[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KEHDTS06CC20AR5FYN4Q01":3,"skill-same:01M6KEHDTS06CC20AR5FYN4Q01":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":22,"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},"01M6KEHDTS06CC20AR5FYN4Q01","json-extraction",null,"Skill to extract information from the structured JSON data, including Slack messages and document metadata.","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\u002Fb1-one-shot-gemini-3-flash-preview\u002Fenterprise-information-search\u002Fjson-extraction\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34],"extraction","json","json extraction","slack","metadata","messages","data","extract","document","structured","information","slack messages","2026-11-10 10:12:30",false,"---\nname: json-extraction\ndescription: Skill to extract information from the structured JSON data, including Slack messages and document metadata.\n---\n\n# JSON Extraction Skill\n\nThis skill covers how to efficiently navigate and extract information from the enterprise data JSON files.\n\n## Data Structure\nThe product data files (e.g., `\u002Froot\u002FDATA\u002Fproducts\u002FProduct.json`) typically have the following structure:\n- `slack`: A list of channel messages. Each message has a `User`, `text`, and `timestamp`.\n- `documents`: A list of document metadata, including `author`, `date`, `type`, and `content`.\n- `meeting_transcripts`: Transcripts of meetings.\n- `urls`: Shared URLs and their descriptions.\n\n## Techniques\n### Extracting Document Authors and Reviewers\n1. Search the `documents` list for a specific `type` (e.g., \"Market Research Report\").\n2. Identify the `author` field.\n3. Search `slack` messages around the document's `date` to find discussions and feedback.\n4. Users who provide specific suggestions or critiques in the Slack threads are considered reviewers.\n\n### Identifying Competitor Insights\n1. Search `slack` messages and `meeting_transcripts` for keywords like \"competitor\", \"strengths\", \"weaknesses\", or specific competitor names (e.g., \"Salesforce\", \"HubSpot\").\n2. Map the `userId` from those messages to identify the team members.\n\n### Finding Shared URLs\n1. Search the `slack` messages for \"http\" or \"demo\".\n2. Cross-reference with the `urls` list in the JSON if available.\n","# JSON Extraction Skill\n\nThis skill covers how to efficiently navigate and extract information from the enterprise data JSON files.\n\n## Data Structure\nThe product data files (e.g., `\u002Froot\u002FDATA\u002Fproducts\u002FProduct.json`) typically have the following structure:\n- `slack`: A list of channel messages. Each message has a `User`, `text`, and `timestamp`.\n- `documents`: A list of document metadata, including `author`, `date`, `type`, and `content`.\n- `meeting_transcripts`: Transcripts of meetings.\n- `urls`: Shared URLs and their descriptions.\n\n## Techniques\n### Extracting Document Authors and Reviewers\n1. Search the `documents` list for a specific `type` (e.g., \"Market Research Report\").\n2. Identify the `author` field.\n3. Search `slack` messages around the document's `date` to find discussions and feedback.\n4. Users who provide specific suggestions or critiques in the Slack threads are considered reviewers.\n\n### Identifying Competitor Insights\n1. Search `slack` messages and `meeting_transcripts` for keywords like \"competitor\", \"strengths\", \"weaknesses\", or specific competitor names (e.g., \"Salesforce\", \"HubSpot\").\n2. Map the `userId` from those messages to identify the team members.\n\n### Finding Shared URLs\n1. Search the `slack` messages for \"http\" or \"demo\".\n2. Cross-reference with the `urls` list in the JSON if available.\n",{"name":5,"description":7},"main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fb1-one-shot-gemini-3-flash-preview\u002Fenterprise-information-search\u002Fjson-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":49,"prompt":59,"zipAvailable":60},[50,53,56],{"tool":51,"command":52},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill json-extraction",{"tool":54,"command":55},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill json-extraction",{"tool":57,"command":58},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill json-extraction","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb1-one-shot-gemini-3-flash-preview\u002Fenterprise-information-search\u002Fjson-extraction\u002FSKILL.md",true,[],[63,79,101,119,138,150],{"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":72,"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":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",[73,74,75,76,77,78],"object counter","object","vision","computer","Computer Vision","image",{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":86,"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",[85],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[87,88,89,90,91,92,32,93,94,95,96,97,98,99,100],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","performing","plan","for","user","it","requirements","essential","itineraries",{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":107,"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",[],[108,109,110,111,112,113,114,90,115,116,91,117,95,118,88],"search","tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":125,"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",[],[126,127,128,95,129,130,24,131,132,133,134,135,117,136,137],"glm output","output","glm","tasks","metrics","basics","guidance","matching","verifier","processing","root","calibration",{"skillNo":139,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":142,"categories":143,"keywords":145,"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",[144],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[146,137,128,127,132,131,129,147,148,95,149],"glm calibration","setup","companion","metric",{"skillNo":151,"name":152,"nameZh":6,"description":153,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":156,"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",[],[157,128,131,158,146,137,95,127,159,160,161,162,163,164,129],"glm basics","inspect","relevant","files","good","use","how","Evaluation"]