[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6MHSABAXZDXE2RGD1WSHQA2":3,"skill-same:01M6MHSABAXZDXE2RGD1WSHQA2":74},{"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":27,"publishedAt":45,"linkOnly":46,"markdownContent":47,"markdownBody":48,"frontMatter":49,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":13,"repositoryHtmlUrl":57,"repositoryHomepageUrl":6,"ownerHtmlUrl":58,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":59,"install":60,"resources":73},"01M6MHSABAXZDXE2RGD1WSHQA2","linkedin-profile",null,"Use when someone wants their LinkedIn profile audited or rewritten — headline, About section, experience bullets, Featured, banner, recommendations — or says \"fix my headline\", \"my profile gets views but nothing happens\", \"optimize my LinkedIn profile\", \"what should my About section say\". Scores the headline on five dimensions, audits the whole profile 0-100 and ranks fixes by points per hour, and assembles an About section that survives the \"…see more\" fold.","JiayiV\u002Fquestion_mixing","JiayiV","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54466889?v=4","01M6JFJYYMRZ3QRGP9339JNQ2K","01M6JFJZ35KB0QVT50NAHPJA7G",0,"MIT","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fpublic-02-claude-skills-main-marketing-linkedin-skills-linkedin-profile-skill-6156cb20\u002FSKILL.md",[17,22],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000019","营销推广","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000035","市场营销","PROFESSION","适用职业",[28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"linkedin","profile","linkedin profile","fixes","marketing","my","more","about","banner","recommendations","dimensions","but","optimize","Fold","say","use","fix","2026-11-10 10:12:30",false,"---\nname: linkedin-profile\ndescription: Use when someone wants their LinkedIn profile audited or rewritten — headline, About section, experience bullets, Featured, banner, recommendations — or says \"fix my headline\", \"my profile gets views but nothing happens\", \"optimize my LinkedIn profile\", \"what should my About section say\". Scores the headline on five dimensions, audits the whole profile 0-100 and ranks fixes by points per hour, and assembles an About section that survives the \"…see more\" fold.\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Alireza Rezvani\n  category: marketing\n  updated: 2026-08-25\n---\n\n# LinkedIn Profile — audit, then rewrite the parts that pay\n\nA profile is not a CV. A CV is read by someone who already decided to consider you; a\nprofile is read by someone deciding whether to. Three readers, in descending volume: the\n**scanner** (three seconds, from your comment on someone else's post — sees photo and\nheadline only), the **evaluator** (forty seconds — headline, half the About, Featured), the\n**decider** (minutes — everything). Almost all traffic is the scanner. Almost all conversion\nis the decider.\n\n## Workflow\n\n**1. Audit before rewriting.** Ask them to describe their profile section by section, or\nhave them fill [`assets\u002Fprofile_worksheet.md`](assets\u002Fprofile_worksheet.md), then:\n\n```bash\npython3 scripts\u002Fprofile_completeness_auditor.py --input profile.json --output human\n```\n\nExit 0 STRONG \u002F 2 INCOMPLETE \u002F 3 WEAK. It ranks every gap by **points per hour** and prints\na first-hour plan — usually Featured, Open To, and skills, which cost minutes and recover\nreal points. Start there, not with the About section they wanted to agonise over.\n\n**2. Headline next — it is the only string that travels.** It rides along with every comment,\nsearch result, and invitation.\n\n```bash\npython3 scripts\u002Fheadline_scorer.py --headline \"...\" --output human\n```\n\nFive dimensions at 20 points: audience, outcome, proof, searchability, clarity. Exit 0 SHIP\n(≥75) \u002F 2 SHARPEN \u002F 3 REWRITE. It also checks the 220-character cap and whether the first\n~60 characters — the part that survives in search results and invitation previews — carry\nanything.\n\nIterate here. Two or three passes is normal; the stop condition is exit 0, or the user\nsaying they would say it out loud to a peer.\n\n**3. About section — write to the fold.** LinkedIn collapses it after roughly 265-300\ncharacters. Collect the five parts from the user, then assemble:\n\n```bash\npython3 scripts\u002Fabout_section_builder.py --input about.json --output human\n```\n\nIt refuses a fold that cuts mid-sentence, a fold carrying no audience and no proof, a\nmissing call to action, and anything over 2,600 characters.\n\n**4. Experience, Featured, recommendations.** Rewrite duty lists as outcomes. Pin one\nartifact a stranger could evaluate in sixty seconds. Ask for two specific recommendations by\nnaming the project and offering a first draft.