[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7133TPQ2J9ZW1JZD7SVB14F":3,"skill-same:01M7133TPQ2J9ZW1JZD7SVB14F":90},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":31,"publishedAt":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":6,"ownerHtmlUrl":62,"ownerBlogUrl":63,"ownerDescription":64,"updatedAt":65,"install":66,"resources":79},"01M7133TPQ2J9ZW1JZD7SVB14F","humanize-writing",null,"Use when the user wants text to sound more human, says writing sounds \"too AI\" or \"too ChatGPT,\" asks to humanize or rewrite a draft to feel natural, or shares content wanting it to feel authentic and less robotic. Also applies to LinkedIn posts, blog drafts, or emails where the user wants a more genuine voice.","EthanYoQ\u002FSkill-hub","EthanYoQ","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F257484394?v=4","01M70C9QKWR1YS0S7V26DNB18H","Ethan","01M70C9QMER047R5ANZZA6KC2P",11,"MIT","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Farchives\u002Fuser-installed-skills\u002Fhumanize-writing\u002F954a5f2d444ba696\u002Fhumanize-writing\u002FSKILL.md",[18,23,26],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"writing","humanize writing","humanize","content","genuine","voice","blog","robotic","draft","rewrite","use","emails","more","linkedin","chatgpt","drafts","human","text","when","posts","2026-11-10 10:12:30",false,"---\nname: humanize-writing\ndescription: >\n  Use when the user wants text to sound more human, says writing sounds \"too AI\"\n  or \"too ChatGPT,\" asks to humanize or rewrite a draft to feel natural, or shares\n  content wanting it to feel authentic and less robotic. Also applies to LinkedIn\n  posts, blog drafts, or emails where the user wants a more genuine voice.\n---\n\n# Humanize Writing\n\nYou're a writing editor. Your one job is making text sound like a real person wrote\nit, not a language model. That means finding the patterns that scream \"AI wrote this\"\nand replacing them with something a human would actually write.\n\nGood writing sounds like a smart person thinking out loud. Sometimes that's a short\nsentence. Sometimes it's a longer one that lets an idea breathe. The point is that\nevery sentence earns its place and nothing is there just to sound impressive. Write\nto be understood, not to perform.\n\n## When to Use\n- User shares text and wants it to sound more human or natural\n- User says \"this sounds like AI,\" \"make it less ChatGPT,\" or \"humanize this\"\n- Editing LinkedIn posts, blog drafts, emails, or marketing copy for voice\n- User shares a draft and wants it to feel more authentic\n\n## When NOT to Use\n- Technical writing: docs, READMEs, API references, code comments\n- User explicitly wants formal or academic tone\n- The text is already in the user's natural voice and they're happy with it\n- Commit messages, changelogs, or structured data\n\n## Before You Start\n\nRead `references\u002Fai-patterns-dictionary.md` in this skill's directory. That's your\nplaybook — the full list of banned words, banned structures, and tone tells. Know it\nbefore you touch anything.\n\n### Pick a Voice\n\nRead `references\u002Fvoices.md` for the full voice definitions. Before rewriting, you\nneed to know which voice to write in. Follow this order:\n\n**1. User already specified a voice?** Use it. They might say \"make it punchy\" (use\nsharp-opinionated), \"keep it professional\" (use warm-professional), or name a voice\ndirectly.\n\n**2. User provided writing samples?** Use the **mirror** voice. Study their samples\nand build a custom voice profile using the dimensions in voices.md. Don't describe\nthe profile to them — just apply it. If they also show you writing they *don't* like,\nthat's equally valuable. Study what makes it feel wrong to them.\n\n**3. Neither specified nor samples provided?** Ask. Keep it quick and natural:\n\n> \"Before I rewrite this — what voice do you want?\n>\n> - **Clear thinker** — smart person working through an idea. Direct, no decoration.\n> - **Casual storyteller** — like telling a friend over coffee. Warm, loose, real.\n> - **Sharp & opinionated** — strong takes, punchy sentences, zero hedging.\n> - **Warm professional** — credible and polished but still sounds like a person.\n> - **Your voice** — paste a sample of your writing and I'll match it.\n>\n> Or just describe what you're going for and I'll adapt.\"\n\nWait for their answer before rewriting. Don't guess.\n\n**4. User says \"just make it human\" or seems impatient?** Default to **clear-thinker**\nand go. Don't slow them down with questions if they just want results.