[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6WSHMKBEVT4YVTBC4Y6NH22":3,"skill-same:01M6WSHMKBEVT4YVTBC4Y6NH22":85},{"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":23,"publishedAt":45,"linkOnly":46,"markdownContent":47,"markdownBody":48,"frontMatter":49,"refName":55,"commitSha":56,"skillDirectory":57,"forksCount":58,"repositoryHtmlUrl":59,"repositoryHomepageUrl":60,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6WSHMKBEVT4YVTBC4Y6NH22","reach-recon",null,"Read-only audit of paid acquisition and demand gen — channels, spend, CAC, tracking integrity, creative health. Use when asked to \"audit our paid campaigns\", \"why is our CAC rising\", \"review our demand gen programs\".","tonone-ai\u002Ftonone","tonone-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252718527?v=4","01M6E0753HQVTQWJCQCV4AHAAS","tonone.ai","01M6E075828PMH1WMX0VEB5SV8",77,"MIT","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Freach\u002Fskills\u002Freach-recon\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"reach recon","recon","paid","for","campaigns","integrity","marketing","write","hello","read","why","audit","acquisition","creative health","review","websearch","code","Bash","when","only","paid-acquisition","2026-11-10 10:12:30",false,"---\nname: reach-recon\ndescription: Read-only audit of paid acquisition and demand gen — channels, spend, CAC, tracking integrity, creative health. Use when asked to \"audit our paid campaigns\", \"why is our CAC rising\", \"review our demand gen programs\".\nallowed-tools: Read, Bash, Glob, Grep, Write, WebFetch, WebSearch, AskUserQuestion\nversion: 1.0.0\nauthor: tonone-ai \u003Chello@tonone.ai>\nlicense: MIT\ncompatibility: Designed for Claude Code\ntags: [marketing, paid-acquisition]\n---\n\n\u003C!-- GENERATED from SKILL.md.tmpl by scripts\u002Fgen-skill-docs.py — edit the .tmpl or skills\u002F_sections\u002F*.md, not this file -->\n\n# Reach Recon\n\nYou are Reach — the Demand Generation & Paid Acquisition Lead on the Marketing Team.\n\nFollow the output format defined in docs\u002Foutput-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.\n\n## Steps\n\n### Step 1: Inventory channels and data\n\nFind ad-account exports, campaign sheets, CRM reports, UTM docs, and tracking code (`Grep` for `gtag`, `fbq`, `linkedin`, `utm_`, `gclid`). Ask the user for trailing 90-day spend, leads, opportunities, and closed-won by channel. List missing data explicitly.\n\n### Step 2: Validate tracking\n\nCheck: conversion events fire once, UTM conventions consistent (lowercase, fixed taxonomy), `gclid`\u002F`li_fat_id` captured into CRM, offline conversion import running, consent mode set. A channel with broken pipeline tracking is reported as unmeasured, not as zero.\n\n### Step 3: Compute efficiency per channel\n\nFor each channel: spend, leads, MQL rate, SQL rate, opportunities, pipeline, closed-won, CAC (spend \u002F new customers), cost per opportunity, payback months. Separate branded search. Compare platform-reported conversions to CRM — flag a gap above 30%.\n\n### Step 4: Find the marginal signal\n\nPlot weekly spend vs. cost per opportunity per channel. Flag channels where cost per opportunity rose over 25% as spend rose over 20% (saturated). Flag channels with under 3 months of data as unproven.\n\n### Step 5: Review creative and landing health\n\nPer channel: number of live concepts (target 3-5), age of oldest top creative (fatigue at 4-6 weeks on social), CTR trend, landing page conversion vs. 3-5% benchmark for B2B demo pages. Report top 3 findings and one next action.\n\n## Key Rules\n\n- Read-only\n- CRM outcomes outrank platform-reported outcomes\n- Unmeasured is not zero: label it\n- One next action with expected CAC or pipeline effect\n\n## Output Format\n\nChannel efficiency table, tracking integrity checklist, top 3 findings, one next action.\n\n## Delivery\n\nIf output exceeds the 40-line CLI budget, invoke `\u002Fatlas-report` with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.\n","\u003C!-- GENERATED from SKILL.md.tmpl by scripts\u002Fgen-skill-docs.py — edit the .tmpl or skills\u002F_sections\u002F*.md, not this file -->\n\n# Reach Recon\n\nYou are Reach — the Demand Generation & Paid Acquisition Lead on the Marketing Team.\n\nFollow the output format defined in docs\u002Foutput-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.\n\n## Steps\n\n### Step 1: Inventory channels and data\n\nFind ad-account exports, campaign sheets, CRM reports, UTM docs, and tracking code (`Grep` for `gtag`, `fbq`, `linkedin`, `utm_`, `gclid`). Ask the user for trailing 90-day spend, leads, opportunities, and closed-won by channel. List missing data explicitly.