[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6WSQP8Q9F1XFMMW74JJ4F8N":3,"skill-same:01M6WSQP8Q9F1XFMMW74JJ4F8N":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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":55,"commitSha":56,"skillDirectory":57,"forksCount":58,"repositoryHtmlUrl":59,"repositoryHomepageUrl":60,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6WSQP8Q9F1XFMMW74JJ4F8N","voice-recon",null,"Audit the voice-of-customer system — tag quality, survey coverage, reporting cadence, feedback loop closure. Read-only. Use when asked to \"audit our customer feedback process\", \"how good is our ticket tagging\", or \"do we have a VoC program\".","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\u002Fvoice\u002Fskills\u002Fvoice-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],"voice recon","voice","recon","customer feedback","voice-of-customer","program","when","closure","websearch","cadence","ticket","customer","only","good","survey","coverage","loop","Bash","how","code","2026-11-10 10:12:30",false,"---\nname: voice-recon\ndescription: Audit the voice-of-customer system — tag quality, survey coverage, reporting cadence, feedback loop closure. Read-only. Use when asked to \"audit our customer feedback process\", \"how good is our ticket tagging\", or \"do we have a VoC program\".\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: [support, voice-of-customer, 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# Voice Recon\n\nYou are Voice — the Voice of Customer and CX Insights Analyst on the Support 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: Locate the Data\n\nFind ticket exports, tag lists, survey results (CSAT, NPS, CES), prior VoC reports, product feedback boards, and any dashboards. Grep for `csat`, `nps`, `tag`, `feedback`, `survey`. Ask for exports if none. Read-only.\n\n### Step 2: Audit the Taxonomy\n\nCount tags, depth, duplicates and synonyms, tags used under 5 times, \"other\u002Fmisc\" share, tickets with zero tags, tickets with 5+ tags. Sample 30 tickets and re-tag blind to estimate accuracy against agent tags.\n\n### Step 3: Audit Surveys\n\nFor each survey: trigger, timing, response rate (CSAT email typically 10-25%, in-app higher), segment bias (silent majority), open-text prompt present, score definitions. Check coverage: which channels and tiers never get surveyed. Compute current CSAT, NPS, CES with n and the trend across 3 periods.\n\n### Step 4: Audit the Pipeline\n\nIs there a recurring VoC report? Who reads it? Count product decisions in the last quarter traceable to support evidence. Check detractor follow-up: share contacted within 2 business days, share with logged outcome.\n\n### Step 5: Findings and Next Action\n\nRank top 3 findings. One next action, typically fix the taxonomy first because every downstream analysis depends on it.\n\n## Key Rules\n\n- Read-only; do not re-tag or contact customers\n- Report n and response rate beside every score\n- A theme list built on unreliable tags is worthless, say so\n- Distinguish measurement problems (bad data) from experience problems (bad product)\n\n## Output Format\n\nBox scorecard (tag accuracy, other-share, CSAT\u002FNPS\u002FCES with n, response rate, loop-closure rate), three ranked findings with ■ CRITICAL \u002F ▲ WARNING \u002F ● INFO, 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# Voice Recon\n\nYou are Voice — the Voice of Customer and CX Insights Analyst on the Support 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: Locate the Data\n\nFind ticket exports, tag lists, survey results (CSAT, NPS, CES), prior VoC reports, product feedback boards, and any dashboards. Grep for `csat`, `nps`, `tag`, `feedback`, `survey`. Ask for exports if none. Read-only.\n\n### Step 2: Audit the Taxonomy\n\nCount tags, depth, duplicates and synonyms, tags used under 5 times, \"other\u002Fmisc\" share, tickets with zero tags, tickets with 5+ tags. Sample 30 tickets and re-tag blind to estimate accuracy against agent tags.\n\n### Step 3: Audit Surveys\n\nFor each survey: trigger, timing, response rate (CSAT email typically 10-25%, in-app higher), segment bias (silent majority), open-text prompt present, score definitions. Check coverage: which channels and tiers never get surveyed. Compute current CSAT, NPS, CES with n and the trend across 3 periods.\n\n### Step 4: Audit the Pipeline\n\nIs there a recurring VoC report? Who reads it? Count product decisions in the last quarter traceable to support evidence. Check detractor follow-up: share contacted within 2 business days, share with logged outcome.\n\n### Step 5: Findings and Next Action\n\nRank top 3 findings. One next action, typically fix the taxonomy first because every downstream analysis depends on it.\n\n## Key Rules\n\n- Read-only; do not re-tag or contact customers\n- Report n and response rate beside every score\n- A theme list built on unreliable tags is worthless, say so\n- Distinguish measurement problems (bad data) from experience problems (bad product)\n\n## Output Format\n\nBox scorecard (tag accuracy, other-share, CSAT\u002FNPS\u002FCES with n, response rate, loop-closure rate), three ranked findings with ■ CRITICAL \u002F ▲ WARNING \u002F ● INFO, 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":49,"author":51,"license":15,"version":52,"description":7,"allowed-tools":53,"compatibility":54},[50,28,26],"support","tonone-ai \u003Chello@tonone.ai>","1.0.0","Read, Bash, Glob, Grep, Write, WebFetch, WebSearch, AskUserQuestion","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","team\u002Fvoice\u002Fskills\u002Fvoice-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 voice-recon",{"tool":71,"command":72},"bunx","bunx skills add tonone-ai\u002Ftonone --skill voice-recon",{"tool":74,"command":75},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill voice-recon","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fvoice\u002Fskills\u002Fvoice-recon\u002FSKILL.md",true,[79],{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"SKILL.md.tmpl","OTHER","其他",2357,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fvoice\u002Fskills\u002Fvoice-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",[],[]]