[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KH44RY9QCWCWE2F535A8WN":3,"skill-same:01M6KH44RY9QCWCWE2F535A8WN":68},{"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":22,"publishedAt":41,"linkOnly":42,"markdownContent":43,"markdownBody":44,"frontMatter":45,"refName":46,"commitSha":47,"skillDirectory":48,"forksCount":49,"repositoryHtmlUrl":50,"repositoryHomepageUrl":51,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M6KH44RY9QCWCWE2F535A8WN","compile-community-pulse-report-json",null,"How to compile PR and issue statistics into a report.json file for a GitHub repository community pulse report, using jq to build the final JSON structure.","cxcscmu\u002FSkillLearnBench","cxcscmu","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F142838272?v=4","01M6KCQDFQWPDSN0MKZY96MSQP","01M6KCQDM7G70TKJ28NTSQC0RZ",92,"MIT","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb3-teacher-feedback-claude-opus-4-6\u002Fgithub-repo-analytics\u002Frun3_compile-community-pulse-report-json\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"pulse","compile community pulse report json","community","json","compile","report","file","repository","how","jq","github","issue","build","structure","statistics","how to","for","pr","2026-11-10 10:12:30",false,"---\nname: compile-community-pulse-report-json\ndescription: How to compile PR and issue statistics into a report.json file for a GitHub repository community pulse report, using jq to build the final JSON structure.\n---\n\n# Compiling a Community Pulse report.json\n\n## Overall Workflow\n\n1. Fetch PR data with precise repo and date scoping\n2. Fetch issue data excluding PRs\n3. Compute all metrics\n4. Assemble into a single JSON file\n\n## Step-by-Step Script\n\n```bash\n#!\u002Fbin\u002Fbash\nset -e\n\nREPO=\"cli\u002Fcli\"\nSTART=\"2024-12-01\"\nEND=\"2024-12-31\"\n\n# --- Pull Requests ---\n\n# Fetch all PRs created in the date range (use gh pr list for repo-scoped accuracy)\ngh pr list --repo \"$REPO\" --search \"created:${START}..${END}\" --state all --limit 300 \\\n  --json number,author,state,createdAt,mergedAt > \u002Ftmp\u002Fprs.json\n\n# Total PRs\nPR_TOTAL=$(jq length \u002Ftmp\u002Fprs.json)\n\n# Merged PRs (mergedAt is not null and not empty)\nPR_MERGED=$(jq '[.[] | select(.mergedAt != null and .mergedAt != \"\")] | length' \u002Ftmp\u002Fprs.json)\n\n# Closed without merge (state != \"open\" and not merged)\n# Note: state for merged PRs may be \"MERGED\" or \"merged\" depending on gh version\nPR_CLOSED=$(jq '[.[] | select(\n  (.state == \"closed\" or .state == \"CLOSED\") and\n  (.mergedAt == null or .mergedAt == \"\")\n)] | length' \u002Ftmp\u002Fprs.json)\n\n# Average merge time in days\nAVG_MERGE=$(jq '\n  [.[] | select(.mergedAt != null and .mergedAt != \"\") |\n    (((.mergedAt | fromdateiso8601) - (.createdAt | fromdateiso8601)) \u002F 86400)\n  ] | if length > 0 then (add \u002F length * 10 | round \u002F 10) else 0 end\n' \u002Ftmp\u002Fprs.json)\n\n# Top contributor (person who opened the most PRs)\nTOP_CONTRIBUTOR=$(jq -r '\n  [.[] | .author.login] | group_by(.) |\n  map({login: .[0], count: length}) |\n  sort_by(-.count) | .[0].login\n' \u002Ftmp\u002Fprs.json)\n\n# --- Issues ---\n\n# Fetch all issues created in the date range (gh issue list excludes PRs)\ngh issue list --repo \"$REPO\" --search \"created:${START}..${END}\" --state all --limit 300 \\\n  --json number,labels,state,createdAt,closedAt > \u002Ftmp\u002Fissues.json\n\n# Total issues\nISSUE_TOTAL=$(jq length \u002Ftmp\u002Fissues.json)\n\n# Bug reports (any label containing substring \"bug\", case-insensitive)\nBUG_COUNT=$(jq '[.[] | select(.labels | map(.name) | any(test(\"bug\";\"i\")))] | length' \u002Ftmp\u002Fissues.json)\n\n# Resolved bugs (bug reports that are currently closed)\nRESOLVED_BUGS=$(jq '[.