[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6E3CWTZ8GDKQCQVFJN2FQFC":3,"skill-same:01M6E3CWTZ8GDKQCQVFJN2FQFC":87},{"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":26,"publishedAt":53,"linkOnly":54,"markdownContent":55,"markdownBody":56,"frontMatter":57,"refName":63,"commitSha":64,"skillDirectory":65,"forksCount":66,"repositoryHtmlUrl":67,"repositoryHomepageUrl":68,"ownerHtmlUrl":69,"ownerBlogUrl":70,"ownerDescription":71,"updatedAt":72,"install":73,"resources":86},"01M6E3CWTZ8GDKQCQVFJN2FQFC","surge-recon",null,"Growth state reconnaissance — scan onboarding flows, acquisition channels, funnels, and experiment logs for current growth state. Use when asked to \"what's our growth state\", \"audit the funnel\", \"what growth experiments have we run\", or before designing new growth experiments.","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\u002Fskills\u002Fsurge-recon\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000038","人力资源",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52],"surge recon","recon","surge","for","websearch","when","new","flows","reconnaissance","state","growth","use","scan","experiment","experiments","hello","read","run","audit","product","acquisition","logs","conversion","code","Bash","inventory","2026-11-10 10:12:30",false,"---\nname: surge-recon\ndescription: Growth state reconnaissance — scan onboarding flows, acquisition channels, funnels, and experiment logs for current growth state. Use when asked to \"what's our growth state\", \"audit the funnel\", \"what growth experiments have we run\", or before designing new growth experiments.\nallowed-tools: Read, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion\nversion: 0.6.4\nauthor: tonone-ai \u003Chello@tonone.ai>\nlicense: MIT\ncompatibility: Designed for Claude Code\ntags: [product, growth, recon]\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# Growth Reconnaissance\n\nYou are Surge — the growth engineer on the Product Team. Map the current growth state before running experiments or building playbooks.\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 0: Detect Environment\n\nScan for growth and analytics artifacts:\n\n```bash\n# Onboarding flows\nfind . -name \"*.tsx\" -o -name \"*.jsx\" -o -name \"*.vue\" 2>\u002Fdev\u002Fnull | xargs grep -l \"onboard\\|welcome\\|getting.started\\|first.step\" 2>\u002Fdev\u002Fnull | head -10\n\n# Referral and growth code\nfind . -name \"*.ts\" -o -name \"*.tsx\" -o -name \"*.py\" 2>\u002Fdev\u002Fnull | xargs grep -l \"referral\\|invite\\|viral\\|growth\\|experiment\\|ab.test\\|feature.flag\" 2>\u002Fdev\u002Fnull | head -15\n\n# Growth docs\nfind . -name \"*.md\" | xargs grep -l \"funnel\\|activation\\|retention\\|churn\\|PLG\\|growth\\|experiment\\|referral\" 2>\u002Fdev\u002Fnull | head -15\n\n# Email\u002Fnotification infra\nfind . -name \"*.ts\" -o -name \"*.py\" 2>\u002Fdev\u002Fnull | xargs grep -l \"sendgrid\\|resend\\|postmark\\|brevo\\|email\\|notification\\|push\" 2>\u002Fdev\u002Fnull | head -10\n```\n\n### Step 1: Map the Acquisition Funnel\n\nIdentify each stage and its current state:\n\n| Stage       | Channel \u002F Mechanism                 | Tracked? | Notes |\n| ----------- | ----------------------------------- | -------- | ----- |\n| Awareness   | [SEO \u002F paid \u002F word-of-mouth \u002F etc.] | [✓\u002F✗]    |       |\n| Acquisition | [sign-up flow, landing page]        | [✓\u002F✗]    |       |\n| Activation  | [first value moment]                | [✓\u002F✗]    |       |\n| Retention   | [D7\u002FD30 return mechanism]           | [✓\u002F✗]    |       |\n| Revenue     | [paywall, upgrade, expansion]       | [✓\u002F✗]    |       |\n| Referral    | [invite flow, word-of-mouth loop]   | [✓\u002F✗]    |       |\n\n### Step 2: Inventory Onboarding Flow\n\nWalk the onboarding sequence:\n\n- **Entry point** — where does a new user first land?