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 finsilabs/awesome-ecommerce-skills --skill accounts-receivable-automationgit clone --depth 1 https://github.com/finsilabs/awesome-ecommerce-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/finsilabs/awesome-ecommerce-skills/accounts-receivable-automation)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/accounts-receivable-automation"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/accounts-receivable-automation/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/finsilabs/awesome-ecommerce-skills/accounts-receivable-automation"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/accounts-receivable-automation.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 | $0.00035 | $0.02402 |
| Opus 5 | $0.00017 | $0.01201 |
| Sonnet 5 | $0.00007 | $0.00480 |
| Haiku 4.5 | $0.00003 | $0.00240 |
Grade A, and why
accounts-receivable-automation 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 9d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Accounts Receivable Automation
Overview
Accounts receivable (AR) automation converts manual invoice follow-up — sending reminders, tracking payment status, escalating overdue accounts — into a system-driven workflow. In B2B ecommerce, where customers pay on net-30, net-60, or net-90 terms rather than at checkout, AR management directly impacts cash flow and days sales outstanding (DSO).
A well-configured AR system reduces DSO by 5–15 days by ensuring follow-up is timely and persistent, eliminates invoices falling through the cracks, and gives the finance team real-time visibility into what is owed and how overdue each invoice is.
When to Use This Skill
- When your B2B customers pay on credit terms (net-30, net-60, net-90) rather than at checkout
- When your finance team spends more than a few hours per week chasing past-due invoices
- When you have more than 50 active B2B accounts and manual tracking is breaking down
- When you need to enforce credit limits and flag accounts that have exceeded them
- When DSO is higher than industry benchmarks and you need to identify the root cause
- When building a wholesale or distribution ecommerce platform with trade accounts
- When you need audit-ready AR records for lenders or investors
Core Instructions
Step 1: Determine your platform and choose the right AR tool
| Platform | Recommended Tool | Why |
|---|---|---|
| Shopify | Invoiced.com or Apruve (B2B app) + QuickBooks Online | Shopify handles orders; a dedicated AR tool handles net-terms invoicing, dunning, and aging outside Shopify's standard checkout flow |
| Shopify Plus | Shopify B2B (built-in) + Invoiced or NetSuite | Shopify Plus has native B2B payment terms, company accounts, and order approval workflows; pair with Invoiced for advanced dunning |
| WooCommerce | WooCommerce B2B plugin + WooCommerce PDF Invoices | WooCommerce B2B enables net terms; WooCommerce Payments or Stripe handles payments; FreshBooks/QuickBooks sync handles AR aging |
| BigCommerce | BigCommerce B2B Edition + Apruve or NetSuite | BigCommerce B2B Edition supports company accounts, payment terms, and quotes natively |
| Custom / Headless | Stripe Invoicing API or build with Stripe + accounting system webhook | Stripe Invoicing handles invoice creation, dunning, and payment links; pair with QuickBooks or Xero for AR aging |
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/ar-database-schema-design/criteria.json 2.8 KB
- evals/ar-database-schema-design/task.md 1.4 KB
- evals/dunning-engine-implementation/criteria.json 2.8 KB
- evals/dunning-engine-implementation/task.md 1.7 KB
- evals/payment-recording-and-credit-management/criteria.json 2.9 KB
- evals/payment-recording-and-credit-management/task.md 1.7 KB
- tile.json 328 B
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.
- 9d ago First seen · 173 lines · 35 tokens per session scan A be631e72de7b
accounts-receivable-automation is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 35 tokens to every session and 2,402 once invoked, about $0.0002 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 2026-09-03.
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