[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DWFXNSAEPBSQ5HC68WGDS5":3,"skill-same:01M6DWFXNSAEPBSQ5HC68WGDS5":81},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":62,"ownerHtmlUrl":63,"ownerBlogUrl":64,"ownerDescription":65,"updatedAt":66,"install":67,"resources":80},"01M6DWFXNSAEPBSQ5HC68WGDS5","content-locale-humanize-zh",null,"Calibration anchors for AI-slop and translationese in Chinese (zh) text. Use alongside content-locale-humanize when the target is Chinese.","Muvon\u002Foctomind-tap","Muvon","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F25336907?v=4","01M6DWA4KTRX4J73CW5CECKAD0","01M6DWA4QSWFGYE6WDMAMFF1WE",6,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Fcontent-locale-humanize-zh\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"zh","content locale humanize zh","content","humanize","locale","content locale humanize","calibration","native","when","slop","Tools","no tools","data","network","中文","text","access","only","chinese","translation","2026-11-10 10:12:30",false,"---\nname: content-locale-humanize-zh\ntitle: \"Chinese Native-Fluency Calibration\"\ndescription: \"Calibration anchors for AI-slop and translationese in Chinese (zh) text. Use alongside content-locale-humanize when the target is Chinese.\"\nlicense: Apache-2.0\ncompatibility: \"Calibration data only; no tools required. Network access helps for usage checks.\"\ndomains: content\nrules:\n  - content(chinese)\n  - match(\\bzh-(Hans|Hant|CN|TW)\\b)\n  - match(\\bChinese\\b)\n  - match(中文)\n  - semantic(check if this Chinese translation sounds native)\n  - semantic(eliminate translationese from this Chinese text)\n---\n\n## Overview\n\nCalibration anchors and current norms for Chinese (zh-Hans and zh-Hant variants), feeding content-locale-humanize's dimensions. A calibration aid, not the checklist; reason natively beyond it.\n\n## Rules\n\n### AI tells\n\nSourcing confidence: the best quantitative backing of any non-English language here; a Renmin University news-lab corpus study measured roughly 4x higher parallel-sentence-structure rates in AI-generated Chinese than in human writing. Phrase-level tells below are practitioner discourse.\n\n- Overused contrast pivots \"不是…而是…\" and \"不仅…更…\". Both are native constructions; the tell is frequency, mirroring English \"not X, but Y\".\n- \"首先…其次…最后\" as a rhythm crutch when the content doesn't have exactly three steps.\n- Stock frames: \"在当今…的时代\", \"值得注意的是\", \"总而言之\"; parallel four-character slogans stacked for effect.\n\n### Translationese (翻译腔)\n\n- 被-passives where Chinese uses active or topic-comment structure.\n- Long 的 chains copied from English relative clauses; dummy verbs (\"进行讨论\" for \"讨论\", \"作出决定\").\n- Overused 当…的时候, 一个, and pronouns (他, 她, 它, 我们) that Chinese would drop.\n\n### Current norms\n\n- Variant is more than script. zh-Hans (mainland, Singapore) vs zh-Hant (Taiwan, Hong Kong) differ in vocabulary (软件\u002F軟體, 视频\u002F影片, 网络\u002F網路, 信息\u002F資訊) and quotes (“” vs 「」); automatic script conversion is not localization.\n- Punctuation: full-width ，。、；：？！ per GB\u002FT 15834-2011; 《》 for titles; …… and —— as two-character marks. Spacing between Chinese and Latin text or digits follows the house style (common in tech docs, not required by the national standard); hold it throughout.\n\n## References\n\nReviewed 2026-10-12. AI tells: Renmin University 新闻坊 (RUC Journalism Studio) news-lab study; Chinese practitioner guides. Norms: GB\u002FT 15834-2011 标点符号用法.\n","## Overview\n\nCalibration anchors and current norms for Chinese (zh-Hans and zh-Hant variants), feeding content-locale-humanize's dimensions. A calibration aid, not the checklist; reason natively beyond it.