[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KE8WHSBBFWHSQG7REFYB8S":3,"skill-same:01M6KE8WHSBBFWHSQG7REFYB8S":50},{"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":23,"linkOnly":24,"markdownContent":25,"markdownBody":26,"frontMatter":27,"refName":28,"commitSha":29,"skillDirectory":30,"forksCount":31,"repositoryHtmlUrl":32,"repositoryHomepageUrl":33,"ownerHtmlUrl":34,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":35,"install":36,"resources":49},"01M6KE8WHSBBFWHSQG7REFYB8S","mandarin-rhyme",null,"Rules for rhyming in poetry based on modern Mandarin (Pinyin).","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\u002Fchinese-poem-generator\u002Fmandarin-rhyme\u002FSKILL.md",[],[18,19,20,21,22],"rhyme","mandarin rhyme","Rules","Poetry","for","2026-11-10 10:12:30",false,"---\nname: mandarin-rhyme\ndescription: Rules for rhyming in poetry based on modern Mandarin (Pinyin).\n---\n\n# Modern Mandarin Rhyming (现代汉语押韵)\n\nTraditionally, Chinese poetry used the \"Pingshui Rhymes\" (平水韵). However, for modern audiences or specific tasks, rhyming based on the 18 main rhyme groups of modern Mandarin (often called \"Shi Ba Yun\" 十八韵) is common.\n\n## 1. Core Concept\nIn modern poetry, characters that share the same main vowel and coda (if any) in Pinyin are considered to rhyme.\n\n## 2. Common Rhyme Groups (Modern Mandarin)\n- **A (阿):** a, ia, ua.\n- **AN (安):** an, ian, uan, üan.\n- **ANG (昂):** ang, iang, uang.\n- **AO (奥):** ao, iao.\n- **E\u002FO (鹅\u002F喔):** e, o, uo.\n- **EI (诶):** ei, uei (ui).\n- **EN (恩):** en, in, uen (un), ün.\n- **ENG (亨):** eng, ing, ueng.\n- **I\u002FÜ (衣\u002F鱼):** i, ü.\n- **OU (欧):** ou, iou (iu).\n\n## 3. Rules for Regulated Verse (律诗)\n- **Rhyme Position:** Lines 2, 4, 6, 8. (Line 1 is optional).\n- **Rhyme Tone:** Typically, rhymes must all be in the \"Level\" tone (平声 - 1st or 2nd tone in Mandarin).\n\n## 4. Usage in Task\n- Choose a rhyme group (e.g., \"ANG\").\n- Ensure the last characters of lines 1 (optional), 2, 4, 6, and 8 have pinyin ending in \"ang\u002Fiang\u002Fuang\" and are in the 1st or 2nd tone.\n","# Modern Mandarin Rhyming (现代汉语押韵)\n\nTraditionally, Chinese poetry used the \"Pingshui Rhymes\" (平水韵). However, for modern audiences or specific tasks, rhyming based on the 18 main rhyme groups of modern Mandarin (often called \"Shi Ba Yun\" 十八韵) is common.\n\n## 1. Core Concept\nIn modern poetry, characters that share the same main vowel and coda (if any) in Pinyin are considered to rhyme.\n\n## 2. Common Rhyme Groups (Modern Mandarin)\n- **A (阿):** a, ia, ua.\n- **AN (安):** an, ian, uan, üan.\n- **ANG (昂):** ang, iang, uang.\n- **AO (奥):** ao, iao.\n- **E\u002FO (鹅\u002F喔):** e, o, uo.\n- **EI (诶):** ei, uei (ui).\n- **EN (恩):** en, in, uen (un), ün.\n- **ENG (亨):** eng, ing, ueng.\n- **I\u002FÜ (衣\u002F鱼):** i, ü.\n- **OU (欧):** ou, iou (iu).\n\n## 3. Rules for Regulated Verse (律诗)\n- **Rhyme Position:** Lines 2, 4, 6, 8. (Line 1 is optional).\n- **Rhyme Tone:** Typically, rhymes must all be in the \"Level\" tone (平声 - 1st or 2nd tone in Mandarin).\n\n## 4. Usage in Task\n- Choose a rhyme group (e.g., \"ANG\").\n- Ensure the last characters of lines 1 (optional), 2, 4, 6, and 8 have pinyin ending in \"ang\u002Fiang\u002Fuang\" and are in the 1st or 2nd tone.\n",{"name":5,"description":7},"main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fb1-one-shot-gemini-3-flash-preview\u002Fchinese-poem-generator\u002Fmandarin-rhyme",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":37,"prompt":47,"zipAvailable":48},[38,41,44],{"tool":39,"command":40},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill mandarin-rhyme",{"tool":42,"command":43},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill mandarin-rhyme",{"tool":45,"command":46},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill mandarin-rhyme","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fb1-one-shot-gemini-3-flash-preview\u002Fchinese-poem-generator\u002Fmandarin-rhyme\u002FSKILL.md",true,[],[51,69,93,111,131,143],{"skillNo":52,"name":53,"nameZh":6,"description":54,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":55,"categories":56,"keywords":62,"publishedAt":23},"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",[57],{"categoryNo":58,"categoryName":59,"taxonomyType":60,"taxonomyTypeDesc":61},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[63,64,65,66,67,68],"object counter","object","vision","computer","Computer Vision","image",{"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":78,"publishedAt":23},"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",[75],{"categoryNo":76,"categoryName":77,"taxonomyType":60,"taxonomyTypeDesc":61},"01JBSEEDCAT000000000000023","Skill与智能体开发",[79,80,81,82,83,84,85,86,87,22,88,89,90,91,92],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","structured","performing","plan","user","it","requirements","essential","itineraries",{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":23},"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",[],[100,101,102,103,104,105,106,82,107,108,83,109,22,110,80],"search","tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"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":23},"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",[],[118,119,120,22,121,122,123,124,125,126,127,128,109,129,130],"glm output","output","glm","tasks","metrics","json","basics","guidance","matching","verifier","processing","root","calibration",{"skillNo":132,"name":133,"nameZh":6,"description":134,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":138,"publishedAt":23},"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",[137],{"categoryNo":76,"categoryName":77,"taxonomyType":60,"taxonomyTypeDesc":61},[139,130,120,119,125,124,121,140,141,22,142],"glm calibration","setup","companion","metric",{"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":149,"publishedAt":23},"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",[],[150,120,124,151,139,130,22,119,152,153,154,155,156,157,121],"glm basics","inspect","relevant","files","good","use","how","Evaluation"]