Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vivy-yi/finance-skills --skill ar-mastergit clone --depth 1 https://github.com/vivy-yi/finance-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vivy-yi/finance-skills/ar-master)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/ar-master"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/ar-master/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/ar-master"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/ar-master.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00115 | $0.01915 |
| Opus 5 | $0.00057 | $0.00958 |
| Sonnet 5 | $0.00023 | $0.00383 |
| Haiku 4.5 | $0.00012 | $0.00192 |
Grade A, and why
ar-master scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
加载上下文
首次使用时: 读取 ../../CLAUDE.md 获取场景级配置(催款政策/客户分级/坏账规则/升级矩阵)。
/ar-master — 应收账款主流程
完整 AR 周期
Step 1:账龄分析
→ 执行 aging-analysis-ar
→ 识别高风险客户和逾期清单
Step 2:催款执行
→ 执行 collection-automation
→ 按催款政策触发各阶段催款
Step 3:到账核销
→ 从 [CASH] 获取银行到账流水
→ 匹配客户/发票,核销应收
Step 4:客户信用复审
→ 对长期逾期客户执行信用复审
→ 评估是否须调整信用额度或停止合作
Step 5:坏账处理
→ 对逾期 > 180 天的应收评估坏账风险
→ 准备核销材料或启动诉讼
第一步:账龄分析
执行 Skill: aging-analysis-ar
截止日期:[YYYY-MM-DD]
分析结果:
□ 总应收款:[XXX万]
□ 已逾期:[XXX万]([X]%)
□ 逾期率较上月:[上升/下降/持平]
TOP 风险项:
□ 逾期 > 90 天的客户:[X] 家 / [XXX万]
□ 须升级处理:[X] 项
第二步:催款执行
执行 Skill: collection-automation
催款批次:[YYYYMMDD-XXX]
催款结果:
□ 阶段 1(自动提醒):[X] 家 / [XXX万] — 已发送
□ 阶段 2(人工跟进):[X] 家 / [XXX万] — 已联系 [X] 家
□ 阶段 3(正式催款):[X] 家 / [XXX万] — 催款函已发
□ 阶段 4(律师函):[X] 家 — 新订单已冻结
□ 阶段 5(诉讼/核销):[X] 家 / [XXX万] — 待评估
承诺付款跟踪:
□ 本周到期的承诺付款:[X] 笔 / [XXX万]
→ 已到账:[X] 笔 / [XXX万]
→ 未到账:[X] 笔 / [XXX万] — 已再次跟进
第三步:到账核销
从 [CASH] 获取银行到账流水:
□ 本期到账:[X] 笔 / [XXX万]
□ 待认领到账:[X] 笔 / [XXX万](无法匹配客户)
认领处理:
□ 已匹配核销:[X] 笔 / [XXX万]
□ 待客户确认:[X] 笔 / [XXX万](到账金额与应收不完全匹配)
□ 无法匹配:[X] 笔 / [XXX万] — 须跟进
无法匹配的处理:
□ 到账金额 > 应收:记入预收账款
□ 到账金额 < 应收:部分核销,剩余继续催收
□ 无法确认到账客户:联系客户确认
□ 疑似错误到账:核查是否涉及欺诈
第四步:客户信用复审
触发条件:
□ 客户逾期 > 90 天且无还款意愿
□ 客户连续 3 个月出现在 TOP 5 逾期清单
□ 客户涉及重大诉讼/经营异常
□ 客户要求变更收款账户(高风险)
□ 客户申请提升信用额度
执行 Skill: credit-assessment
复审结果:
□ [客户名称] — 信用等级调整为 [C/D]
□ [客户名称] — 信用额度调整为 [XXX万]
□ [客户名称] — 建议停止合作
第五步:坏账处理
逾期 > 180 天的应收评估:
□ 进入诉讼评估:[X] 家 / [XXX万]
→ 法务评估后可起诉:[X] 家 / [XXX万]
→ 证据不足,暂缓起诉:[X] 家 / [XXX万]
□ 准备核销:[X] 家 / [XXX万]
→ 核销审批中:[X] 家 / [XXX万]
→ 已批准核销:[X] 家 / [XXX万]
第六步:生成 AR 周报
═══════════════════════════════════════
应收账款周报
报告周期:[YYYY年MM月第X周]
截止日期:[YYYY-MM-DD]
生成时间:[YYYY-MM-DD HH:MM]
═══════════════════════════════════════
【AR 概览】
总应收款(截止日):[XXX万]
已逾期:[XXX万](逾期率 [X%])
较上周变化:[↑增加/↓减少] [X万]
本月回款目标:[XXX万]
本月实际回款:[XXX万]([X%])
【账龄分布】
0-30天:[XXX万] | 31-60天:[XXX万] | 61-90天:[XXX万] | 91-180天:[XXX万] | >180天:[XXX万]
[X%] | [X%] | [X%] | [X%] | [X%]
【本周催款执行】
本周催款客户数:[X] 家
本周催款金额:[XXX万]
本周承诺付款:[X] 笔 / [XXX万]
本周实际到账(承诺):[X] 笔 / [XXX万]
【本周回款】
本周回款总计:[XXX万]
较上周:[↑/↓] [X%]
大额回款:[客户名称] [XXX万]
【须升级事项】
□ [客户名称] — 逾期 [X] 天 / [XXX万] — [升级原因]
□ [客户名称] — 须核销评估 / 须启动诉讼
【下周工作计划】
□ 继续跟进逾期客户 [X] 家
□ 须发送正式催款函 [X] 封
□ 须评估诉讼可行性 [X] 家
□ 须完成核销审批 [X] 家 / [XXX万]
【AR 健康度指标】
指标 | 本周 | 上周 | 趋势
-----|------|------|----
逾期率 | [X%] | [X%] | [↑/↓/—]
周转天数 | [X]天 | [X]天 | [↑/↓/—]
坏账准备 | [XXX万] | [XXX万] | [↑/↓/—]
═══════════════════════════════════════
报告人:[AR专员/AR主管]
审核人:[AR主管/财务经理]
═══════════════════════════════════════
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 225 lines · 115 tokens per session scan A 4a66ccf0d5bb
ar-master is a skill published in the GitHub repository vivy-yi/finance-skills (27 stars, last pushed 2mo ago), licensed MIT. It adds 115 tokens to every session and 1,915 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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