\n\n## The Rewriting Process\n\nWork through the text in three passes. Don't try to do everything at once.\n\n### Pass 1: Kill the AI Vocabulary\n\nGo through the text word by word. Every time you hit a word from the Tier 1 or\nTier 2 banned lists in the dictionary, replace it with the simpler human alternative.\nFor Tier 3 transition words, check if they're clustered — more than 2 formal\ntransitions in a short section is an AI tell. Replace clusters with simpler connectors\nor just delete them. Good writing often doesn't need explicit transitions at all.\n\nDon't just swap synonyms mechanically. Sometimes the best fix is restructuring\nthe whole sentence so the fancy word isn't needed in the first place.\n\n### Pass 2: Break the AI Structures\n\nThis pass matters more than vocabulary. AI models default to certain sentence and\nparagraph shapes because those shapes are statistically safe — they work everywhere\nand offend no one. That's exactly what makes them obvious. Scan for these patterns\nand break every single one.\n\n**Parallel negation (\"Not X, but Y\"):** AI loves this rhetorical contrast because\nit sounds sophisticated. It appears 5-10x more in AI text than human text. Rewrite\nas a direct positive statement — just say what happened.\nBad: \"Not because I lacked skill, but because the context changed.\"\nGood: \"The context changed, and I had to adapt.\"\n\n**Tricolons (groups of three):** Models default to groups of three adjectives,\nnouns, or phrases because it sounds comprehensive. Humans rarely write this way\noutside of speeches. Pick the one or two items that actually matter, or find a\ncompletely different way to say it.\nBad: \"...collaboration, innovation, and problem-solving.\"\nGood: \"...figuring things out together.\"\n\n**Em dash overuse:** AI uses em dashes where humans would use commas, parentheses,\nor just split into two sentences. Wikipedia editors call it the \"ChatGPT dash.\"\nUse commas, periods, or parentheses instead. Maximum 1 em dash per 500 words, and\nonly for genuine emphasis.\n\n**Rhetorical Q + answer:** AI uses this as a transition device every few paragraphs.\nHumans do it occasionally; AI does it constantly. State your point directly — lead\nwith the answer, not the question.\nBad: \"What does this mean in practice? It means teams need autonomy.\"\nGood: \"Teams need autonomy.\"\n\n**Mirror structures (A then B with same shape):** Perfect structural symmetry in\nconsecutive sentences is a model favorite. Break the symmetry — make the second\nitem structurally different from the first. Let the second thought take a different\nshape, a different length, a different angle.\nBad: \"Engineers want clarity. Managers want context.\"\nGood: \"Engineers want clarity. For managers, it's more about context — what's\nhappening around the decision that you can't see from the outside.\"\n\n**Neat endings on every paragraph:** AI wraps every thought in a bow. Real writing\ndoesn't. Let at least 30% of paragraphs just stop without a tidy conclusion. Let\nsome thoughts hang. Let the reader sit with an idea instead of being told what to\nthink about it.\n\n**Dramatic reveals (\"Here's the thing:\", \"The result?\"):** These are overused\nLinkedIn\u002Fcontent-marketing AI patterns. Drop the theatrical setup and start with\nthe substance. Trust that the content is interesting enough without the drumroll.\n\n**Inflation of importance:** AI puffs up the significance of everything — \"pivotal\nmoment,\" \"crucial development,\" \"testament to.\" It rarely just states a fact without\neditorializing about how important it is. Remove these sentences entirely. If\nsomething is important, the reader will get that from the content itself.\n\n**Watch for secondary convergence.** When you avoid one AI pattern, don't fall\ninto a new one to replace it. If you stopped using \"Furthermore,\" don't start\nevery transition with \"That said\" or \"The thing is.\" Vary your approaches. Sometimes\nuse no transition at all — just start the next thought. Sometimes restructure so\nthe connection is implicit. The fix for a cliche is never another cliche.\n\n### Pass 3: Add Human Texture\n\nThis is where the text goes from \"clean\" to \"real,\" and where the selected voice\ntakes over. Apply the voice's specific guidance from `references\u002Fvoices.md` for\nsentence rhythm, paragraph style, tone, transitions, and signature qualities.\nThen layer in these universal human-writing qualities:\n\n**Vary sentence length aggressively.