[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KFS2SV71V3049Y63QR2W2B":3,"skill-same:01M6KFS2SV71V3049Y63QR2W2B":62},{"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":35,"linkOnly":36,"markdownContent":37,"markdownBody":38,"frontMatter":39,"refName":40,"commitSha":41,"skillDirectory":42,"forksCount":43,"repositoryHtmlUrl":44,"repositoryHomepageUrl":45,"ownerHtmlUrl":46,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":47,"install":48,"resources":61},"01M6KFS2SV71V3049Y63QR2W2B","run2_gh-issue-analysis",null,"How to identify bug report issues and count resolved bugs in a date range from GitHub Search API results.","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\u002Fgithub-repo-analytics\u002Frun2_gh-issue-analysis\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34],"run2 gh issue analysis","gh issue","analysis","issue","gh","how","github search api","bugs","how to","bug","results","github","api","search","issues","report","bug report","2026-11-10 10:12:30",false,"---\nname: run2_gh-issue-analysis\ndescription: How to identify bug report issues and count resolved bugs in a date range from GitHub Search API results.\n---\n\n# GitHub Issue Analysis: Bug Detection and Resolution\n\n## Bug Report Detection\nA bug report = issue with at least one label whose name contains the substring \"bug\" (case-insensitive).\n\nLabels from the Search API are returned as objects:\n```json\n\"labels\": [{\"id\": 1234, \"name\": \"type: bug\", \"color\": \"d73a4a\", ...}]\n```\n\n```python\ndef is_bug_report(issue):\n    \"\"\"Returns True if any label name contains 'bug' (case-insensitive).\"\"\"\n    labels = issue.get(\"labels\", [])\n    return any(\"bug\" in lbl.get(\"name\", \"\").lower() for lbl in labels)\n```\n\n## Counting Resolved Bugs\n\"Resolved bugs\" = bug report issues (created in the month) that were **closed** during the same month.\n\n```python\nMONTH_START = \"2024-12-01T00:00:00Z\"\nMONTH_END   = \"2025-01-01T00:00:00Z\"  # exclusive\n\ndef is_resolved_in_month(issue):\n    if issue.get(\"state\") != \"closed\":\n        return False\n    closed_at = issue.get(\"closed_at\") or \"\"\n    return MONTH_START \u003C= closed_at \u003C MONTH_END\n\nbug_issues = [i for i in issues if is_bug_report(i)]\nresolved_bugs = [i for i in bug_issues if is_resolved_in_month(i)]\n```\n\n## String Comparison for ISO 8601 Dates\nISO 8601 timestamps like `\"2024-12-15T10:30:00Z\"` are lexicographically sortable — direct string comparison `>=` and `\u003C` works correctly when all strings use the same format.\n\n## Complete Example\n```python\nissues = fetch_search(\"repo:cli\u002Fcli is:issue created:2024-12-01..2024-12-31\")\ntotal_issues = len(issues)\nbug_issues = [i for i in issues if is_bug_report(i)]\nresolved_bugs = [i for i in bug_issues if is_resolved_in_month(i)]\n\nprint(f\"Total issues: {total_issues}\")\nprint(f\"Bug reports:  {len(bug_issues)}\")\nprint(f\"Resolved bugs: {len(resolved_bugs)}\")\n```\n","# GitHub Issue Analysis: Bug Detection and Resolution\n\n## Bug Report Detection\nA bug report = issue with at least one label whose name contains the substring \"bug\" (case-insensitive).\n\nLabels from the Search API are returned as objects:\n```json\n\"labels\": [{\"id\": 1234, \"name\": \"type: bug\", \"color\": \"d73a4a\", ...}]\n```\n\n```python\ndef is_bug_report(issue):\n    \"\"\"Returns True if any label name contains 'bug' (case-insensitive).\"\"\"\n    labels = issue.get(\"labels\", [])\n    return any(\"bug\" in lbl.get(\"name\", \"\").lower() for lbl in labels)\n```\n\n## Counting Resolved Bugs\n\"Resolved bugs\" = bug report issues (created in the month) that were **closed** during the same month.\n\n```python\nMONTH_START = \"2024-12-01T00:00:00Z\"\nMONTH_END   = \"2025-01-01T00:00:00Z\"  # exclusive\n\ndef is_resolved_in_month(issue):\n    if issue.get(\"state\") != \"closed\":\n        return False\n    closed_at = issue.get(\"closed_at\") or \"\"\n    return MONTH_START \u003C= closed_at \u003C MONTH_END\n\nbug_issues = [i for i in issues if is_bug_report(i)]\nresolved_bugs = [i for i in bug_issues if is_resolved_in_month(i)]\n```\n\n## String Comparison for ISO 8601 Dates\nISO 8601 timestamps like `\"2024-12-15T10:30:00Z\"` are lexicographically sortable — direct string comparison `>=` and `\u003C` works correctly when all strings use the same format.\n\n## Complete Example\n```python\nissues = fetch_search(\"repo:cli\u002Fcli is:issue created:2024-12-01..2024-12-31\")\ntotal_issues = len(issues)\nbug_issues = [i for i in issues if is_bug_report(i)]\nresolved_bugs = [i for i in bug_issues if is_resolved_in_month(i)]\n\nprint(f\"Total issues: {total_issues}\")\nprint(f\"Bug reports:  {len(bug_issues)}\")\nprint(f\"Resolved bugs: {len(resolved_bugs)}\")\n```\n",{"name":5,"description":7},"main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Fgithub-repo-analytics\u002Frun2_gh-issue-analysis",8,"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":49,"prompt":59,"zipAvailable":60},[50,53,56],{"tool":51,"command":52},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill run2_gh-issue-analysis",{"tool":54,"command":55},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill run2_gh-issue-analysis",{"tool":57,"command":58},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill run2_gh-issue-analysis","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Fgithub-repo-analytics\u002Frun2_gh-issue-analysis\u002FSKILL.md",true,[],[63,81,106,123,143,155],{"skillNo":64,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":67,"categories":68,"keywords":74,"publishedAt":35},"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",[69],{"categoryNo":70,"categoryName":71,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[75,76,77,78,79,80],"object counter","object","vision","computer","Computer Vision","image",{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":90,"publishedAt":35},"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",[87],{"categoryNo":88,"categoryName":89,"taxonomyType":72,"taxonomyTypeDesc":73},"01JBSEEDCAT000000000000023","Skill与智能体开发",[91,92,93,94,95,96,97,98,99,100,101,102,103,104,105],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","structured","performing","plan","for","user","it","requirements","essential","itineraries",{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":35},"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",[],[31,113,114,115,116,117,118,94,119,120,95,121,100,122,92],"tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"skillNo":124,"name":125,"nameZh":6,"description":126,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":127,"categories":128,"keywords":129,"publishedAt":35},"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",[],[130,131,132,100,133,134,135,136,137,138,139,140,121,141,142],"glm output","output","glm","tasks","metrics","json","basics","guidance","matching","verifier","processing","root","calibration",{"skillNo":144,"name":145,"nameZh":6,"description":146,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":147,"categories":148,"keywords":150,"publishedAt":35},"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",[149],{"categoryNo":88,"categoryName":89,"taxonomyType":72,"taxonomyTypeDesc":73},[151,142,132,131,137,136,133,152,153,100,154],"glm calibration","setup","companion","metric",{"skillNo":156,"name":157,"nameZh":6,"description":158,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":161,"publishedAt":35},"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",[],[162,132,136,163,151,142,100,131,164,165,166,167,23,168,133],"glm basics","inspect","relevant","files","good","use","Evaluation"]