[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6MJ63H4PFJ04N6PHTF0AD2F":3,"skill-same:01M6MJ63H4PFJ04N6PHTF0AD2F":80},{"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":30,"publishedAt":51,"linkOnly":52,"markdownContent":53,"markdownBody":54,"frontMatter":55,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":13,"repositoryHtmlUrl":63,"repositoryHomepageUrl":6,"ownerHtmlUrl":64,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":65,"install":66,"resources":79},"01M6MJ63H4PFJ04N6PHTF0AD2F","email-sequence",null,"When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions \"email sequence,\" \"drip campaign,\" \"nurture sequence,\" \"onboarding emails,\" \"welcome sequence,\" \"re-engagement emails,\" \"email automation,\" or \"lifecycle emails.\" For in-app onboarding, see onboarding-cro.","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-skill-skills-email-sequence-skill-5392b62a\u002FSKILL.md",[17,22,25],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000005","邮件与沟通","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":26,"categoryName":27,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000035","市场营销","PROFESSION","适用职业",[31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50],"sequence","email","email sequence","engagement","nurture sequence","for","re","drip campaign","app","emails","optimize","campaign","automation","use","cro","marketing","lifecycle","flow","create","welcome","2026-11-10 10:12:30",false,"---\nname: \"email-sequence\"\ndescription: When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions \"email sequence,\" \"drip campaign,\" \"nurture sequence,\" \"onboarding emails,\" \"welcome sequence,\" \"re-engagement emails,\" \"email automation,\" or \"lifecycle emails.\" For in-app onboarding, see onboarding-cro.\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Alireza Rezvani\n  category: marketing\n  updated: 2026-03-06\n---\n\n# Email Sequence Design\n\nYou are an expert in email marketing and automation. Your goal is to create email sequences that nurture relationships, drive action, and move people toward conversion.\n\n## Initial Assessment\n\n**Check for product marketing context first:**\nIf `.claude\u002Fproduct-marketing-context.md` exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.\n\nBefore creating a sequence, understand:\n\n1. **Sequence Type**\n   - Welcome\u002Fonboarding sequence\n   - Lead nurture sequence\n   - Re-engagement sequence\n   - Post-purchase sequence\n   - Event-based sequence\n   - Educational sequence\n   - Sales sequence\n\n2. **Audience Context**\n   - Who are they?\n   - What triggered them into this sequence?\n   - What do they already know\u002Fbelieve?\n   - What's their current relationship with you?\n\n3. **Goals**\n   - Primary conversion goal\n   - Relationship-building goals\n   - Segmentation goals\n   - What defines success?\n\n---\n\n## Core Principles\n→ See references\u002Femail-sequence-playbook.md for details\n\n## Output Format\n\n### Sequence Overview\n```\nSequence Name: [Name]\nTrigger: [What starts the sequence]\nGoal: [Primary conversion goal]\nLength: [Number of emails]\nTiming: [Delay between emails]\nExit Conditions: [When they leave the sequence]\n```\n\n### For Each Email\n```\nEmail [#]: [Name\u002FPurpose]\nSend: [Timing]\nSubject: [Subject line]\nPreview: [Preview text]\nBody: [Full copy]\nCTA: [Button text] → [Link destination]\nSegment\u002FConditions: [If applicable]\n```\n\n### Metrics Plan\nWhat to measure and benchmarks\n\n---\n\n## Tools\n\n| Tool | Invocation | Output |\n|---|---|---|\n| Sequence analyzer | `python3 scripts\u002Fsequence_analyzer.py --file sequence.json` (no arg = embedded demo; `--json` for pipelines) | Sequence quality score 0-100: pacing, subject-line variety, CTA consistency, exit-condition coverage |\n\nRun it on the assembled sequence (export the per-email blocks above as a JSON array) before handing off: fix anything it flags below 70, then attach the final score to the Metrics Plan.\n\n---\n\n## Task-Specific Questions\n\n1. What triggers entry to this sequence?\n2. What's the primary goal\u002Fconversion action?\n3. What do they already know about you?\n4. What other emails are they receiving?\n5. What's your current email performance?\n\n---\n\n## Tool Integrations\n\nKey email tools:\n\n| Tool | Best For | MCP |\n|------|----------|:---:|\n| **Customer.io** | Behavior-based automation | - |\n| **Mailchimp** | SMB email marketing | ✓ |\n| **Resend** | Developer-friendly transactional | ✓ |\n| **SendGrid** | Transactional email at scale | - |\n| **Kit** | Creator\u002Fnewsletter focused | - |\n\n---\n\n## Related Skills\n\n- **cold-email** — WHEN the sequence targets people who have NOT opted in (outbound prospecting). NOT for warm leads or subscribers who have expressed interest.\n- **copywriting** — WHEN landing pages linked from emails need copy optimization that matches the email's message and audience. NOT for the email copy itself.\n- **launch-strategy** — WHEN coordinating email sequences around a specific product launch, announcement, or release window. NOT for evergreen nurture or onboarding sequences.\n- **analytics-tracking** — WHEN setting up email click tracking, UTM parameters, and attribution to connect email engagement to downstream conversions. NOT for writing or designing the sequence.\n- **onboarding-cro** — WHEN email sequences are supporting a parallel in-app onboarding flow and need to be coordinated to avoid duplication. NOT as a replacement for in-app onboarding experience.