[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KFRDEVX2G39501D5XDD8PG":3,"skill-same:01M6KFRDEVX2G39501D5XDD8PG":56},{"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":29,"linkOnly":30,"markdownContent":31,"markdownBody":32,"frontMatter":33,"refName":34,"commitSha":35,"skillDirectory":36,"forksCount":37,"repositoryHtmlUrl":38,"repositoryHomepageUrl":39,"ownerHtmlUrl":40,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":41,"install":42,"resources":55},"01M6KFRDEVX2G39501D5XDD8PG","run2_fuzzy-fund-search",null,"Fuzzy search for hedge funds or stocks by name in SEC 13F filings; handles cases where rank 1 is skipped due to amendment filtering.","cxcscmu\u002FSkillLearnBench","cxcscmu","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F142838272?v=4","01M6KCQDFQWPDSN0MKZY96MSQP","01M6KCQDM7G70TKJ28NTSQC0RZ",93,"MIT","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Ffinancial-analysis\u002Frun2_fuzzy-fund-search\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28],"search","fund","fuzzy fund search","run2 fuzzy fund search","filtering","stocks","name","filings","13f","for","fuzzy search","2026-11-10 10:12:30",false,"---\nname: run2_fuzzy-fund-search\ndescription: Fuzzy search for hedge funds or stocks by name in SEC 13F filings; handles cases where rank 1 is skipped due to amendment filtering.\n---\n\n# Fuzzy Fund and Stock Search (Improved)\n\n## Overview\nUses Levenshtein-based fuzzy search to find fund names and stock CUSIPs in SEC 13F data.\n\n## Setup\n- Scripts: `\u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002F`\n- Data: `\u002Froot\u002F2025-q2\u002F` and `\u002Froot\u002F2025-q3\u002F`\n\n## IMPORTANT: Rank 1 May Be Skipped\nThe `search_fund.py` script filters out amendments (`ISAMENDMENT == 'N'`). If the best match only has amendments, rank 1 is silently skipped and output starts from rank 2.\n\n**Workaround**: Always grep COVERPAGE.tsv directly when the fund isn't in rank 1:\n```bash\ngrep -i \"renaissance technologies\" \u002Froot\u002F2025-q3\u002FCOVERPAGE.tsv\n```\nThis gives the raw row with ACCESSION_NUMBER (column 1) and FILINGMANAGER_NAME.\n\n## Search a Fund by Name\n\n```bash\npython3 \u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002Fsearch_fund.py \\\n    --keywords \"renaissance technologies\" \\\n    --quarter 2025-q3 \\\n    --topk 5\n```\n\nIf rank 1 is missing, use grep fallback (see above).\n\n## Search a Fund by Accession Number\n\n```bash\npython3 \u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002Fsearch_fund.py \\\n    --accession_number 0001037389-25-000064 \\\n    --quarter 2025-q3\n```\n\n## Search a Stock CUSIP by Name\n\n```bash\npython3 \u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002Fsearch_stock_cusip.py \\\n    --keywords \"palantir\" \\\n    --topk 3\n```\n\nReturns consistent CUSIP regardless of rank (same stock repeated): `69608A108` for Palantir.\n\n## Known Fund Accession Numbers (Q3 2025)\n- Renaissance Technologies LLC: `0001037389-25-000064`\n- Berkshire Hathaway Inc (Q3): `0001193125-25-282901`\n- Berkshire Hathaway Inc (Q2): `0000950123-25-008343`\n","# Fuzzy Fund and Stock Search (Improved)\n\n## Overview\nUses Levenshtein-based fuzzy search to find fund names and stock CUSIPs in SEC 13F data.\n\n## Setup\n- Scripts: `\u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002F`\n- Data: `\u002Froot\u002F2025-q2\u002F` and `\u002Froot\u002F2025-q3\u002F`\n\n## IMPORTANT: Rank 1 May Be Skipped\nThe `search_fund.py` script filters out amendments (`ISAMENDMENT == 'N'`). If the best match only has amendments, rank 1 is silently skipped and output starts from rank 2.\n\n**Workaround**: Always grep COVERPAGE.tsv directly when the fund isn't in rank 1:\n```bash\ngrep -i \"renaissance technologies\" \u002Froot\u002F2025-q3\u002FCOVERPAGE.tsv\n```\nThis gives the raw row with ACCESSION_NUMBER (column 1) and FILINGMANAGER_NAME.\n\n## Search a Fund by Name\n\n```bash\npython3 \u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002Fsearch_fund.py \\\n    --keywords \"renaissance technologies\" \\\n    --quarter 2025-q3 \\\n    --topk 5\n```\n\nIf rank 1 is missing, use grep fallback (see above).