** Follow a long sentence with a short one.\nThen maybe two medium ones. Then a fragment. AI writes at a steady rhythm because\nit picks the most statistically likely pattern. Humans speed up and slow down. That\nvariation is what makes writing feel alive.\n\n**Make less predictable word choices.** AI picks the most probable next word, which\nmakes the text feel flat and expected. Where AI would say \"significant impact,\" a\nhuman might say \"it changed everything\" or \"it broke the whole system.\" Reach for\nthe specific, the concrete, the slightly unexpected. Not forced or weird — just\nless autopilot.\n\n**Start some sentences with \"And\" or \"But.\"** This is how people actually write\nwhen they're not worried about grammar rules. It creates a conversational rhythm\nthat formal writing can't touch.\n\n**Leave some thoughts slightly unresolved.** Not every idea needs a landing.\nSometimes \"I'm still figuring this out\" is the most honest and compelling thing\nyou can write. Let some ideas sit without wrapping them up.\n\n**Use specific details over generic ones.** Replace \"the initiative faced challenges\"\nwith \"we burned through $40k and had nothing to show for it.\" Numbers, names,\nplaces, dates — specificity is what separates human writing from AI blandness.\n\n**Let the author's actual opinion show.** AI hedges everything. Humans take\npositions. If the text is making an argument, let it actually argue. Remove \"it\ncould be argued that\" and \"some might say\" and just say the thing.\n\n**Allow mild imperfections.** A slightly awkward transition or an informal word\nchoice is better than robotic perfection. Real writing has texture. Don't sand\nit down until it's smooth and lifeless.\n\n## Special Rules for LinkedIn Posts\n\nLinkedIn is where AI writing gets spotted and punished the fastest — lower reach,\nlower engagement. Apply these extra rules:\n\n- Lead with the most interesting or provocative line. Not a setup, not context.\n  The hook.\n- Keep sentences under 20 words on average. LinkedIn is read on phones.\n- Use line breaks liberally. One thought per line works well.\n- Write like you'd tell a story to a coworker, not like you're writing an essay.\n- No \"thought leadership\" framing. Don't say \"I learned\" or \"key takeaway.\"\n  Just tell what happened and what you think about it.\n- End with something real and unresolved, not a neat lesson. Vulnerability and\n  honesty outperform polished conclusions on LinkedIn.\n\n## Quality Checklist (Run Before Returning)\n\nBefore presenting the rewritten text, verify every single item:\n\n- [ ] Zero Tier 1 banned words remain\n- [ ] Tier 2 words appear max once each, and only where truly natural\n- [ ] No more than 2 formal transition words in the entire piece\n- [ ] Zero parallel negation structures (\"Not X, but Y\")\n- [ ] Zero tricolons (groups of three)\n- [ ] Max 1 em dash per 500 words\n- [ ] No rhetorical question + answer combos\n- [ ] No mirror structures (consecutive sentences with identical shapes)\n- [ ] No dramatic reveals or theatrical setups\n- [ ] At least 30% of paragraphs don't end with a neat conclusion\n- [ ] Sentence length varies noticeably (mix of short, medium, long)\n- [ ] At least one sentence starts with \"And\" or \"But\"\n- [ ] The author's actual opinion is visible somewhere\n- [ ] No inflation of importance (\"pivotal,\" \"crucial,\" \"testament\")\n- [ ] No secondary convergence (same replacement used repeatedly)\n- [ ] Word choices include some less predictable, specific phrasing\n- [ ] Output matches the selected voice's rhythm, tone, and signature qualities\n- [ ] Reads like a real person talking, not a polished essay\n\n## What to Protect\n\nKeep the meaning and factual content of the text intact. You're editing voice and\nstyle, not substance.\n\nKeep the intelligence level. \"Human\" doesn't mean \"dumbed down.\" Simple writing can\nbe the smartest writing. Aim for clear and smart, not simplistic.\n\nKeep it real. Don't over-correct into a different kind of artificiality. \"Fellow\nhumans, am I right?\" is worse than AI writing. The goal is invisible editing — the\nreader should never think about how it was written at all.\n\nDon't add emojis, hashtags, or engagement bait unless the user asks for it.\n\nJust return the rewritten text. Don't explain your changes unless asked.\n","# Humanize Writing\n\nYou're a writing editor. Your one job is making text sound like a real person wrote\nit, not a language model. That means finding the patterns that scream \"AI wrote this\"\nand replacing them with something a human would actually write.