\n\n## Rules\n\n- **Never invent a credential, a metric, or a role.** Every number on a profile is checkable\n  by someone. If the proof does not exist, the claim is qualitative or it is absent.\n- **First person.** A profile in third person reads as a press release someone else wrote.\n- **The fold is the section.** Whatever sits above \"…see more\" is what most readers get.\n- **Front-load the headline.** The strongest segment first; everything after is a bonus.\n- **Do not fetch anything.** The user describes their own profile; nothing is scraped.\n\n## Scripts\n\n| Script | Role |\n|---|---|\n| [`scripts\u002Fheadline_scorer.py`](scripts\u002Fheadline_scorer.py) | Headline 0-100 on audience \u002F outcome \u002F proof \u002F searchability \u002F clarity, plus the 220-char cap and front-load check. |\n| [`scripts\u002Fprofile_completeness_auditor.py`](scripts\u002Fprofile_completeness_auditor.py) | Whole profile 0-100 across 14 weighted checks; fixes ranked by points per hour with a first-hour plan. |\n| [`scripts\u002Fabout_section_builder.py`](scripts\u002Fabout_section_builder.py) | Assembles the About section from named parts and refuses a broken fold, a missing CTA, or an over-length section. |\n\n## References and assets\n\n- [`references\u002Fprofile_architecture.md`](references\u002Fprofile_architecture.md) — what each section is for, and the three readers (7 sources)\n- [`references\u002Fheadline_and_positioning.md`](references\u002Fheadline_and_positioning.md) — the 220 characters that follow you everywhere (7 sources)\n\n- [`assets\u002Fprofile_worksheet.md`](assets\u002Fprofile_worksheet.md) — fillable section-by-section worksheet\n- [`assets\u002Fexample_profile.json`](assets\u002Fexample_profile.json) — input shape for the auditor\n\n## Distinct from\n\n- **`linkedin-strategy`** — what to post and how often. This is who you are before you post.\n  If the audience answer is fuzzy, run `positioning_brief.py` there first; the headline\n  falls out of a good brief in ten minutes.\n- **`product-team\u002F`, `c-level-advisor\u002F`** — career and role strategy. This writes the profile,\n  not the career plan.\n\n---\n\n**Version:** 1.0.0\n","# LinkedIn Profile — audit, then rewrite the parts that pay\n\nA profile is not a CV. A CV is read by someone who already decided to consider you; a\nprofile is read by someone deciding whether to. Three readers, in descending volume: the\n**scanner** (three seconds, from your comment on someone else's post — sees photo and\nheadline only), the **evaluator** (forty seconds — headline, half the About, Featured), the\n**decider** (minutes — everything). Almost all traffic is the scanner. Almost all conversion\nis the decider.\n\n## Workflow\n\n**1. Audit before rewriting.** Ask them to describe their profile section by section, or\nhave them fill [`assets\u002Fprofile_worksheet.md`](assets\u002Fprofile_worksheet.md), then:\n\n```bash\npython3 scripts\u002Fprofile_completeness_auditor.py --input profile.json --output human\n```\n\nExit 0 STRONG \u002F 2 INCOMPLETE \u002F 3 WEAK. It ranks every gap by **points per hour** and prints\na first-hour plan — usually Featured, Open To, and skills, which cost minutes and recover\nreal points. Start there, not with the About section they wanted to agonise over.\n\n**2. Headline next — it is the only string that travels.** It rides along with every comment,\nsearch result, and invitation.\n\n```bash\npython3 scripts\u002Fheadline_scorer.py --headline \"...\" --output human\n```\n\nFive dimensions at 20 points: audience, outcome, proof, searchability, clarity. Exit 0 SHIP\n(≥75) \u002F 2 SHARPEN \u002F 3 REWRITE. It also checks the 220-character cap and whether the first\n~60 characters — the part that survives in search results and invitation previews — carry\nanything.\n\nIterate here. Two or three passes is normal; the stop condition is exit 0, or the user\nsaying they would say it out loud to a peer.\n\n**3. About section — write to the fold.** LinkedIn collapses it after roughly 265-300\ncharacters. Collect the five parts from the user, then assemble:\n\n```bash\npython3 scripts\u002Fabout_section_builder.py --input about.json --output human\n```\n\nIt refuses a fold that cuts mid-sentence, a fold carrying no audience and no proof, a\nmissing call to action, and anything over 2,600 characters.\n\n**4. Experience, Featured, recommendations.** Rewrite duty lists as outcomes. Pin one\nartifact a stranger could evaluate in sixty seconds. Ask for two specific recommendations by\nnaming the project and offering a first draft.\n\n## Rules\n\n- **Never invent a credential, a metric, or a role.