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afrexai-accounts-receivableafrexai 应收账款

Agent Skill

afrexai-accounts-receivable 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

19,020

周安装

762

GitHub Stars

公开资料未说明

下载量

6,157
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:afrexai-accounts-receivable(afrexai 应收账款)
来源仓库:https://github.com/1kalin/afrexai-accounts-receivable
安装命令:
openclaw skills install afrexai-accounts-receivable
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install afrexai-accounts-receivable

简介

自动化应收账款:帐龄报告、确定收款优先顺序、草稿付款提醒、匹配付款、跟踪 DSO 和预测坏账风险。

SKILL.md

Accounts Receivable Manager

Automate AR workflows: aging analysis, collection prioritization, payment follow-ups, cash application, and bad debt forecasting.

What It Does

  1. AR Aging Report — Bucket outstanding invoices by 0-30, 31-60, 61-90, 90+ days with risk scoring
  2. Collection Priority Queue — Rank overdue accounts by amount × days × risk for optimal follow-up order
  3. Payment Reminder Drafts — Generate professional escalation emails (friendly → firm → final notice → collections)
  4. Cash Application Matching — Match incoming payments to open invoices with variance handling
  5. Bad Debt Forecasting — Predict write-offs using historical payment patterns and aging trends
  6. DSO Tracking — Calculate Days Sales Outstanding with trend analysis and benchmarks by industry

How to Use

Tell your agent what you need:

  • "Run an AR aging analysis for our open invoices"
  • "Prioritize our collection queue — what should we chase first?"
  • "Draft a 60-day overdue reminder for [client name]"
  • "Our DSO is 47 days — how does that compare to SaaS benchmarks?"
  • "Forecast bad debt exposure for Q1"

AR Aging Buckets

BucketRisk LevelAction
Current (0-30)LowMonitor
31-60 daysMediumFriendly reminder
61-90 daysHighEscalation call + written notice
90+ daysCriticalFinal demand → collections/write-off review

Collection Priority Formula

Priority Score = (Invoice Amount × 0.4) + (Days Overdue × 0.3) + (Customer Risk Score × 0.3)

Customer Risk Score (1-10) based on:

  • Payment history (avg days to pay)
  • Number of past-due invoices
  • Credit limit utilization
  • Industry default rates

Payment Reminder Escalation

Day 1 (Invoice Due)

Subject: Invoice #[NUM] — Payment Due Today Tone: Friendly, informational

Day 7 (1 Week Overdue)

Subject: Friendly Reminder — Invoice #[NUM] Past Due Tone: Warm but clear

Day 30 (1 Month Overdue)

Subject: Payment Required — Invoice #[NUM] Now 30 Days Past Due Tone: Professional, firm

Day 60 (2 Months Overdue)

Subject: Urgent — Invoice #[NUM] Significantly Overdue Tone: Serious, mention late fees / service impact

Day 90+ (Final Notice)

Subject: Final Notice — Invoice #[NUM] Requires Immediate Payment Tone: Formal, mention collections referral

DSO Benchmarks by Industry

IndustryGood DSOAverage DSOPoor DSO
SaaS / Software<3030-45>60
Professional Services<3535-55>70
Manufacturing<4040-60>75
Construction<4545-70>90
Healthcare<3535-50>65

Bad Debt Forecasting Model

Estimate write-off probability by aging bucket:

  • Current: 1-2% default rate
  • 31-60 days: 5-8%
  • 61-90 days: 15-25%
  • 90-120 days: 30-50%
  • 120+ days: 50-80%

Apply to outstanding amounts for expected loss provision.

Cash Application Rules

  1. Exact match — Payment amount matches one open invoice exactly
  2. Combination match — Payment matches sum of multiple invoices
  3. Short payment — Payment < invoice amount → flag for dispute/deduction review
  4. Overpayment — Payment > invoice → apply to oldest open balance or issue credit
  5. Unidentified — No match found → hold in suspense, research within 48 hours

Output Format

When generating AR reports, include:

  • Total AR outstanding
  • Aging distribution ($ and %)
  • Top 10 overdue accounts by priority score
  • DSO current vs. 3-month trend
  • Estimated bad debt exposure
  • Recommended actions (who to call, what to send)

Take It Further

This skill handles AR analysis and workflows. For full financial operations automation:

Built by AfrexAI — operational AI for businesses that run on results, not hype.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

71.37%
按下载量换算4,394

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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