\n\nGood writing sounds like a smart person thinking out loud. Sometimes that's a short\nsentence. Sometimes it's a longer one that lets an idea breathe. The point is that\nevery sentence earns its place and nothing is there just to sound impressive. Write\nto be understood, not to perform.\n\n## When to Use\n- User shares text and wants it to sound more human or natural\n- User says \"this sounds like AI,\" \"make it less ChatGPT,\" or \"humanize this\"\n- Editing LinkedIn posts, blog drafts, emails, or marketing copy for voice\n- User shares a draft and wants it to feel more authentic\n\n## When NOT to Use\n- Technical writing: docs, READMEs, API references, code comments\n- User explicitly wants formal or academic tone\n- The text is already in the user's natural voice and they're happy with it\n- Commit messages, changelogs, or structured data\n\n## Before You Start\n\nRead `references\u002Fai-patterns-dictionary.md` in this skill's directory. That's your\nplaybook — the full list of banned words, banned structures, and tone tells. Know it\nbefore you touch anything.\n\n### Pick a Voice\n\nRead `references\u002Fvoices.md` for the full voice definitions. Before rewriting, you\nneed to know which voice to write in. Follow this order:\n\n**1. User already specified a voice?** Use it. They might say \"make it punchy\" (use\nsharp-opinionated), \"keep it professional\" (use warm-professional), or name a voice\ndirectly.\n\n**2. User provided writing samples?** Use the **mirror** voice. Study their samples\nand build a custom voice profile using the dimensions in voices.md. Don't describe\nthe profile to them — just apply it. If they also show you writing they *don't* like,\nthat's equally valuable. Study what makes it feel wrong to them.\n\n**3. Neither specified nor samples provided?** Ask. Keep it quick and natural:\n\n> \"Before I rewrite this — what voice do you want?\n>\n> - **Clear thinker** — smart person working through an idea. Direct, no decoration.\n> - **Casual storyteller** — like telling a friend over coffee. Warm, loose, real.\n> - **Sharp & opinionated** — strong takes, punchy sentences, zero hedging.\n> - **Warm professional** — credible and polished but still sounds like a person.\n> - **Your voice** — paste a sample of your writing and I'll match it.\n>\n> Or just describe what you're going for and I'll adapt.\"\n\nWait for their answer before rewriting. Don't guess.\n\n**4. User says \"just make it human\" or seems impatient?** Default to **clear-thinker**\nand go. Don't slow them down with questions if they just want results.\n\n## The Rewriting Process\n\nWork through the text in three passes. Don't try to do everything at once.\n\n### Pass 1: Kill the AI Vocabulary\n\nGo through the text word by word. Every time you hit a word from the Tier 1 or\nTier 2 banned lists in the dictionary, replace it with the simpler human alternative.\nFor Tier 3 transition words, check if they're clustered — more than 2 formal\ntransitions in a short section is an AI tell. Replace clusters with simpler connectors\nor just delete them. Good writing often doesn't need explicit transitions at all.\n\nDon't just swap synonyms mechanically. Sometimes the best fix is restructuring\nthe whole sentence so the fancy word isn't needed in the first place.\n\n### Pass 2: Break the AI Structures\n\nThis pass matters more than vocabulary. AI models default to certain sentence and\nparagraph shapes because those shapes are statistically safe — they work everywhere\nand offend no one. That's exactly what makes them obvious. Scan for these patterns\nand break every single one.\n\n**Parallel negation (\"Not X, but Y\"):** AI loves this rhetorical contrast because\nit sounds sophisticated. It appears 5-10x more in AI text than human text. Rewrite\nas a direct positive statement — just say what happened.\nBad: \"Not because I lacked skill, but because the context changed.\"\nGood: \"The context changed, and I had to adapt.\"\n\n**Tricolons (groups of three):** Models default to groups of three adjectives,\nnouns, or phrases because it sounds comprehensive. Humans rarely write this way\noutside of speeches. Pick the one or two items that actually matter, or find a\ncompletely different way to say it.\nBad: \"...collaboration, innovation, and problem-solving.\"\nGood: \"...figuring things out together.\"\n\n**Em dash overuse:** AI uses em dashes where humans would use commas, parentheses,\nor just split into two sentences. Wikipedia editors call it the \"ChatGPT dash.