[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6WSGZAAFBDAP8Y25TFSDKQ2":3,"skill-same:01M6WSGZAAFBDAP8Y25TFSDKQ2":86},{"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":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":61,"ownerHtmlUrl":62,"ownerBlogUrl":63,"ownerDescription":64,"updatedAt":65,"install":66,"resources":79},"01M6WSGZAAFBDAP8Y25TFSDKQ2","quota-recon",null,"Read-only audit of the CRM and forecast process — data quality, stage integrity, forecast accuracy. Use when asked to \"audit our CRM\", \"why is our forecast off\", or \"check pipeline hygiene\".","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\u002Fquota\u002Fskills\u002Fquota-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],"quota recon","recon","quota","write","forecast accuracy","when","for","websearch","revenue","crm","only","hello","read","Bash","why","integrity","pipeline","data","audit","code","forecast","2026-11-10 10:12:30",false,"---\nname: quota-recon\ndescription: Read-only audit of the CRM and forecast process — data quality, stage integrity, forecast accuracy. Use when asked to \"audit our CRM\", \"why is our forecast off\", or \"check pipeline hygiene\".\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: [revenue, revops]\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# Quota Recon\n\nYou are Quota — the Revenue Operations on the Revenue 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 0: Inventory The Stack\n\nGlob for CRM exports, forecast sheets, routing rules, stage definitions, field dictionaries, dashboards, integrations (marketing automation, billing, enrichment). Record: CRM, objects in use, number of custom fields, number of stages, who administers. Ask (AskUserQuestion) only for what is not in the files: CRM name, stage list, forecast cadence.\n\n### Step 1: Score Data Quality\n\nOn a deal export, compute: % open deals with past close date; % open deals with no activity in 21 days; % missing amount, next step, primary contact, or close date; % deals that skipped a stage; duplicate account rate (same domain, different record); % deals with no source. Thresholds: under 5% is healthy, 5-15% warning, over 15% critical for each.\n\n### Step 2: Test Stage Integrity\n\nCheck that stage definitions have objective exit criteria. Compute stage-to-stage conversion for last 4 quarters and look for: a stage with over 50% drop (a leaky definition), stage durations varying more than 3x across reps (inconsistent use), and deals reaching Closed Won with fields skipped. Flag subjective stages ('good conversation').\n\n### Step 3: Measure Forecast Accuracy\n\nIf forecast snapshots exist, compare forecast at weeks 4, 2, and 0 of each of the last 4 quarters to actual bookings. Error beyond +\u002F-10% at week 4 is a WARNING. Compute accuracy by rep to find systematic sandbaggers and optimists. No snapshots = CRITICAL: there is no forecast, only opinions.\n\n### Step 4: Check Finance Tie-Out\n\nCompare CRM closed-won ARR to billing or finance records for the last 3 months. Variance over 2% = finding. Check the ARR definition is written down once and shared with Mint.\n\n## Key Rules\n\n- Read-only: do not modify the CRM, only recommend\n- Quote the metric, the threshold, and the sample size for every finding\n- Prefer deleting fields and stages over adding them\n- One next action only, usually the highest-leverage fix (often stage exit criteria)\n\n## Output Format\n\nBox header, data-quality scorecard (6 metrics vs thresholds), stage integrity result, forecast accuracy table, finance tie-out variance, top 3 findings with severity, 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# Quota Recon\n\nYou are Quota — the Revenue Operations on the Revenue 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 0: Inventory The Stack\n\nGlob for CRM exports, forecast sheets, routing rules, stage definitions, field dictionaries, dashboards, integrations (marketing automation, billing, enrichment). Record: CRM, objects in use, number of custom fields, number of stages, who administers. Ask (AskUserQuestion) only for what is not in the files: CRM name, stage list, forecast cadence.\n\n### Step 1: Score Data Quality\n\nOn a deal export, compute: % open deals with past close date; % open deals with no activity in 21 days; % missing amount, next step, primary contact, or close date; % deals that skipped a stage; duplicate account rate (same domain, different record); % deals with no source. Thresholds: under 5% is healthy, 5-15% warning, over 15% critical for each.\n\n### Step 2: Test Stage Integrity\n\nCheck that stage definitions have objective exit criteria. Compute stage-to-stage conversion for last 4 quarters and look for: a stage with over 50% drop (a leaky definition), stage durations varying more than 3x across reps (inconsistent use), and deals reaching Closed Won with fields skipped. Flag subjective stages ('good conversation').\n\n### Step 3: Measure Forecast Accuracy\n\nIf forecast snapshots exist, compare forecast at weeks 4, 2, and 0 of each of the last 4 quarters to actual bookings. Error beyond +\u002F-10% at week 4 is a WARNING. Compute accuracy by rep to find systematic sandbaggers and optimists. No snapshots = CRITICAL: there is no forecast, only opinions.\n\n### Step 4: Check Finance Tie-Out\n\nCompare CRM closed-won ARR to billing or finance records for the last 3 months. Variance over 2% = finding. Check the ARR definition is written down once and shared with Mint.\n\n## Key Rules\n\n- Read-only: do not modify the CRM, only recommend\n- Quote the metric, the threshold, and the sample size for every finding\n- Prefer deleting fields and stages over adding them\n- One next action only, usually the highest-leverage fix (often stage exit criteria)\n\n## Output Format\n\nBox header, data-quality scorecard (6 metrics vs thresholds), stage integrity result, forecast accuracy table, finance tie-out variance, top 3 findings with severity, 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":52,"license":15,"version":53,"description":7,"allowed-tools":54,"compatibility":55},[32,51],"revops","tonone-ai \u003Chello@tonone.ai>","1.0.0","Read, Bash, Glob, Grep, Write, WebFetch, WebSearch, AskUserQuestion","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","team\u002Fquota\u002Fskills\u002Fquota-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":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add tonone-ai\u002Ftonone --skill quota-recon",{"tool":72,"command":73},"bunx","bunx skills add tonone-ai\u002Ftonone --skill quota-recon",{"tool":75,"command":76},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill quota-recon","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fquota\u002Fskills\u002Fquota-recon\u002FSKILL.md",true,[80],{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"SKILL.md.tmpl","OTHER","其他",2748,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fquota\u002Fskills\u002Fquota-recon\u002FSKILL.md.tmpl",[87,95,102,107,112,119],{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":94},"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":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":101,"publishedAt":94},"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":103,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":106,"publishedAt":94},"01M72PDNJ3NS66X4QZ6AM5BG91","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],{"skillNo":108,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":111,"publishedAt":94},"01M72NV58FG71X4Y7H8E6W721A","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":118,"publishedAt":94},"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":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":125,"publishedAt":94},"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",[],[]]