\n\n## Rules\n\n### AI tells\n\nSourcing confidence: the best quantitative backing of any non-English language here; a Renmin University news-lab corpus study measured roughly 4x higher parallel-sentence-structure rates in AI-generated Chinese than in human writing. Phrase-level tells below are practitioner discourse.\n\n- Overused contrast pivots \"不是…而是…\" and \"不仅…更…\". Both are native constructions; the tell is frequency, mirroring English \"not X, but Y\".\n- \"首先…其次…最后\" as a rhythm crutch when the content doesn't have exactly three steps.\n- Stock frames: \"在当今…的时代\", \"值得注意的是\", \"总而言之\"; parallel four-character slogans stacked for effect.\n\n### Translationese (翻译腔)\n\n- 被-passives where Chinese uses active or topic-comment structure.\n- Long 的 chains copied from English relative clauses; dummy verbs (\"进行讨论\" for \"讨论\", \"作出决定\").\n- Overused 当…的时候, 一个, and pronouns (他, 她, 它, 我们) that Chinese would drop.\n\n### Current norms\n\n- Variant is more than script. zh-Hans (mainland, Singapore) vs zh-Hant (Taiwan, Hong Kong) differ in vocabulary (软件\u002F軟體, 视频\u002F影片, 网络\u002F網路, 信息\u002F資訊) and quotes (“” vs 「」); automatic script conversion is not localization.\n- Punctuation: full-width ，。、；：？！ per GB\u002FT 15834-2011; 《》 for titles; …… and —— as two-character marks. Spacing between Chinese and Latin text or digits follows the house style (common in tech docs, not required by the national standard); hold it throughout.\n\n## References\n\nReviewed 2026-10-12. AI tells: Renmin University 新闻坊 (RUC Journalism Studio) news-lab study; Chinese practitioner guides. Norms: GB\u002FT 15834-2011 标点符号用法.\n",{"name":5,"rules":48,"title":55,"domains":25,"license":14,"description":7,"compatibility":56},[49,50,51,52,53,54],"content(chinese)","match(\\bzh-(Hans|Hant|CN|TW)\\b)","match(\\bChinese\\b)","match(中文)","semantic(check if this Chinese translation sounds native)","semantic(eliminate translationese from this Chinese text)","Chinese Native-Fluency Calibration","Calibration data only; no tools required. Network access helps for usage checks.","master","e9e4a19559669b1627b1ac5ed3f77b8e36cfad95","skills\u002Fcontent-locale-humanize-zh",0,"https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap","https:\u002F\u002Foctomind.run\u002Ftap\u002F","https:\u002F\u002Fgithub.com\u002FMuvon","https:\u002F\u002Fmuvon.io","We bring ideas to life","2026-11-14 13:21:16",{"source":8,"skillName":5,"commands":68,"prompt":78,"zipAvailable":79},[69,72,75],{"tool":70,"command":71},"npx","npx skills add Muvon\u002Foctomind-tap --skill content-locale-humanize-zh",{"tool":73,"command":74},"bunx","bunx skills add Muvon\u002Foctomind-tap --skill content-locale-humanize-zh",{"tool":76,"command":77},"pnpm","pnpm dlx skills add Muvon\u002Foctomind-tap --skill content-locale-humanize-zh","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Fcontent-locale-humanize-zh\u002FSKILL.md",true,[],[82,116,142,161,185,211],{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":86,"categories":87,"keywords":97,"publishedAt":43},"01M70SFC5CTHRKA9B97N1ARVZ2","seo-content-refresh","Finds decaying pages, picks update, merge, redirect or remove, and briefs each refresh. Use to prioritize existing content and judge whether it helped.","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Fseo-content-refresh\u002FSKILL.md",[88,93,96],{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000019","营销推广","SCENARIO","使用场景",{"categoryNo":94,"categoryName":95,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000035","市场营销",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[98,99,100,101,102,25,103,104,105,106,107,108,39,109,110,111,112,113,114,115],"seo content refresh","seo","seo content","content refresh","refresh","posts","remove","web