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 payment-reconciliation-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/payment-reconciliation-automation)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/payment-reconciliation-automation"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/payment-reconciliation-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/payment-reconciliation-automation"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/payment-reconciliation-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 | $0.00031 | $0.02496 |
| Opus 5 | $0.00015 | $0.01248 |
| Sonnet 5 | $0.00006 | $0.00499 |
| Haiku 4.5 | $0.00003 | $0.00250 |
Grade A, and why
payment-reconciliation-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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Payment Reconciliation Automation
Overview
Payment reconciliation matches what your payment processors (Stripe, PayPal, Shopify Payments) say they collected against what your accounting system recorded and what your bank actually received. Discrepancies arise from processor fees, refunds, chargebacks, rolling reserves, and currency conversion — none of which are automatically journaled in most ecommerce setups. Manual reconciliation does not scale beyond a few hundred transactions per day.
For most merchants, automated reconciliation is solved by connecting your ecommerce platform to your accounting system (QuickBooks, Xero) via a dedicated sync tool rather than building custom matching logic.
When to Use This Skill
- When your finance team spends more than two hours per day on manual payment reconciliation
- When processing transactions across two or more payment processors (e.g., Stripe + PayPal)
- When month-end close is blocked by unresolved payment discrepancies
- When chargebacks or refunds are not being reliably reflected in your accounting system
- When you need SOC 2 or PCI-DSS audit documentation for payment flows
Core Instructions
Step 1: Determine your platform and choose the reconciliation approach
| Platform | Recommended Reconciliation Tool | Notes |
|---|---|---|
| Shopify Payments | A2X or Bench Accounting | A2X maps Shopify payouts to QuickBooks/Xero journal entries automatically, handling fees, refunds, and adjustments |
| Shopify + Stripe | A2X for Stripe + A2X for Shopify | Connect both sources to QuickBooks/Xero; A2X reconciles each payout separately |
| WooCommerce + Stripe | Synder or WooCommerce QuickBooks Online plugin | Synder syncs every Stripe transaction to QuickBooks with fees separated |
| WooCommerce + PayPal | Synder or PayPal for WooCommerce + QuickBooks | Synder handles both Stripe and PayPal in one connection |
| BigCommerce | A2X (has BigCommerce connector) or Synder | Same approach as Shopify |
| Custom / Headless | Build reconciliation pipeline using Stripe Balance Transactions API | See Custom / Headless section below |
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/database-schema-and-alerting/criteria.json 3.0 KB
- evals/database-schema-and-alerting/task.md 1.6 KB
- evals/matching-engine-with-tolerances/criteria.json 2.4 KB
- evals/matching-engine-with-tolerances/task.md 1.6 KB
- evals/transaction-ingestion-pipeline/criteria.json 2.8 KB
- evals/transaction-ingestion-pipeline/task.md 1.7 KB
- tile.json 336 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 · 202 lines · 31 tokens per session scan A 7f50d6edb706
payment-reconciliation-automation is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 31 tokens to every session and 2,496 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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