[] | select(\n  (.state == \"closed\" or .state == \"CLOSED\") and\n  (.labels | map(.name) | any(test(\"bug\";\"i\")))\n)] | length' \u002Ftmp\u002Fissues.json)\n\n# --- Assemble JSON ---\njq -n \\\n  --argjson pr_total \"$PR_TOTAL\" \\\n  --argjson pr_merged \"$PR_MERGED\" \\\n  --argjson pr_closed \"$PR_CLOSED\" \\\n  --argjson avg_merge \"$AVG_MERGE\" \\\n  --arg top \"$TOP_CONTRIBUTOR\" \\\n  --argjson issue_total \"$ISSUE_TOTAL\" \\\n  --argjson bug \"$BUG_COUNT\" \\\n  --argjson resolved \"$RESOLVED_BUGS\" \\\n  '{\n    pr: {\n      total: $pr_total,\n      merged: $pr_merged,\n      closed: $pr_closed,\n      avg_merge_days: $avg_merge,\n      top_contributor: $top\n    },\n    issue: {\n      total: $issue_total,\n      bug: $bug,\n      resolved_bugs: $resolved\n    }\n  }' > \u002Fapp\u002Freport.json\n\ncat \u002Fapp\u002Freport.json\n```\n\n## Key Points\n\n- **`closed` in PR section** = closed WITHOUT merge (not all closed PRs)\n- **`gh issue list`** inherently excludes PRs, unlike `gh search issues`\n- **`gh pr list`** is repo-scoped and won't include fork PRs\n- **Bug detection** uses case-insensitive substring match on label names for \"bug\"\n- **`avg_merge_days`** is rounded to 1 decimal place\n- **`top_contributor`** is the author login who opened the most PRs in the period\n\n## Debugging Tips\n\nIf counts seem off:\n1. Check that `createdAt` dates are within range: `jq '[.[] | .createdAt] | sort' \u002Ftmp\u002Fprs.json`\n2. Check for PR contamination in issues: `jq '[.[] | .url \u002F\u002F .number]' \u002Ftmp\u002Fissues.json`\n3. Verify merged detection: `jq '[.[] | {number, state, mergedAt}]' \u002Ftmp\u002Fprs.json`\n4. Cross-reference totals with GitHub web UI search: `repo:cli\u002Fcli is:pr created:2024-12-01..2024-12-31`","# Compiling a Community Pulse report.json\n\n## Overall Workflow\n\n1. Fetch PR data with precise repo and date scoping\n2. Fetch issue data excluding PRs\n3. Compute all metrics\n4. Assemble into a single JSON file\n\n## Step-by-Step Script\n\n```bash\n#!\u002Fbin\u002Fbash\nset -e\n\nREPO=\"cli\u002Fcli\"\nSTART=\"2024-12-01\"\nEND=\"2024-12-31\"\n\n# --- Pull Requests ---\n\n# Fetch all PRs created in the date range (use gh pr list for repo-scoped accuracy)\ngh pr list --repo \"$REPO\" --search \"created:${START}..${END}\" --state all --limit 300 \\\n  --json number,author,state,createdAt,mergedAt > \u002Ftmp\u002Fprs.json\n\n# Total PRs\nPR_TOTAL=$(jq length \u002Ftmp\u002Fprs.json)\n\n# Merged PRs (mergedAt is not null and not empty)\nPR_MERGED=$(jq '[.[] | select(.mergedAt != null and .mergedAt != \"\")] | length' \u002Ftmp\u002Fprs.json)\n\n# Closed without merge (state != \"open\" and not merged)\n# Note: state for merged PRs may be \"MERGED\" or \"merged\" depending on gh version\nPR_CLOSED=$(jq '[.[] | select(\n  (.state == \"closed\" or .state == \"CLOSED\") and\n  (.mergedAt == null or .mergedAt == \"\")\n)] | length' \u002Ftmp\u002Fprs.json)\n\n# Average merge time in days\nAVG_MERGE=$(jq '\n  [.[] | select(.mergedAt != null and .mergedAt != \"\") |\n    (((.mergedAt | fromdateiso8601) - (.createdAt | fromdateiso8601)) \u002F 86400)\n  ] | if length > 0 then (add \u002F length * 10 | round \u002F 10) else 0 end\n' \u002Ftmp\u002Fprs.json)\n\n# Top contributor (person who opened the most PRs)\nTOP_CONTRIBUTOR=$(jq -r '\n  [.[] | .author.login] | group_by(.) |\n  map({login: .[0], count: length}) |\n  sort_by(-.count) | .[0].login\n' \u002Ftmp\u002Fprs.json)\n\n# --- Issues ---\n\n# Fetch all issues created in the date range (gh issue list excludes PRs)\ngh issue list --repo \"$REPO\" --search \"created:${START}..${END}\" --state all --limit 300 \\\n  --json number,labels,state,createdAt,closedAt > \u002Ftmp\u002Fissues.json\n\n# Total issues\nISSUE_TOTAL=$(jq length \u002Ftmp\u002Fissues.json)\n\n# Bug reports (any label containing substring \"bug\", case-insensitive)\nBUG_COUNT=$(jq '[.[] | select(.labels | map(.name) | any(test(\"bug\";\"i\")))] | length' \u002Ftmp\u002Fissues.json)\n\n# Resolved bugs (bug reports that are currently closed)\nRESOLVED_BUGS=$(jq '[.