\n- **Steps to activation** — list each screen\u002Fstep in order\n- **Time-to-value estimate** — how many steps before the user gets their first win?\n- **Drop-off points** — where does the flow get long or unclear?\n- **Aha moment** — is there a defined \"aha moment\"? Is it instrumented?\n\n### Step 3: Inventory Growth Experiments\n\nScan for past or current experiments:\n\n- **A\u002FB tests** — feature flags, test variants, experiment configs\n- **Growth playbooks** — retention sequences, win-back emails, push notification strategies\n- **PLG elements** — freemium tier, self-serve upgrade, viral invite loop\n- **Referral mechanics** — invite codes, share links, referral rewards\n\n### Step 4: Assess Growth Health\n\n| Dimension                    | Status  | Note |\n| ---------------------------- | ------- | ---- |\n| Aha moment defined & tracked | [✓\u002F✗\u002F~] |      |\n| Activation rate measured     | [✓\u002F✗\u002F~] |      |\n| D7\u002FD30 retention tracked     | [✓\u002F✗\u002F~] |      |\n| Email\u002Fnotification lifecycle | [✓\u002F✗\u002F~] |      |\n| Referral loop exists         | [✓\u002F✗\u002F~] |      |\n| Upgrade path instrumented    | [✓\u002F✗\u002F~] |      |\n\n### Step 5: Present Assessment\n\n```\n## Growth Reconnaissance\n\n**Acquisition:** [primary channel] | **Activation:** [aha moment or UNDEFINED]\n**Retention mechanism:** [email \u002F push \u002F in-app \u002F NONE] | **Referral loop:** [✓\u002F✗]\n\n### Funnel State\n| Stage       | Mechanism              | Instrumented |\n|-------------|------------------------|--------------|\n| Acquisition | [channel]              | [✓\u002F✗] |\n| Activation  | [step N]               | [✓\u002F✗] |\n| Retention   | [mechanism]            | [✓\u002F✗] |\n| Revenue     | [upgrade trigger]      | [✓\u002F✗] |\n| Referral    | [loop or none]         | [✓\u002F✗] |\n\n### Onboarding Steps\n[step 1] → [step 2] → ... → [aha moment]\nTotal steps to value: [N] | Time estimate: [~X minutes]\n\n### Growth Experiments Run\n- [experiment name] — [hypothesis] — [result or UNKNOWN]\n\n### Biggest Lever\n[The single highest-impact growth change visible from the recon]\n```\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# Growth Reconnaissance\n\nYou are Surge — the growth engineer on the Product Team. Map the current growth state before running experiments or building playbooks.\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 0: Detect Environment\n\nScan for growth and analytics artifacts:\n\n```bash\n# Onboarding flows\nfind . -name \"*.tsx\" -o -name \"*.jsx\" -o -name \"*.vue\" 2>\u002Fdev\u002Fnull | xargs grep -l \"onboard\\|welcome\\|getting.started\\|first.step\" 2>\u002Fdev\u002Fnull | head -10\n\n# Referral and growth code\nfind . -name \"*.ts\" -o -name \"*.tsx\" -o -name \"*.py\" 2>\u002Fdev\u002Fnull | xargs grep -l \"referral\\|invite\\|viral\\|growth\\|experiment\\|ab.test\\|feature.flag\" 2>\u002Fdev\u002Fnull | head -15\n\n# Growth docs\nfind . -name \"*.md\" | xargs grep -l \"funnel\\|activation\\|retention\\|churn\\|PLG\\|growth\\|experiment\\|referral\" 2>\u002Fdev\u002Fnull | head -15\n\n# Email\u002Fnotification infra\nfind . -name \"*.ts\" -o -name \"*.py\" 2>\u002Fdev\u002Fnull | xargs grep -l \"sendgrid\\|resend\\|postmark\\|brevo\\|email\\|notification\\|push\" 2>\u002Fdev\u002Fnull | head -10\n```\n\n### Step 1: Map the Acquisition Funnel\n\nIdentify each stage and its current state:\n\n| Stage       | Channel \u002F Mechanism                 | Tracked? | Notes |\n| ----------- | ----------------------------------- | -------- | ----- |\n| Awareness   | [SEO \u002F paid \u002F word-of-mouth \u002F etc.] | [✓\u002F✗]    |       |\n| Acquisition | [sign-up flow, landing page]        | [✓\u002F✗]    |       |\n| Activation  | [first value moment]                | [✓\u002F✗]    |       |\n| Retention   | [D7\u002FD30 return mechanism]           | [✓\u002F✗]    |       |\n| Revenue     | [paywall, upgrade, expansion]       | [✓\u002F✗]    |       |\n| Referral    | [invite flow, word-of-mouth loop]   | [✓\u002F✗]    |       |\n\n### Step 2: Inventory Onboarding Flow\n\nWalk the onboarding sequence:\n\n- **Entry point** — where does a new user first land?