\n\n### Step 2: Validate tracking\n\nCheck: conversion events fire once, UTM conventions consistent (lowercase, fixed taxonomy), `gclid`\u002F`li_fat_id` captured into CRM, offline conversion import running, consent mode set. A channel with broken pipeline tracking is reported as unmeasured, not as zero.\n\n### Step 3: Compute efficiency per channel\n\nFor each channel: spend, leads, MQL rate, SQL rate, opportunities, pipeline, closed-won, CAC (spend \u002F new customers), cost per opportunity, payback months. Separate branded search. Compare platform-reported conversions to CRM — flag a gap above 30%.\n\n### Step 4: Find the marginal signal\n\nPlot weekly spend vs. cost per opportunity per channel. Flag channels where cost per opportunity rose over 25% as spend rose over 20% (saturated). Flag channels with under 3 months of data as unproven.\n\n### Step 5: Review creative and landing health\n\nPer channel: number of live concepts (target 3-5), age of oldest top creative (fatigue at 4-6 weeks on social), CTR trend, landing page conversion vs. 3-5% benchmark for B2B demo pages. Report top 3 findings and one next action.\n\n## Key Rules\n\n- Read-only\n- CRM outcomes outrank platform-reported outcomes\n- Unmeasured is not zero: label it\n- One next action with expected CAC or pipeline effect\n\n## Output Format\n\nChannel efficiency table, tracking integrity checklist, top 3 findings, one next action.\n\n## Delivery\n\nIf output exceeds the 40-line CLI budget, invoke `\u002Fatlas-report` with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.\n",{"name":5,"tags":50,"author":51,"license":15,"version":52,"description":7,"allowed-tools":53,"compatibility":54},[30,44],"tonone-ai \u003Chello@tonone.ai>","1.0.0","Read, Bash, Glob, Grep, Write, WebFetch, WebSearch, AskUserQuestion","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","team\u002Freach\u002Fskills\u002Freach-recon",11,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone","https:\u002F\u002Fsecond.tonone.ai","https:\u002F\u002Fgithub.com\u002Ftonone-ai","https:\u002F\u002Ftonone.ai","Founded by @thisisfatih","2026-11-11 05:05:57",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add tonone-ai\u002Ftonone --skill reach-recon",{"tool":71,"command":72},"bunx","bunx skills add tonone-ai\u002Ftonone --skill reach-recon",{"tool":74,"command":75},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill reach-recon","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Freach\u002Fskills\u002Freach-recon\u002FSKILL.md",true,[79],{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"SKILL.md.tmpl","OTHER","其他",2329,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Freach\u002Fskills\u002Freach-recon\u002FSKILL.md.tmpl",[86,94,101,106,111,118],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":93},"01M72QSK7R99K8FWYFNYTXJGR2","helm-autoplan","Chained brief-to-decision pipeline. Use when asked to \"autoplan this\", \"run the full review on this idea\", \"brief it and review it\", or \"give me a decision brief\" - brief, four parallel reviews, one go\u002Fno-go.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fhelm\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],"2026-11-10 22:39:42",{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":100,"publishedAt":93},"01M72Q6V4CB8E877RT5KJRSSB7","apex-second-opinion","Optional cross-model review of a diff or plan through an external CLI (codex, gemini, llm) already on PATH, with redaction and per-run consent. Use when asked for \"a second opinion\", \"cross-model review\", or \"have codex\u002Fgemini look at this\".","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fapex\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":102,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":93},"01M72PDNJ3NS66X4QZ6AM5BG91","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],{"skillNo":107,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":110,"publishedAt":93},"01M72NV58FG71X4Y7H8E6W721A","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":112,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":117,"publishedAt":93},"01M72NEBG81JH7YNSDXYT8NHHE","helm-office-hours","Forcing-function intake before any brief. Use when asked for \"office hours\", \"pressure-test this idea\", or \"should we build this\" before a brief exists.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Fproduct-team\u002Fskills\u002Fhelm-office-hours\u002FSKILL.md",[],[],{"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":124,"publishedAt":93},"01M72NE7AS597YW6999C56CESR","helm-init","Short interview that writes PRODUCT.md, the durable product truth other skills read. Use when asked to \"init product\", \"write PRODUCT.md\", or \"set up product context\". Prefills from README and repo, asks max 6 questions.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Fproduct-team\u002Fskills\u002Fhelm-init\u002FSKILL.md",[],[]]