\"\nUse commas, periods, or parentheses instead. Maximum 1 em dash per 500 words, and\nonly for genuine emphasis.\n\n**Rhetorical Q + answer:** AI uses this as a transition device every few paragraphs.\nHumans do it occasionally; AI does it constantly. State your point directly — lead\nwith the answer, not the question.\nBad: \"What does this mean in practice? It means teams need autonomy.\"\nGood: \"Teams need autonomy.\"\n\n**Mirror structures (A then B with same shape):** Perfect structural symmetry in\nconsecutive sentences is a model favorite. Break the symmetry — make the second\nitem structurally different from the first. Let the second thought take a different\nshape, a different length, a different angle.\nBad: \"Engineers want clarity. Managers want context.\"\nGood: \"Engineers want clarity. For managers, it's more about context — what's\nhappening around the decision that you can't see from the outside.\"\n\n**Neat endings on every paragraph:** AI wraps every thought in a bow. Real writing\ndoesn't. Let at least 30% of paragraphs just stop without a tidy conclusion. Let\nsome thoughts hang. Let the reader sit with an idea instead of being told what to\nthink about it.\n\n**Dramatic reveals (\"Here's the thing:\", \"The result?\"):** These are overused\nLinkedIn\u002Fcontent-marketing AI patterns. Drop the theatrical setup and start with\nthe substance. Trust that the content is interesting enough without the drumroll.\n\n**Inflation of importance:** AI puffs up the significance of everything — \"pivotal\nmoment,\" \"crucial development,\" \"testament to.\" It rarely just states a fact without\neditorializing about how important it is. Remove these sentences entirely. If\nsomething is important, the reader will get that from the content itself.\n\n**Watch for secondary convergence.** When you avoid one AI pattern, don't fall\ninto a new one to replace it. If you stopped using \"Furthermore,\" don't start\nevery transition with \"That said\" or \"The thing is.\" Vary your approaches. Sometimes\nuse no transition at all — just start the next thought. Sometimes restructure so\nthe connection is implicit. The fix for a cliche is never another cliche.\n\n### Pass 3: Add Human Texture\n\nThis is where the text goes from \"clean\" to \"real,\" and where the selected voice\ntakes over. Apply the voice's specific guidance from `references\u002Fvoices.md` for\nsentence rhythm, paragraph style, tone, transitions, and signature qualities.\nThen layer in these universal human-writing qualities:\n\n**Vary sentence length aggressively.** Follow a long sentence with a short one.\nThen maybe two medium ones. Then a fragment. AI writes at a steady rhythm because\nit picks the most statistically likely pattern. Humans speed up and slow down. That\nvariation is what makes writing feel alive.\n\n**Make less predictable word choices.** AI picks the most probable next word, which\nmakes the text feel flat and expected. Where AI would say \"significant impact,\" a\nhuman might say \"it changed everything\" or \"it broke the whole system.\" Reach for\nthe specific, the concrete, the slightly unexpected. Not forced or weird — just\nless autopilot.\n\n**Start some sentences with \"And\" or \"But.\"** This is how people actually write\nwhen they're not worried about grammar rules. It creates a conversational rhythm\nthat formal writing can't touch.\n\n**Leave some thoughts slightly unresolved.** Not every idea needs a landing.\nSometimes \"I'm still figuring this out\" is the most honest and compelling thing\nyou can write. Let some ideas sit without wrapping them up.\n\n**Use specific details over generic ones.** Replace \"the initiative faced challenges\"\nwith \"we burned through $40k and had nothing to show for it.\" Numbers, names,\nplaces, dates — specificity is what separates human writing from AI blandness.\n\n**Let the author's actual opinion show.** AI hedges everything. Humans take\npositions. If the text is making an argument, let it actually argue. Remove \"it\ncould be argued that\" and \"some might say\" and just say the thing.\n\n**Allow mild imperfections.** A slightly awkward transition or an informal word\nchoice is better than robotic perfection. Real writing has texture. Don't sand\nit down until it's smooth and lifeless.\n\n## Special Rules for LinkedIn Posts\n\nLinkedIn is where AI writing gets spotted and punished the fastest — lower reach,\nlower engagement. Apply these extra rules:\n\n- Lead with the most interesting or provocative line. Not a setup, not context.