search","performance","search","traffic","drop","websearch","revamp","merge","diagnosis","update","decay",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":124,"publishedAt":43},"01M70SBWQCHGH7HGS51Y0GTKKW","marketing-review-program","Plans how to ask real customers for honest public reviews: site choice, invitation copy, incentive and disclosure rules. Use to start a review program.","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Fmarketing-review-program\u002FSKILL.md",[122,123],{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},{"categoryNo":94,"categoryName":95,"taxonomyType":20,"taxonomyTypeDesc":21},[125,126,127,128,129,130,105,107,131,132,133,40,134,135,136,137,138,139,140,141],"program","review","marketing review program","marketing","reviews","get","campaign","choice","how to","generated","ask","plan","product","generate","customer","how","request",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":148,"publishedAt":43},"01M70SBB65Z2FC71Q7DEAXGJBG","geo-source-actions","Turns AI citation findings into ranked per-source actions for Reddit threads, listicles, review sites and videos. Records only. Use after a GEO audit.","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Fgeo-source-actions\u002FSKILL.md",[],[149,150,151,152,153,130,105,107,154,155,40,110,126,156,157,158,137,159,160,35],"actions","geo source actions","source","geo","sources","copilot","domains","llms","threads","youtube","audit","action",{"skillNo":162,"name":163,"nameZh":6,"description":164,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":165,"categories":166,"keywords":170,"publishedAt":43},"01M70S99D3Y6GF097GTXWBXHPW","commerce-ai-readiness","Audits product feeds, markup and live pages for AI shopping assistants, then lists exact fixes. Use to make a store catalog readable to AI shoppers.","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Fcommerce-ai-readiness\u002FSKILL.md",[167],{"categoryNo":168,"categoryName":169,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000031","产品经理",[171,172,173,174,175,176,177,178,179,180,107,181,154,40,39,182,183,137,159,184],"ai readiness","commerce ai readiness","commerce","readiness","feeds","ready","show","shopping","discover","checkout","up","ecommerce","documentation","recommend",{"skillNo":186,"name":187,"nameZh":6,"description":188,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":189,"categories":190,"keywords":194,"publishedAt":43},"01M6DWSX45J42KTK6XASKJRGPA","tap-model-training","Train, evaluate and publish the octomind-embed model behind capability auto-activation. Use when capability triggers or skill semantic() phrases change.","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Ftap-model-training\u002FSKILL.md",[191],{"categoryNo":192,"categoryName":193,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000023","Skill与智能体开发",[195,196,197,198,199,181,200,201,202,203,204,205,206,207,208,140,209,210,31,114],"model","training","tap","tap model training","scope","eval","uv","auto","dataset","activate","api","capabilities","publish","change","embedding","re",{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":215,"categories":216,"keywords":218,"publishedAt":43},"01M6DWSQB7NSW53Z86XM81R1W1","tap-deps-authoring","Write dep scripts for the octomind-tap registry: header comments, platform.sh, mcp vs dep types, npx\u002Fuvx pattern. Use when editing deps\u002F\u003Corg>\u002F\u003Ctool>.sh.","https:\u002F\u002Fgithub.com\u002FMuvon\u002Foctomind-tap\u002Fblob\u002Fmaster\u002Fskills\u002Ftap-deps-authoring\u002FSKILL.md",[217],{"categoryNo":192,"categoryName":193,"taxonomyType":91,"taxonomyTypeDesc":92},[219,197,220,221,222,223,224,225,226,227,228,229,230,231,232,233,31,234,235,236],"deps","tap deps authoring","authoring","DEP","MCP","run","scripts","pattern","install","registry","platform","repo","editing","tool","types","write","org","for"]