[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KFQ8CXFVBBC2W2KV8VWW3B":3,"skill-same:01M6KFQ8CXFVBBC2W2KV8VWW3B":59},{"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":32,"linkOnly":33,"markdownContent":34,"markdownBody":35,"frontMatter":36,"refName":37,"commitSha":38,"skillDirectory":39,"forksCount":40,"repositoryHtmlUrl":41,"repositoryHomepageUrl":42,"ownerHtmlUrl":43,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":44,"install":45,"resources":58},"01M6KFQ8CXFVBBC2W2KV8VWW3B","run2_cvss-score-extraction",null,"Extract CVSS v3 scores from Trivy vulnerability JSON with source priority (NVD > GHSA > RedHat) and fallback to N\u002FA.","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\u002Fb2-self-feedback-claude-sonnet-4-6\u002Fdependency-vulnerability-check\u002Frun2_cvss-score-extraction\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31],"extraction","cvss","cvss score extraction","run2 cvss score","run2 cvss score extraction","NVD","trivy","vulnerability","json","extract","fallback","v3","with","source","2026-11-10 10:12:30",false,"---\nname: run2_cvss-score-extraction\ndescription: Extract CVSS v3 scores from Trivy vulnerability JSON with source priority (NVD > GHSA > RedHat) and fallback to N\u002FA.\n---\n\n# CVSS Score Extraction (Round 2)\n\n## Priority Order\nNVD V3Score → GHSA V3Score → RedHat V3Score → N\u002FA\n\nDo NOT fall back to V2Score — severity labels (HIGH\u002FCRITICAL) come from Trivy's own assessment and are already correct; we only need the numeric score for reporting.\n\n## Canonical Implementation\n\n```python\ndef get_cvss_score(vuln):\n    \"\"\"\n    Extract CVSS v3 score with source priority: NVD > GHSA > RedHat.\n    Returns float score or string 'N\u002FA'.\n    \"\"\"\n    cvss = vuln.get('CVSS', {})\n    if not isinstance(cvss, dict):\n        return 'N\u002FA'\n    for source in ['nvd', 'ghsa', 'redhat']:\n        entry = cvss.get(source, {})\n        if isinstance(entry, dict):\n            score = entry.get('V3Score')\n            if score is not None and isinstance(score, (int, float)):\n                return score\n    return 'N\u002FA'\n```\n\n## Real-World Examples from This Task\n\n| CVE | NVD | GHSA | RedHat | Result |\n|-----|-----|------|--------|--------|\n| CVE-2024-29415 (ip) | - | 8.1 | 9.8 | **8.1** (GHSA wins, NVD absent) |\n| CVE-2022-25883 (semver) | 7.5 | 7.5 | 7.5 | **7.5** (NVD wins) |\n| CVE-2026-23745 (tar) | - | - | 8.2 | **8.2** (RedHat only) |\n\n## Notes\n- Source keys in Trivy JSON are lowercase: `nvd`, `ghsa`, `redhat`\n- Only `V3Score` field is relevant (not `V3Vector`)\n- When NVD is absent, GHSA is usually the next best source\n","# CVSS Score Extraction (Round 2)\n\n## Priority Order\nNVD V3Score → GHSA V3Score → RedHat V3Score → N\u002FA\n\nDo NOT fall back to V2Score — severity labels (HIGH\u002FCRITICAL) come from Trivy's own assessment and are already correct; we only need the numeric score for reporting.\n\n## Canonical Implementation\n\n```python\ndef get_cvss_score(vuln):\n    \"\"\"\n    Extract CVSS v3 score with source priority: NVD > GHSA > RedHat.\n    Returns float score or string 'N\u002FA'.\n    \"\"\"\n    cvss = vuln.get('CVSS', {})\n    if not isinstance(cvss, dict):\n        return 'N\u002FA'\n    for source in ['nvd', 'ghsa', 'redhat']:\n        entry = cvss.get(source, {})\n        if isinstance(entry, dict):\n            score = entry.get('V3Score')\n            if score is not None and isinstance(score, (int, float)):\n                return score\n    return 'N\u002FA'\n```\n\n## Real-World Examples from This Task\n\n| CVE | NVD | GHSA | RedHat | Result |\n|-----|-----|------|--------|--------|\n| CVE-2024-29415 (ip) | - | 8.1 | 9.8 | **8.1** (GHSA wins, NVD absent) |\n| CVE-2022-25883 (semver) | 7.5 | 7.5 | 7.5 | **7.5** (NVD wins) |\n| CVE-2026-23745 (tar) | - | - | 8.2 | **8.2** (RedHat only) |\n\n## Notes\n- Source keys in Trivy JSON are lowercase: `nvd`, `ghsa`, `redhat`\n- Only `V3Score` field is relevant (not `V3Vector`)\n- When NVD is absent, GHSA is usually the next best source\n",{"name":5,"description":7},"main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Fdependency-vulnerability-check\u002Frun2_cvss-score-extraction",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":46,"prompt":56,"zipAvailable":57},[47,50,53],{"tool":48,"command":49},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill run2_cvss-score-extraction",{"tool":51,"command":52},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill run2_cvss-score-extraction",{"tool":54,"command":55},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill run2_cvss-score-extraction","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb2-self-feedback-claude-sonnet-4-6\u002Fdependency-vulnerability-check\u002Frun2_cvss-score-extraction\u002FSKILL.md",true,[],[60,78,103,121,140,152],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":71,"publishedAt":32},"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",[66],{"categoryNo":67,"categoryName":68,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[72,73,74,75,76,77],"object counter","object","vision","computer","Computer Vision","image",{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":87,"publishedAt":32},"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",[84],{"categoryNo":85,"categoryName":86,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000023","Skill与智能体开发",[88,89,90,91,92,93,94,95,96,97,98,99,100,101,102],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","structured","performing","plan","for","user","it","requirements","essential","itineraries",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":109,"publishedAt":32},"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",[],[110,111,112,113,114,115,116,91,117,118,92,119,97,120,89],"search","tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":125,"categories":126,"keywords":127,"publishedAt":32},"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",[],[128,129,130,97,131,132,26,133,134,135,136,137,119,138,139],"glm output","output","glm","tasks","metrics","basics","guidance","matching","verifier","processing","root","calibration",{"skillNo":141,"name":142,"nameZh":6,"description":143,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":144,"categories":145,"keywords":147,"publishedAt":32},"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",[146],{"categoryNo":85,"categoryName":86,"taxonomyType":69,"taxonomyTypeDesc":70},[148,139,130,129,134,133,131,149,150,97,151],"glm calibration","setup","companion","metric",{"skillNo":153,"name":154,"nameZh":6,"description":155,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":156,"categories":157,"keywords":158,"publishedAt":32},"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",[],[159,130,133,160,148,139,97,129,161,162,163,164,165,166,131],"glm basics","inspect","relevant","files","good","use","how","Evaluation"]