** Every number on a profile is checkable\n  by someone. If the proof does not exist, the claim is qualitative or it is absent.\n- **First person.** A profile in third person reads as a press release someone else wrote.\n- **The fold is the section.** Whatever sits above \"…see more\" is what most readers get.\n- **Front-load the headline.** The strongest segment first; everything after is a bonus.\n- **Do not fetch anything.** The user describes their own profile; nothing is scraped.\n\n## Scripts\n\n| Script | Role |\n|---|---|\n| [`scripts\u002Fheadline_scorer.py`](scripts\u002Fheadline_scorer.py) | Headline 0-100 on audience \u002F outcome \u002F proof \u002F searchability \u002F clarity, plus the 220-char cap and front-load check. |\n| [`scripts\u002Fprofile_completeness_auditor.py`](scripts\u002Fprofile_completeness_auditor.py) | Whole profile 0-100 across 14 weighted checks; fixes ranked by points per hour with a first-hour plan. |\n| [`scripts\u002Fabout_section_builder.py`](scripts\u002Fabout_section_builder.py) | Assembles the About section from named parts and refuses a broken fold, a missing CTA, or an over-length section. |\n\n## References and assets\n\n- [`references\u002Fprofile_architecture.md`](references\u002Fprofile_architecture.md) — what each section is for, and the three readers (7 sources)\n- [`references\u002Fheadline_and_positioning.md`](references\u002Fheadline_and_positioning.md) — the 220 characters that follow you everywhere (7 sources)\n\n- [`assets\u002Fprofile_worksheet.md`](assets\u002Fprofile_worksheet.md) — fillable section-by-section worksheet\n- [`assets\u002Fexample_profile.json`](assets\u002Fexample_profile.json) — input shape for the auditor\n\n## Distinct from\n\n- **`linkedin-strategy`** — what to post and how often. This is who you are before you post.\n  If the audience answer is fuzzy, run `positioning_brief.py` there first; the headline\n  falls out of a good brief in ten minutes.\n- **`product-team\u002F`, `c-level-advisor\u002F`** — career and role strategy. This writes the profile,\n  not the career plan.\n\n---\n\n**Version:** 1.0.0\n",{"name":5,"license":14,"metadata":50,"description":7},{"author":51,"updated":52,"version":53,"category":32},"Alireza Rezvani",1787616000000,"1.0.0","main","068c2486ccc0f8d200a3db4d21ec137064eda3b4","skills\u002Fpublic-02-claude-skills-main-marketing-linkedin-skills-linkedin-profile-skill-6156cb20","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing","https:\u002F\u002Fgithub.com\u002FJiayiV","2026-08-25 16:30:52",{"source":8,"skillName":5,"commands":61,"prompt":71,"zipAvailable":72},[62,65,68],{"tool":63,"command":64},"npx","npx skills add JiayiV\u002Fquestion_mixing --skill linkedin-profile",{"tool":66,"command":67},"bunx","bunx skills add JiayiV\u002Fquestion_mixing --skill linkedin-profile",{"tool":69,"command":70},"pnpm","pnpm dlx skills add JiayiV\u002Fquestion_mixing --skill linkedin-profile","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fpublic-02-claude-skills-main-marketing-linkedin-skills-linkedin-profile-skill-6156cb20\u002FSKILL.md",true,[],[75,100,127,158,186,219],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":79,"categories":80,"keywords":81,"publishedAt":45},"01M6NN9PJS9NHWPDG4QP93BP8F","webmcpify","Make a web app agent-ready — propose a WebMCP tool manifest, integrate, verify in a real browser, heal; unrelated code stays untouched. Use for \"webmcpify\", \"add WebMCP\", or \"expose app actions to AI agents\".","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fwebmcpify\u002FSKILL.md",[],[77,82,83,84,85,86,87,88,89,90,91,92,93,43,94,95,96,97,98,99],"github","ai agents","web","notes","code","browser","https","actions","manifest","inventory","verify","tool","ready","unrelated","app","scope","for","webmcp",{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":104,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":107,"publishedAt":45},"01M6NN6KZE5RBN6NGHN2WXV1RE","vardoger-analyze","Use when the user asks to personalize the GitHub Copilot CLI assistant, adapt Copilot to their style, use vardoger, or analyze their Copilot CLI conversation history. Reads the local session directory at `~\u002F.copilot\u002Fsession-state\u002F`, extracts recurring preferences and conventions, and writes a fenced personalization block into `~\u002F.copilot\u002Fcopilot-instructions.md`. Runs entirely on the user's machine via the local `vardoger` CLI (`pipx install vardoger`); no network calls and no uploads. Triggers: 'personalize my copilot', 'analyze my copilot history', 'tailor copilot to me', 'run vardoger', 'update my copilot instructions from history', 'make copilot learn my style'.