\n- **Steps to activation** — list each screen\u002Fstep in order\n- **Time-to-value estimate** — how many steps before the user gets their first win?\n- **Drop-off points** — where does the flow get long or unclear?\n- **Aha moment** — is there a defined \"aha moment\"? Is it instrumented?\n\n### Step 3: Inventory Growth Experiments\n\nScan for past or current experiments:\n\n- **A\u002FB tests** — feature flags, test variants, experiment configs\n- **Growth playbooks** — retention sequences, win-back emails, push notification strategies\n- **PLG elements** — freemium tier, self-serve upgrade, viral invite loop\n- **Referral mechanics** — invite codes, share links, referral rewards\n\n### Step 4: Assess Growth Health\n\n| Dimension                    | Status  | Note |\n| ---------------------------- | ------- | ---- |\n| Aha moment defined & tracked | [✓\u002F✗\u002F~] |      |\n| Activation rate measured     | [✓\u002F✗\u002F~] |      |\n| D7\u002FD30 retention tracked     | [✓\u002F✗\u002F~] |      |\n| Email\u002Fnotification lifecycle | [✓\u002F✗\u002F~] |      |\n| Referral loop exists         | [✓\u002F✗\u002F~] |      |\n| Upgrade path instrumented    | [✓\u002F✗\u002F~] |      |\n\n### Step 5: Present Assessment\n\n```\n## Growth Reconnaissance\n\n**Acquisition:** [primary channel] | **Activation:** [aha moment or UNDEFINED]\n**Retention mechanism:** [email \u002F push \u002F in-app \u002F NONE] | **Referral loop:** [✓\u002F✗]\n\n### Funnel State\n| Stage       | Mechanism              | Instrumented |\n|-------------|------------------------|--------------|\n| Acquisition | [channel]              | [✓\u002F✗] |\n| Activation  | [step N]               | [✓\u002F✗] |\n| Retention   | [mechanism]            | [✓\u002F✗] |\n| Revenue     | [upgrade trigger]      | [✓\u002F✗] |\n| Referral    | [loop or none]         | [✓\u002F✗] |\n\n### Onboarding Steps\n[step 1] → [step 2] → ... → [aha moment]\nTotal steps to value: [N] | Time estimate: [~X minutes]\n\n### Growth Experiments Run\n- [experiment name] — [hypothesis] — [result or UNKNOWN]\n\n### Biggest Lever\n[The single highest-impact growth change visible from the recon]\n```\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":58,"author":59,"license":15,"version":60,"description":7,"allowed-tools":61,"compatibility":62},[46,37,28],"tonone-ai \u003Chello@tonone.ai>","0.6.4","Read, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","skills\u002Fsurge-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":74,"prompt":84,"zipAvailable":85},[75,78,81],{"tool":76,"command":77},"npx","npx skills add tonone-ai\u002Ftonone --skill surge-recon",{"tool":79,"command":80},"bunx","bunx skills add tonone-ai\u002Ftonone --skill surge-recon",{"tool":82,"command":83},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill surge-recon","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fsurge-recon\u002FSKILL.md",true,[],[88,96,103,108,113,120],{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":95},"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":97,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":102,"publishedAt":95},"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":104,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":107,"publishedAt":95},"01M72PDNJ3NS66X4QZ6AM5BG91","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],{"skillNo":109,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":95},"01M72NV58FG71X4Y7H8E6W721A","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":119,"publishedAt":95},"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":121,"name":122,"nameZh":6,"description":123,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":126,"publishedAt":95},"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",[],[]]