[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6WSQYXMZ3KDRNKFD9HXNH4F":3,"skill-same:01M6WSQYXMZ3KDRNKFD9HXNH4F":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":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":62,"ownerHtmlUrl":63,"ownerBlogUrl":64,"ownerDescription":65,"updatedAt":66,"install":67,"resources":80},"01M6WSQYXMZ3KDRNKFD9HXNH4F","voice-report",null,"Produce the voice-of-customer report — CSAT\u002FNPS\u002FCES drivers, ranked themes, product asks with evidence. Use when asked to \"write the VoC report\", \"what are customers complaining about\", or \"summarize support feedback for product\".","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-report\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},"01JBSEEDCAT000000000000034","行政与办公人员",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"voice report","report","voice","feedback","voice-of-customer","when","for","websearch","themes","evidence","write","read","customer","Bash","reporting","produce","product","code","hello","support","2026-11-10 10:12:30",false,"---\nname: voice-report\ndescription: Produce the voice-of-customer report — CSAT\u002FNPS\u002FCES drivers, ranked themes, product asks with evidence. Use when asked to \"write the VoC report\", \"what are customers complaining about\", or \"summarize support feedback for product\".\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, reporting]\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 Report\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: Define Period and Data\n\nDefault: last 30 days vs prior 30 and same period last quarter. Gather tickets, CSAT\u002FNPS\u002FCES responses, churn and cancellation reasons, and community or review feedback. Record n per source.\n\n### Step 2: Score Movement and Drivers\n\nReport each score with n, response rate, and delta. Find drivers: compare CSAT\u002FNPS by tag, product area, plan, tenure, channel, and first-response time bucket. Name the 2-3 segments that explain most of the movement. Run a keyword\u002Ftheme pass on open-text of detractors vs promoters.\n\n### Step 3: Rank Themes\n\nFor each candidate theme compute: ticket count and trend, accounts affected, ARR exposure, average effort (replies per ticket, reopen rate), and detractor share. Impact = tickets x average ticket cost + ARR at risk. Keep the top 5. Apply the escalation threshold: 20+ tickets in 30 days, 3+ accounts above $50k ARR, or any data\u002Fsecurity impact.\n\n### Step 4: Write Each Theme as a Product Ask\n\nFormat: Problem (one sentence), Evidence (counts, trend, 3 verbatims with account tier, no PII), Cost (tickets\u002Fmonth, hours, ARR), Root cause class (defect, UX, missing capability, docs), Ask (specific decision), Owner (Helm for backlog, Crest for strategic, Echo for research). Note what is already known or in flight.\n\n### Step 5: Close-the-Loop Section\n\nReport detractor follow-up rate, themes fixed since last report with before\u002Fafter ticket volume, and which asks were declined (with reason). End with decisions requested and dates.\n\n## Key Rules\n\n- Max 5 themes; a longer list is a dump\n- No metric without n; under 30 responses mark directional\n- Verbatims are representative, not extreme; label the selection method\n- Separate correlation from cause; flag untested drivers as hypotheses\n- Previous asks get status; never present repeat themes as new\n\n## Output Format\n\nOne-page summary (scores, top 5 themes ranked with impact, decisions requested) plus full report with evidence appendix.\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 Report\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: Define Period and Data\n\nDefault: last 30 days vs prior 30 and same period last quarter. Gather tickets, CSAT\u002FNPS\u002FCES responses, churn and cancellation reasons, and community or review feedback. Record n per source.\n\n### Step 2: Score Movement and Drivers\n\nReport each score with n, response rate, and delta. Find drivers: compare CSAT\u002FNPS by tag, product area, plan, tenure, channel, and first-response time bucket. Name the 2-3 segments that explain most of the movement. Run a keyword\u002Ftheme pass on open-text of detractors vs promoters.\n\n### Step 3: Rank Themes\n\nFor each candidate theme compute: ticket count and trend, accounts affected, ARR exposure, average effort (replies per ticket, reopen rate), and detractor share. Impact = tickets x average ticket cost + ARR at risk. Keep the top 5. Apply the escalation threshold: 20+ tickets in 30 days, 3+ accounts above $50k ARR, or any data\u002Fsecurity impact.\n\n### Step 4: Write Each Theme as a Product Ask\n\nFormat: Problem (one sentence), Evidence (counts, trend, 3 verbatims with account tier, no PII), Cost (tickets\u002Fmonth, hours, ARR), Root cause class (defect, UX, missing capability, docs), Ask (specific decision), Owner (Helm for backlog, Crest for strategic, Echo for research). Note what is already known or in flight.\n\n### Step 5: Close-the-Loop Section\n\nReport detractor follow-up rate, themes fixed since last report with before\u002Fafter ticket volume, and which asks were declined (with reason). End with decisions requested and dates.\n\n## Key Rules\n\n- Max 5 themes; a longer list is a dump\n- No metric without n; under 30 responses mark directional\n- Verbatims are representative, not extreme; label the selection method\n- Separate correlation from cause; flag untested drivers as hypotheses\n- Previous asks get status; never present repeat themes as new\n\n## Output Format\n\nOne-page summary (scores, top 5 themes ranked with impact, decisions requested) plus full report with evidence appendix.\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":52,"author":53,"license":15,"version":54,"description":7,"allowed-tools":55,"compatibility":56},[46,31,41],"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-report",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":68,"prompt":78,"zipAvailable":79},[69,72,75],{"tool":70,"command":71},"npx","npx skills add tonone-ai\u002Ftonone --skill voice-report",{"tool":73,"command":74},"bunx","bunx skills add tonone-ai\u002Ftonone --skill voice-report",{"tool":76,"command":77},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill voice-report","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fvoice\u002Fskills\u002Fvoice-report\u002FSKILL.md",true,[81],{"path":82,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":85,"sourceHtmlUrl":86},"SKILL.md.tmpl","OTHER","其他",2634,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fvoice\u002Fskills\u002Fvoice-report\u002FSKILL.md.tmpl",[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",[],[]]