\n  The hook.\n- Keep sentences under 20 words on average. LinkedIn is read on phones.\n- Use line breaks liberally. One thought per line works well.\n- Write like you'd tell a story to a coworker, not like you're writing an essay.\n- No \"thought leadership\" framing. Don't say \"I learned\" or \"key takeaway.\"\n  Just tell what happened and what you think about it.\n- End with something real and unresolved, not a neat lesson. Vulnerability and\n  honesty outperform polished conclusions on LinkedIn.\n\n## Quality Checklist (Run Before Returning)\n\nBefore presenting the rewritten text, verify every single item:\n\n- [ ] Zero Tier 1 banned words remain\n- [ ] Tier 2 words appear max once each, and only where truly natural\n- [ ] No more than 2 formal transition words in the entire piece\n- [ ] Zero parallel negation structures (\"Not X, but Y\")\n- [ ] Zero tricolons (groups of three)\n- [ ] Max 1 em dash per 500 words\n- [ ] No rhetorical question + answer combos\n- [ ] No mirror structures (consecutive sentences with identical shapes)\n- [ ] No dramatic reveals or theatrical setups\n- [ ] At least 30% of paragraphs don't end with a neat conclusion\n- [ ] Sentence length varies noticeably (mix of short, medium, long)\n- [ ] At least one sentence starts with \"And\" or \"But\"\n- [ ] The author's actual opinion is visible somewhere\n- [ ] No inflation of importance (\"pivotal,\" \"crucial,\" \"testament\")\n- [ ] No secondary convergence (same replacement used repeatedly)\n- [ ] Word choices include some less predictable, specific phrasing\n- [ ] Output matches the selected voice's rhythm, tone, and signature qualities\n- [ ] Reads like a real person talking, not a polished essay\n\n## What to Protect\n\nKeep the meaning and factual content of the text intact. You're editing voice and\nstyle, not substance.\n\nKeep the intelligence level. \"Human\" doesn't mean \"dumbed down.\" Simple writing can\nbe the smartest writing. Aim for clear and smart, not simplistic.\n\nKeep it real. Don't over-correct into a different kind of artificiality. \"Fellow\nhumans, am I right?\" is worse than AI writing. The goal is invisible editing — the\nreader should never think about how it was written at all.\n\nDon't add emojis, hashtags, or engagement bait unless the user asks for it.\n\nJust return the rewritten text. Don't explain your changes unless asked.\n",{"name":5,"description":7},"mine","1e7390741dffd3d5041fca4ebc056071ee3ba137","archives\u002Fuser-installed-skills\u002Fhumanize-writing\u002F954a5f2d444ba696\u002Fhumanize-writing",5,"https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub","https:\u002F\u002Fgithub.com\u002FEthanYoQ","www.orz.md","Part Marketer, Part AI Explorer.","2026-11-07 14:52:29",{"source":8,"skillName":5,"commands":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add EthanYoQ\u002FSkill-hub --skill humanize-writing",{"tool":72,"command":73},"bunx","bunx skills add EthanYoQ\u002FSkill-hub --skill humanize-writing",{"tool":75,"command":76},"pnpm","pnpm dlx skills add EthanYoQ\u002FSkill-hub --skill humanize-writing","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Farchives\u002Fuser-installed-skills\u002Fhumanize-writing\u002F954a5f2d444ba696\u002Fhumanize-writing\u002FSKILL.md",true,[80,86],{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fai-patterns-dictionary.md","REFERENCE","参考文档",8227,"https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Farchives\u002Fuser-installed-skills\u002Fhumanize-writing\u002F954a5f2d444ba696\u002Fhumanize-writing\u002Freferences\u002Fai-patterns-dictionary.md",{"path":87,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Fvoices.md",6845,"https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Farchives\u002Fuser-installed-skills\u002Fhumanize-writing\u002F954a5f2d444ba696\u002Fhumanize-writing\u002Freferences\u002Fvoices.md",[91,118,147,170,188,203],{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":98,"publishedAt":52},"01M713CBDSYARG4PXFXK2R2NNN","xhs-pharma-social-listening","Run evidence-disciplined Xiaohongshu social listening for foreign pharma employee pain points. Use when the user asks to collect and analyze notes\u002Fcomments about pharma companies, aliases, roles, compliance, medical affairs, or AI topics, then produce a cited and scored sampled-insight report. Includes independent-evidence counting, MediaCrawler batch collection, and CAPTCHA\u002F461 fallback to Agent