", \"patent_date\"],\n    \"s\": [{\"patent_date\": \"desc\"}],\n    \"o\": {\"per_page\": 100, \"page\": 1},\n}\n\nresponse = requests.post(\n    f\"{BASE}\u002Fpatent\u002F\",\n    headers={\"X-Api-Key\": API_KEY, \"Content-Type\": \"application\u002Fjson\"},\n    json=payload,\n    timeout=30,\n)\nresponse.raise_for_status()\nprint(response.json())\n```\n\nBefore reusing a query, verify current endpoint names, field paths, request\nparameters, and API-key availability in the live PatentSearch docs.\n\n## Trademark\u002FTSDR Workflow\n\nUse TSDR when the task needs trademark case status, documents, images, owner\nhistory, or prosecution events.\n\nWorkflow:\n\n1. Normalize the serial number or registration number.\n2. Check the current TSDR API instructions and required API-key header.\n3. Fetch status first, then documents only if needed.\n4. Respect the lower rate limit for PDF, ZIP, and multi-case downloads.\n5. Capture retrieval date and serial\u002Fregistration identifier in the output.\n\nFor large trademark pulls, prefer documented bulk-data flows rather than\nscreen-scraping public pages.\n\n## File Wrapper and Prosecution History\n\nFor application status, transaction history, and prosecution documents:\n\n- Start with ODP Patent File Wrapper search.\n- Use exact identifiers when available: application number, publication number,\n  patent number, or party name.\n- Record whether the record is a granted patent, pre-grant publication, or\n  pending application.\n- Cross-check document dates and status against the record detail page before\n  citing them.\n\n## Assignment Workflow\n\nFor patent or trademark ownership:\n\n1. Search official assignment data by patent\u002Fapplication\u002Fregistration number,\n   assignor, assignee, or reel\u002Fframe when available.\n2. Record conveyance text, execution date, recordation date, and parties.\n3. Distinguish assignment records from current legal ownership conclusions.\n4. If ownership is material, flag the result for attorney or subject-matter\n   review.\n\n## Reproducible Output\n\nEvery USPTO research pass should include a log table:\n\n```markdown\n| Source | Date searched | Identifier\u002Fquery | Filters | Results | Notes |\n| --- | --- | --- | --- | ---: | --- |\n| PatentSearch | 2026-05-11 | `assignee=Alphabet AND date>=2024` | patent endpoint | 118 | API docs checked before run |\n| TSDR | 2026-05-11 | `serial=90000000` | status only | 1 | API-key flow, no document bulk pull |\n```\n\nFor final writeups, separate:\n\n- official record facts\n- inferred analysis\n- secondary-source convenience matches\n- unresolved gaps or records that require legal review\n\n## Review Checklist\n\n- Did you use an official USPTO or USPTO-supported source first?\n- Did you verify current endpoint and field names before running code?\n- Are API keys kept out of files, shell history, and output logs?\n- Does the query log include the date searched and exact request shape?\n- Are rate limits respected?\n- Are legal conclusions avoided or explicitly escalated?\n- Are secondary sources labeled as secondary?\n\n## References\n\n- [USPTO APIs catalog](https:\u002F\u002Fdeveloper.uspto.gov\u002Fapi-catalog)\n- [USPTO Open Data Portal](https:\u002F\u002Fdata.uspto.gov\u002F)\n- [PatentSearch API reference](https:\u002F\u002Fsearch.patentsview.org\u002Fdocs\u002Fdocs\u002FSearch%20API\u002FSearchAPIReference\u002F)\n- [PatentSearch API updates](https:\u002F\u002Fsearch.patentsview.org\u002Fdocs\u002F)\n- [TSDR API bulk download FAQ](https:\u002F\u002Fdeveloper.uspto.gov\u002Ffaq\u002Ftsdr-api-bulk-download)\n",{"name":5,"origin":24,"description":7},"community","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa","core\u002Fskills\u002Fscientific-db-uspto-database",1,"https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI","https:\u002F\u002Fyana.vutam.link\u002F","https:\u002F\u002Fgithub.com\u002FHoronomos-laps","https:\u002F\u002Fyana.vutam.link","An open-source governed runtime & execution environment for multi-agent AI systems.","2026-11-11 23:56:26",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill uspto-database",{"tool":41,"command":42},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill uspto-database",{"tool":44,"command":45},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill uspto-database","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fscientific-db-uspto-database\u002FSKILL.md",true,[],[50,58,65,73,81,89],{"skillNo":51,"name":52,"nameZh":6,"description":53,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":54,"licenseFileUrl":6,"sourceHtmlUrl":55,"categories":56,"keywords":57,"publishedAt":19},"01M735GKET5YVYKAY62W2P5YXB","openai--sentry--sentry","Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.","MIT","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fopenai--sentry--sentry\u002FSKILL.md",[],[],{"skillNo":59,"name":60,"nameZh":6,"description":61,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":62,"categories":63,"keywords":64,"publishedAt":19},"01M73DCAP83T17HY7SMGK7MGFE","ito-basket-compare","Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. Use for read-only basket comparison and gap analysis without investment advice or live trading.","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fito-basket-compare\u002FSKILL.md",[],[],{"skillNo":66,"name":67,"nameZh":6,"description":68,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":69,"sourceHtmlUrl":70,"categories":71,"keywords":72,"publishedAt":19},"01M734CYEMZFDR3KH6SW0JP8TD","implementing-network-traffic-baselining","Build network traffic baselines from NetFlow\u002FIPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly\u002Fdaily traffic pattern profiling","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FSKILL.md",[],[],{"skillNo":74,"name":75,"nameZh":6,"description":76,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":77,"sourceHtmlUrl":78,"categories":79,"keywords":80,"publishedAt":19},"01M73ASZ6NJRJM44Z2P84NGQ3Q","detecting-evasion-techniques-in-endpoint-logs","Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FSKILL.md",[],[],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":85,"sourceHtmlUrl":86,"categories":87,"keywords":88,"publishedAt":19},"01M734AFNXD06Z78QRK0VKGT7Q","implementing-microsegmentation-with-guardicore","Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FSKILL.md",[],[],{"skillNo":90,"name":91,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":19},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]