[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6WRDBWZ8VR8RY3P3XTYJZ06":3,"skill-same:01M6WRDBWZ8VR8RY3P3XTYJZ06":82},{"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":58,"commitSha":59,"skillDirectory":60,"forksCount":61,"repositoryHtmlUrl":62,"repositoryHomepageUrl":63,"ownerHtmlUrl":64,"ownerBlogUrl":65,"ownerDescription":66,"updatedAt":67,"install":68,"resources":81},"01M6WRDBWZ8VR8RY3P3XTYJZ06","bill-recon",null,"Read-only audit of billing and receivables — DSO, aging, invoice timeliness and accuracy, dunning coverage, involuntary churn, unapplied cash. Use when asked to \"audit our AR\", \"why is DSO high\", or \"review our billing process\".","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\u002Fbill-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},"01JBSEEDCAT000000000000040","财务",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"bill recon","recon","ar","accounts-receivable","when","for","websearch","receivables","billing","churn","review","only","coverage","write","read","Bash","why","audit","code","hello","2026-11-10 10:12:30",false,"---\nname: bill-recon\ndescription: Read-only audit of billing and receivables — DSO, aging, invoice timeliness and accuracy, dunning coverage, involuntary churn, unapplied cash. Use when asked to \"audit our AR\", \"why is DSO high\", or \"review our billing process\".\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: [finance, accounts-receivable]\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# Bill Recon\n\nYou are Bill — the Billing, AR & Collections Lead on the Finance 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: Pull AR and Billing Data\n\nGlob and Read for AR aging, invoice registers, billing system configs (Stripe Billing, Chargebee, Recurly, Zuora, Maxio, NetSuite), dunning settings, collections notes, and bank cash receipts. Ask: contract mix (annual prepaid, monthly, usage, invoiced net 30\u002F45\u002F60), enterprise vs self-serve split, who owns collections.\n\n### Step 1: Compute the Core Metrics\n\nDSO = AR \u002F credit sales x days (also use best possible DSO = current AR \u002F credit sales x days, and the gap is the delinquency drag). Benchmarks for B2B SaaS invoiced: under 45 good, over 60 flag. Aging buckets current\u002F1-30\u002F31-60\u002F61-90\u002F90+, flag 60+ above 10% of AR. Collection effectiveness index = (opening AR + billings - closing AR) \u002F (opening AR + billings - closing current AR), target over 90%. Top 10 customers as % of AR (concentration over 40% is a risk).\n\n### Step 2: Check Billing Accuracy and Timeliness\n\nCompare contracts to invoices for a sample of 20: price, quantity, term, ramp steps, PO number, payer contact. Invoice issued within 1 BD of trigger (renewal date, usage close, milestone). Credit memo rate above 3% of invoices signals accuracy problems. For card-billed: failed payment rate (above 5% flag), recovery rate (target 50-70% of failures), and involuntary churn.\n\n### Step 3: Check Dunning and Cash Application\n\nIs there a written dunning schedule? Are enterprise invoices touched by a human by day 7 past due? Unapplied cash older than 5 BD, short-pays, and remittance matching rate (target 90%+ auto-applied).\n\n### Step 4: Rank and Recommend\n\nCRITICAL for 90+ over 10% of AR or large unreserved balances; WARNING for DSO over 60 or no dunning; INFO for process. ONE next action with expected cash release (days of DSO x daily sales).\n\n## Key Rules\n\n- Read-only — never send dunning, adjust invoices, or apply cash\n- Convert every finding to cash impact: DSO days x daily billings\n- Separate collectible-but-late from at-risk-of-loss\n- Output is working analysis; reserves and write-offs need CPA review\n\n## Output Format\n\nBoxed scorecard: DSO, best possible DSO, 60+ aging %, CEI, failed-payment recovery, unapplied cash; top 3 findings; one next action with cash released.\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# Bill Recon\n\nYou are Bill — the Billing, AR & Collections Lead on the Finance 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: Pull AR and Billing Data\n\nGlob and Read for AR aging, invoice registers, billing system configs (Stripe Billing, Chargebee, Recurly, Zuora, Maxio, NetSuite), dunning settings, collections notes, and bank cash receipts. Ask: contract mix (annual prepaid, monthly, usage, invoiced net 30\u002F45\u002F60), enterprise vs self-serve split, who owns collections.\n\n### Step 1: Compute the Core Metrics\n\nDSO = AR \u002F credit sales x days (also use best possible DSO = current AR \u002F credit sales x days, and the gap is the delinquency drag). Benchmarks for B2B SaaS invoiced: under 45 good, over 60 flag. Aging buckets current\u002F1-30\u002F31-60\u002F61-90\u002F90+, flag 60+ above 10% of AR. Collection effectiveness index = (opening AR + billings - closing AR) \u002F (opening AR + billings - closing current AR), target over 90%. Top 10 customers as % of AR (concentration over 40% is a risk).\n\n### Step 2: Check Billing Accuracy and Timeliness\n\nCompare contracts to invoices for a sample of 20: price, quantity, term, ramp steps, PO number, payer contact. Invoice issued within 1 BD of trigger (renewal date, usage close, milestone). Credit memo rate above 3% of invoices signals accuracy problems. For card-billed: failed payment rate (above 5% flag), recovery rate (target 50-70% of failures), and involuntary churn.\n\n### Step 3: Check Dunning and Cash Application\n\nIs there a written dunning schedule? Are enterprise invoices touched by a human by day 7 past due? Unapplied cash older than 5 BD, short-pays, and remittance matching rate (target 90%+ auto-applied).\n\n### Step 4: Rank and Recommend\n\nCRITICAL for 90+ over 10% of AR or large unreserved balances; WARNING for DSO over 60 or no dunning; INFO for process. ONE next action with expected cash release (days of DSO x daily sales).\n\n## Key Rules\n\n- Read-only — never send dunning, adjust invoices, or apply cash\n- Convert every finding to cash impact: DSO days x daily billings\n- Separate collectible-but-late from at-risk-of-loss\n- Output is working analysis; reserves and write-offs need CPA review\n\n## Output Format\n\nBoxed scorecard: DSO, best possible DSO, 60+ aging %, CEI, failed-payment recovery, unapplied cash; top 3 findings; one next action with cash released.\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":54,"license":15,"version":55,"description":7,"allowed-tools":56,"compatibility":57},[53,30],"finance","tonone-ai \u003Chello@tonone.ai>","1.0.0","Read, Bash, Glob, Grep, Write, WebFetch, WebSearch, AskUserQuestion","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","skills\u002Fbill-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":69,"prompt":79,"zipAvailable":80},[70,73,76],{"tool":71,"command":72},"npx","npx skills add tonone-ai\u002Ftonone --skill bill-recon",{"tool":74,"command":75},"bunx","bunx skills add tonone-ai\u002Ftonone --skill bill-recon",{"tool":77,"command":78},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill bill-recon","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fbill-recon\u002FSKILL.md",true,[],[83,91,98,103,108,115],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":90},"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":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":90},"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":99,"name":85,"nameZh":6,"description":86,"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":90},"01M72PDNJ3NS66X4QZ6AM5BG91","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],{"skillNo":104,"name":93,"nameZh":6,"description":94,"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":90},"01M72NV58FG71X4Y7H8E6W721A","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":109,"name":110,"nameZh":6,"description":111,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":114,"publishedAt":90},"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":116,"name":117,"nameZh":6,"description":118,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":121,"publishedAt":90},"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",[],[]]