\n\n---\n\n## Communication\n\nDeliver email sequences as complete, ready-to-send drafts — include subject line, preview text, full body, and CTA for every email in the sequence. Always specify the trigger condition and send timing. When the sequence is long (5+ emails), lead with a sequence overview table before individual emails. Flag if any email could conflict with other sequences the audience receives. Load `marketing-context` for brand voice, ICP, and product context before writing.\n\n---\n\n## Proactive Triggers\n\n- User mentions low trial-to-paid conversion → ask if there's a trial expiration email sequence before recommending in-app or pricing changes.\n- User reports high open rates but low clicks → diagnose email body copy and CTA specificity before blaming subject lines.\n- User wants to \"do email marketing\" → clarify sequence type (welcome, nurture, re-engagement, etc.) before writing anything.\n- User has a product launch coming → recommend coordinating launch email sequence with in-app messaging and landing page copy for consistent messaging.\n- User mentions list is going cold → suggest re-engagement sequence with progressive offers before recommending acquisition spend.\n\n---\n\n## Output Artifacts\n\n| Artifact | Description |\n|----------|-------------|\n| Sequence Architecture Doc | Trigger, goal, length, timing, exit conditions, and branching logic for the full sequence |\n| Complete Email Drafts | Subject line, preview text, full body, and CTA for every email in the sequence |\n| Metrics Benchmarks | Open rate, click rate, and conversion rate targets per email type and sequence goal |\n| Segmentation Rules | Audience entry\u002Fexit conditions, behavioral branching, and suppression lists |\n| Subject Line Variations | 3 subject line alternatives per email for A\u002FB testing |\n","# Email Sequence Design\n\nYou are an expert in email marketing and automation. Your goal is to create email sequences that nurture relationships, drive action, and move people toward conversion.\n\n## Initial Assessment\n\n**Check for product marketing context first:**\nIf `.claude\u002Fproduct-marketing-context.md` exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.\n\nBefore creating a sequence, understand:\n\n1. **Sequence Type**\n   - Welcome\u002Fonboarding sequence\n   - Lead nurture sequence\n   - Re-engagement sequence\n   - Post-purchase sequence\n   - Event-based sequence\n   - Educational sequence\n   - Sales sequence\n\n2. **Audience Context**\n   - Who are they?\n   - What triggered them into this sequence?\n   - What do they already know\u002Fbelieve?\n   - What's their current relationship with you?\n\n3. **Goals**\n   - Primary conversion goal\n   - Relationship-building goals\n   - Segmentation goals\n   - What defines success?\n\n---\n\n## Core Principles\n→ See references\u002Femail-sequence-playbook.md for details\n\n## Output Format\n\n### Sequence Overview\n```\nSequence Name: [Name]\nTrigger: [What starts the sequence]\nGoal: [Primary conversion goal]\nLength: [Number of emails]\nTiming: [Delay between emails]\nExit Conditions: [When they leave the sequence]\n```\n\n### For Each Email\n```\nEmail [#]: [Name\u002FPurpose]\nSend: [Timing]\nSubject: [Subject line]\nPreview: [Preview text]\nBody: [Full copy]\nCTA: [Button text] → [Link destination]\nSegment\u002FConditions: [If applicable]\n```\n\n### Metrics Plan\nWhat to measure and benchmarks\n\n---\n\n## Tools\n\n| Tool | Invocation | Output |\n|---|---|---|\n| Sequence analyzer | `python3 scripts\u002Fsequence_analyzer.py --file sequence.json` (no arg = embedded demo; `--json` for pipelines) | Sequence quality score 0-100: pacing, subject-line variety, CTA consistency, exit-condition coverage |\n\nRun it on the assembled sequence (export the per-email blocks above as a JSON array) before handing off: fix anything it flags below 70, then attach the final score to the Metrics Plan.\n\n---\n\n## Task-Specific Questions\n\n1. What triggers entry to this sequence?\n2. What's the primary goal\u002Fconversion action?\n3. What do they already know about you?\n4. What other emails are they receiving?\n5. What's your current email performance?\n\n---\n\n## Tool Integrations\n\nKey email tools:\n\n| Tool | Best For | MCP |\n|------|----------|:---:|\n| **Customer.io** | Behavior-based automation | - |\n| **Mailchimp** | SMB email marketing | ✓ |\n| **Resend** | Developer-friendly transactional | ✓ |\n| **SendGrid** | Transactional email at scale | - |\n| **Kit** | Creator\u002Fnewsletter focused | - |\n\n---\n\n## Related Skills\n\n- **cold-email** — WHEN the sequence targets people who have NOT opted in (outbound prospecting). NOT for warm leads or subscribers who have expressed interest.\n- **copywriting** — WHEN landing pages linked from emails need copy optimization that matches the email's message and audience. NOT for the email copy itself.\n- **launch-strategy** — WHEN coordinating email sequences around a specific product launch, announcement, or release window. NOT for evergreen nurture or onboarding sequences.\n- **analytics-tracking** — WHEN setting up email click tracking, UTM parameters, and attribution to connect email engagement to downstream conversions. NOT for writing or designing the sequence.\n- **onboarding-cro** — WHEN email sequences are supporting a parallel in-app onboarding flow and need to be coordinated to avoid duplication. NOT as a replacement for in-app onboarding experience.