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fvardoger-analyze\u002FSKILL.md",[],[108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,33,125,126],"vardoger analyze","analyze","directory","cli","github copilot","copilot","run","update","learn","network","my style","install","conversation","me","local","github copilot cli","pipx","at","copilot instructions",{"skillNo":128,"name":129,"nameZh":6,"description":130,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":131,"categories":132,"keywords":139,"publishedAt":45},"01M6NN3CZGQP3XAJ04BM1NNYGT","transloadit-media-processing","Process media files (video, audio, images, documents) using Transloadit. Use when asked to encode video to HLS\u002FMP4, generate thumbnails, resize or watermark images, extract audio, concatenate clips, add subtitles, OCR documents, or run any media processing pipeline. Covers 86+ processing robots for file transformation at scale.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Ftransloadit-media-processing\u002FSKILL.md",[133,136],{"categoryNo":134,"categoryName":135,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":137,"categoryName":138,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[140,141,142,143,144,145,146,147,148,149,150,151,152,43,153,154,155,156,98,157],"transloadit media processing","Media","media processing","processing","MCP","mcp server","documents","subtitles","pipeline","ocr","Video","Audio","mp4","images","files","transformation","free","hls",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":167,"publishedAt":45},"01M6NN28E92F9GH4WFYQ2H1Y15","terraform-azurerm-set-diff-analyzer","Analyze Terraform plan JSON output for AzureRM Provider to distinguish between false-positive diffs (order-only changes in Set-type attributes) and actual resource changes. Use when reviewing terraform plan output for Azure resources like Application Gateway, Load Balancer, Firewall, Front Door, NSG, and other resources with Set-type attributes that cause spurious diffs due to internal ordering changes.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fterraform-azurerm-set-diff-analyzer\u002FSKILL.md",[164],{"categoryNo":165,"categoryName":166,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",[168,169,170,171,172,173,174,175,176,43,177,178,179,180,181,182,183,184,185,98],"terraform","SET","terraform azurerm set diff analyzer","diff","analyzer","diffs","azure","gateway","firewall","only","resource changes","provider","resources","load balancer","attributes","front","load","balancer",{"skillNo":187,"name":188,"nameZh":6,"description":189,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":190,"categories":191,"keywords":201,"publishedAt":45},"01M6NN1QMH2TDYWTH3XY3N5XPV","technical-job-search","Use this skill when a software engineer asks for help with job search tasks: parsing or analyzing a job description, tailoring a CV\u002Fresume, writing a cover letter, evaluating a job offer, or drafting a post-interview follow-up email. Do not activate for general career advice unrelated to an active job search action.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Ftechnical-job-search\u002FSKILL.md",[192,195,198],{"categoryNo":193,"categoryName":194,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":196,"categoryName":197,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000036","内容创作者",{"categoryNo":199,"categoryName":200,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000038","人力资源",[202,203,204,205,206,207,208,209,109,210,43,211,212,213,214,215,216,217,98,218],"search","Job Search","technical job search","technical","writing","tasks","email","parsing","interview","up","engineer","general","activate","do","task","cv","letter",{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":223,"categories":224,"keywords":225,"publishedAt":45},"01M6NMZFA67XYS1GS09WT42235","steno-mode","Shorthand-first response compression that cuts ~40% of response tokens while preserving technical precision and exact literals. Use when the user says \"steno mode\", \"shorthand mode\", \"compressed responses\", \"token reduction\", \"brief structured output\", or invokes \u002Fsteno. Supports four compression levels: lite, brief, court, machine. Do not trigger for requests needing polished prose such as onboarding\u002Ftutorial content, stakeholder or customer-facing copy, or teaching-focused explanations.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fsteno-mode\u002FSKILL.md",[],[226,227,228,229,230,205,231,43,215,232,233,234,235,236,237,238,239,240,98,241],"steno mode","mode","customer","brief","first","tutorial","teaching","tokens","as","trigger","structured output","machine","output","court","requests","response compression"]