[] | select(\n  (.state == \"closed\" or .state == \"CLOSED\") and\n  (.labels | map(.name) | any(test(\"bug\";\"i\")))\n)] | length' \u002Ftmp\u002Fissues.json)\n\n# --- Assemble JSON ---\njq -n \\\n  --argjson pr_total \"$PR_TOTAL\" \\\n  --argjson pr_merged \"$PR_MERGED\" \\\n  --argjson pr_closed \"$PR_CLOSED\" \\\n  --argjson avg_merge \"$AVG_MERGE\" \\\n  --arg top \"$TOP_CONTRIBUTOR\" \\\n  --argjson issue_total \"$ISSUE_TOTAL\" \\\n  --argjson bug \"$BUG_COUNT\" \\\n  --argjson resolved \"$RESOLVED_BUGS\" \\\n  '{\n    pr: {\n      total: $pr_total,\n      merged: $pr_merged,\n      closed: $pr_closed,\n      avg_merge_days: $avg_merge,\n      top_contributor: $top\n    },\n    issue: {\n      total: $issue_total,\n      bug: $bug,\n      resolved_bugs: $resolved\n    }\n  }' > \u002Fapp\u002Freport.json\n\ncat \u002Fapp\u002Freport.json\n```\n\n## Key Points\n\n- **`closed` in PR section** = closed WITHOUT merge (not all closed PRs)\n- **`gh issue list`** inherently excludes PRs, unlike `gh search issues`\n- **`gh pr list`** is repo-scoped and won't include fork PRs\n- **Bug detection** uses case-insensitive substring match on label names for \"bug\"\n- **`avg_merge_days`** is rounded to 1 decimal place\n- **`top_contributor`** is the author login who opened the most PRs in the period\n\n## Debugging Tips\n\nIf counts seem off:\n1. Check that `createdAt` dates are within range: `jq '[.[] | .createdAt] | sort' \u002Ftmp\u002Fprs.json`\n2. Check for PR contamination in issues: `jq '[.[] | .url \u002F\u002F .number]' \u002Ftmp\u002Fissues.json`\n3. Verify merged detection: `jq '[.[] | {number, state, mergedAt}]' \u002Ftmp\u002Fprs.json`\n4. Cross-reference totals with GitHub web UI search: `repo:cli\u002Fcli is:pr created:2024-12-01..2024-12-31`",{"name":5,"description":7},"main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fb3-teacher-feedback-claude-opus-4-6\u002Fgithub-repo-analytics\u002Frun3_compile-community-pulse-report-json",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":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill compile-community-pulse-report-json",{"tool":60,"command":61},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill compile-community-pulse-report-json",{"tool":63,"command":64},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill compile-community-pulse-report-json","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb3-teacher-feedback-claude-opus-4-6\u002Fgithub-repo-analytics\u002Frun3_compile-community-pulse-report-json\u002FSKILL.md",true,[],[69,87,111,129,148,160],{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":80,"publishedAt":41},"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",[75],{"categoryNo":76,"categoryName":77,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[81,82,83,84,85,86],"object counter","object","vision","computer","Computer Vision","image",{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":96,"publishedAt":41},"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",[93],{"categoryNo":94,"categoryName":95,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000023","Skill与智能体开发",[97,98,99,100,101,102,103,104,105,39,106,107,108,109,110],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","structured","performing","plan","user","it","requirements","essential","itineraries",{"skillNo":112,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":117,"publishedAt":41},"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",[],[118,119,120,121,122,123,124,100,125,126,101,127,39,128,98],"search","tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"skillNo":130,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":133,"categories":134,"keywords":135,"publishedAt":41},"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",[],[136,137,138,39,139,140,26,141,142,143,144,145,127,146,147],"glm output","output","glm","tasks","metrics","basics","guidance","matching","verifier","processing","root","calibration",{"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":155,"publishedAt":41},"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",[154],{"categoryNo":94,"categoryName":95,"taxonomyType":78,"taxonomyTypeDesc":79},[156,147,138,137,142,141,139,157,158,39,159],"glm calibration","setup","companion","metric",{"skillNo":161,"name":162,"nameZh":6,"description":163,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":164,"categories":165,"keywords":166,"publishedAt":41},"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",[],[167,138,141,168,156,147,39,137,169,170,171,172,31,173,139],"glm basics","inspect","relevant","files","good","use","Evaluation"]