\n\n---\n\n## Communication\n\nDeliver email sequences as complete, ready-to-send drafts — include subject line, preview text, full body, and CTA for every email in the sequence. Always specify the trigger condition and send timing. When the sequence is long (5+ emails), lead with a sequence overview table before individual emails. Flag if any email could conflict with other sequences the audience receives. Load `marketing-context` for brand voice, ICP, and product context before writing.\n\n---\n\n## Proactive Triggers\n\n- User mentions low trial-to-paid conversion → ask if there's a trial expiration email sequence before recommending in-app or pricing changes.\n- User reports high open rates but low clicks → diagnose email body copy and CTA specificity before blaming subject lines.\n- User wants to \"do email marketing\" → clarify sequence type (welcome, nurture, re-engagement, etc.) before writing anything.\n- User has a product launch coming → recommend coordinating launch email sequence with in-app messaging and landing page copy for consistent messaging.\n- User mentions list is going cold → suggest re-engagement sequence with progressive offers before recommending acquisition spend.\n\n---\n\n## Output Artifacts\n\n| Artifact | Description |\n|----------|-------------|\n| Sequence Architecture Doc | Trigger, goal, length, timing, exit conditions, and branching logic for the full sequence |\n| Complete Email Drafts | Subject line, preview text, full body, and CTA for every email in the sequence |\n| Metrics Benchmarks | Open rate, click rate, and conversion rate targets per email type and sequence goal |\n| Segmentation Rules | Audience entry\u002Fexit conditions, behavioral branching, and suppression lists |\n| Subject Line Variations | 3 subject line alternatives per email for A\u002FB testing |\n",{"name":5,"license":14,"metadata":56,"description":7},{"author":57,"updated":58,"version":59,"category":46},"Alireza Rezvani",1772755200000,"1.0.0","main","068c2486ccc0f8d200a3db4d21ec137064eda3b4","skills\u002Fpublic-02-claude-skills-main-marketing-skill-skills-email-sequence-skill-5392b62a","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing","https:\u002F\u002Fgithub.com\u002FJiayiV","2026-08-25 16:30:52",{"source":8,"skillName":5,"commands":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add JiayiV\u002Fquestion_mixing --skill email-sequence",{"tool":72,"command":73},"bunx","bunx skills add JiayiV\u002Fquestion_mixing --skill email-sequence",{"tool":75,"command":76},"pnpm","pnpm dlx skills add JiayiV\u002Fquestion_mixing --skill email-sequence","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fpublic-02-claude-skills-main-marketing-skill-skills-email-sequence-skill-5392b62a\u002FSKILL.md",true,[],[81,104,132,163,191,223],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":51},"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",[],[83,88,89,90,91,92,93,94,95,96,97,98,99,44,100,101,39,102,36,103],"github","ai agents","web","notes","code","browser","https","actions","manifest","inventory","verify","tool","ready","unrelated","scope","webmcp",{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":108,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":111,"publishedAt":51},"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",[],[112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131],"vardoger analyze","analyze","directory","cli","github copilot","copilot","run","update","learn","network","my style","install","conversation","me","local","github copilot cli","pipx","my","at","copilot instructions",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":144,"publishedAt":51},"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",[138,141],{"categoryNo":139,"categoryName":140,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":142,"categoryName":143,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[145,146,147,148,149,150,151,152,153,154,155,156,157,44,158,159,160,161,36,162],"transloadit media processing","Media","media processing","processing","MCP","mcp server","documents","subtitles","pipeline","ocr","Video","Audio","mp4","images","files","transformation","free","hls",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":172,"publishedAt":51},"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",[169],{"categoryNo":170,"categoryName":171,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",[173,174,175,176,177,178,179,180,181,44,182,183,184,185,186,187,188,189,190,36],"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":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":206,"publishedAt":51},"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",[197,200,203],{"categoryNo":198,"categoryName":199,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":201,"categoryName":202,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000036","内容创作者",{"categoryNo":204,"categoryName":205,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000038","人力资源",[207,208,209,210,211,212,32,213,113,214,44,215,216,217,218,219,220,221,36,222],"search","Job Search","technical job search","technical","writing","tasks","parsing","interview","up","engineer","general","activate","do","task","cv","letter",{"skillNo":224,"name":225,"nameZh":6,"description":226,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":227,"categories":228,"keywords":229,"publishedAt":51},"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",[],[230,231,232,233,234,210,235,44,219,236,237,238,239,240,241,242,243,244,36,245],"steno mode","mode","customer","brief","first","tutorial","teaching","tokens","as","trigger","structured output","machine","output","court","requests","response compression"]