\n\n## Search a Fund by Accession Number\n\n```bash\npython3 \u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002Fsearch_fund.py \\\n    --accession_number 0001037389-25-000064 \\\n    --quarter 2025-q3\n```\n\n## Search a Stock CUSIP by Name\n\n```bash\npython3 \u002Froot\u002F.claude\u002Fskills\u002Ffuzzy-name-search\u002Fscripts\u002Fsearch_stock_cusip.py \\\n    --keywords \"palantir\" \\\n    --topk 3\n```\n\nReturns consistent CUSIP regardless of rank (same stock repeated): `69608A108` for Palantir.\n\n## Known Fund Accession Numbers (Q3 2025)\n- Renaissance Technologies LLC: `0001037389-25-000064`\n- Berkshire Hathaway Inc (Q3): `0001193125-25-282901`\n- Berkshire Hathaway Inc (Q2): `0000950123-25-008343`\n",{"name":5,"description":7},"main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Ffinancial-analysis\u002Frun2_fuzzy-fund-search",7,"https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench","https:\u002F\u002Fcxcscmu.github.io\u002FSkillLearnBench","https:\u002F\u002Fgithub.com\u002Fcxcscmu","2026-10-02 22:55:36",{"source":8,"skillName":5,"commands":43,"prompt":53,"zipAvailable":54},[44,47,50],{"tool":45,"command":46},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill run2_fuzzy-fund-search",{"tool":48,"command":49},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill run2_fuzzy-fund-search",{"tool":51,"command":52},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill run2_fuzzy-fund-search","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Ffinancial-analysis\u002Frun2_fuzzy-fund-search\u002FSKILL.md",true,[],[57,75,99,116,136,148],{"skillNo":58,"name":59,"nameZh":6,"description":60,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":61,"categories":62,"keywords":68,"publishedAt":29},"01M6KM5KH175P5ABP5JMX2SBDQ","object_counter","Count occurrences of an object in the image using computer vision algorithm.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Fvideo-object-counting\u002Fobject_counter\u002FSKILL.md",[63],{"categoryNo":64,"categoryName":65,"taxonomyType":66,"taxonomyTypeDesc":67},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[69,70,71,72,73,74],"object counter","object","vision","computer","Computer Vision","image",{"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":84,"publishedAt":29},"01M6KM51TMVXG79MMPCS6Y8G86","travel-planning-workflow","Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftravel-planning\u002Ftravel-planning-workflow\u002FSKILL.md",[81],{"categoryNo":82,"categoryName":83,"taxonomyType":66,"taxonomyTypeDesc":67},"01JBSEEDCAT000000000000023","Skill与智能体开发",[85,86,87,88,89,90,91,92,93,27,94,95,96,97,98],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","structured","performing","plan","user","it","requirements","essential","itineraries",{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":29},"01M6KM4DY820XHS9YTSK5QP5HD","bundled-dataset-search-tool","invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftravel-planning\u002Fbundled-dataset-search-tool\u002FSKILL.md",[],[18,106,107,108,109,110,111,88,112,113,89,114,27,115,86],"tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":122,"publishedAt":29},"01M6KM465BB9PQ0B548HQSVAWZ","glm-output","Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final \u002Froot\u002Fmetrics.json.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftemperature-simulation\u002Fglm-output\u002FSKILL.md",[],[123,124,125,27,126,127,128,129,130,131,132,133,114,134,135],"glm output","output","glm","tasks","metrics","json","basics","guidance","matching","verifier","processing","root","calibration",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":143,"publishedAt":29},"01M6KM40KY3QWDW5W97S39R2BC","glm-calibration","Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftemperature-simulation\u002Fglm-calibration\u002FSKILL.md",[142],{"categoryNo":82,"categoryName":83,"taxonomyType":66,"taxonomyTypeDesc":67},[144,135,125,124,130,129,126,145,146,27,147],"glm calibration","setup","companion","metric",{"skillNo":149,"name":150,"nameZh":6,"description":151,"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":154,"publishedAt":29},"01M6KM3VHHVSGMGHJQB3PPT6YG","glm-basics","A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftemperature-simulation\u002Fglm-basics\u002FSKILL.md",[],[155,125,129,156,144,135,27,124,157,158,159,160,161,162,126],"glm basics","inspect","relevant","files","good","use","how","Evaluation"]