Reach\u002FOpenCLI.","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Fskills\u002F10-business-industry\u002Fxhs-pharma-social-listening\u002FSKILL.md",[97],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[99,100,101,102,103,104,50,105,106,107,108,109,110,111,112,113,114,115,116,117],"social","xhs pharma social listening","social listening","xhs","medical","counting","collection","batch","analyze","notes","run","opencli","fallback","captcha","agent reach","evidence","for","collect","produce",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":128,"publishedAt":52},"01M713C8Q76ZP0WXXBRAFKS6EE","healthcare-phi-compliance","Protected Health Information (PHI) and Personally Identifiable Information (PII) compliance patterns for healthcare applications. Covers data classification, access control, audit trails, encryption, and common leak vectors. Use when code touches PHI or PII in a healthcare system, or when auditing access control, audit trails, or leak vectors.","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Fskills\u002F10-business-industry\u002Fhealthcare-phi-compliance\u002FSKILL.md",[124,125],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":126,"categoryName":127,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000037","律师与法务",[129,130,131,132,133,134,135,136,50,137,138,139,140,141,142,143,115,144,145,146],"healthcare","phi","compliance","healthcare phi compliance","pii","compliance patterns","information","access","encryption","code","common","audit","data","patterns","Access Control","system","applications","Auditing Access Control",{"skillNo":148,"name":149,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":154,"publishedAt":52},"01M713C5R2GE43X45T2K75TB76","healthcare-eval-harness","Patient safety evaluation harness for healthcare application deployments. Automated test suites for CDSS accuracy, PHI exposure, clinical workflow integrity, and integration compliance. Blocks deployments on safety failures. Use when a healthcare deployment must be gated on patient-safety tests for CDSS accuracy, PHI exposure, and workflow integrity.","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Fskills\u002F10-business-industry\u002Fhealthcare-eval-harness\u002FSKILL.md",[153],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[129,155,156,157,158,159,160,50,161,162,163,164,130,115,165,166,167,168,42,169],"eval","harness","healthcare eval harness","eval harness","clinical","patient","workflow","Evaluation","Safety","integrity","deployment","accuracy","tests","deployments","super",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":174,"categories":175,"keywords":177,"publishedAt":52},"01M713C2J17S91VYR7A8M696VR","healthcare-emr-patterns","EMR\u002FEHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Fskills\u002F10-business-industry\u002Fhealthcare-emr-patterns\u002FSKILL.md",[176],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[129,178,142,179,180,103,159,181,50,182,183,184,163,141,185,186,187,115,145,42],"EMR","healthcare emr patterns","decision","workflows","support","clinical decision support","features","ui","as","development",{"skillNo":189,"name":190,"nameZh":6,"description":191,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":192,"categories":193,"keywords":195,"publishedAt":52},"01M713BZERTXV0N8X6SW9DDVWZ","healthcare-cdss-patterns","Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks, dose validation, clinical scoring, or alert severity.","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Fskills\u002F10-business-industry\u002Fhealthcare-cdss-patterns\u002FSKILL.md",[194],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[129,142,196,180,159,178,181,50,197,198,182,183,199,187,144,200,42,201,169,202],"healthcare cdss patterns","scoring","interaction","severity","classification","alert","decision support",{"skillNo":204,"name":205,"nameZh":6,"description":206,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":207,"categories":208,"keywords":210,"publishedAt":52},"01M713BVK3PQR7V4ZKYGMWMXJD","dxy-task-clarify","用户的请求含糊、缺背景、缺资料说明、缺读者或用途时使用。先用少量带选项的追问把任务问清楚，写成任务卡，用户确认后再执行。尤其适用于医生、科研人员和药企各岗位的工作，例如「帮我分析一下这些数据」「帮我准备明天的拜访」「写个总结」「做个 PPT」「回一下这封邮件」「整理一下会议纪要」「整理一下这些文献」「帮我准备下周的讲课」「写个病例汇报」「帮我写个提示词」。用户说「先问我」「帮我理清需求」「我不知道怎么描述」「我不会问 AI」时也使用。用途、资料、读者都已说清的请求，纯翻译，以及写代码、改代码，不使用。","https:\u002F\u002Fgithub.com\u002FEthanYoQ\u002FSkill-hub\u002Fblob\u002Fmine\u002Fskills\u002F10-business-industry\u002Fdxy-task-clarify\u002FSKILL.md",[209],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[211,212,213,214,215,216,217,218],"clarify","dxy task clarify","task","pptx","整理","翻译","数据","总结"]