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 chargeback-management-preventiongit 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/chargeback-management-prevention)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/chargeback-management-prevention"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/chargeback-management-prevention/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/chargeback-management-prevention"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/chargeback-management-prevention.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 | $0.00034 | $0.02248 |
| Opus 5 | $0.00017 | $0.01124 |
| Sonnet 5 | $0.00007 | $0.00450 |
| Haiku 4.5 | $0.00003 | $0.00225 |
Grade A, and why
chargeback-management-prevention 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chargeback Management and Prevention
Overview
A chargeback occurs when a cardholder disputes a transaction with their bank, forcing a reversal of funds and levying a fee ($15–$100 per dispute) on the merchant. A chargeback ratio above 1% (Visa) or 1.5% (Mastercard) triggers the card network's dispute monitoring programs, which can result in monthly fines and ultimately account termination.
Effective chargeback management has two tracks: (1) preventing disputes with fraud scoring and clear communication, and (2) winning more disputes by submitting complete evidence within the response window. Most platforms now integrate directly with Stripe or PayPal for dispute management, making automated evidence submission accessible to all merchants.
When to Use This Skill
- When chargeback ratio is approaching 0.65% (the early-warning level Visa monitors before the 1% threshold)
- When your team is manually compiling evidence packages and missing response deadlines
- When processing international transactions with higher dispute rates
- When your dispute win rate is below 40% and you need to understand why
- When friendly fraud (customers who received goods but dispute anyway) is a significant problem
Core Instructions
Step 1: Determine your platform and dispute management approach
| Platform | How Disputes Are Handled | Recommended Tool |
|---|---|---|
| Shopify Payments | Disputes managed in Shopify Admin → Payments → Disputes | Shopify's built-in dispute response + Chargebacks911 or Kount for high volume |
| Shopify + Stripe | Disputes appear in Stripe Dashboard + Shopify Admin | Stripe Radar for prevention; Stripe's dispute workflow for response |
| WooCommerce + Stripe | Disputes in Stripe Dashboard; no WooCommerce-native interface | Stripe Radar for fraud scoring; Stripe Dashboard for dispute response |
| WooCommerce + PayPal | Disputes in PayPal Resolution Center | PayPal Seller Protection + manual evidence submission in Resolution Center |
| BigCommerce | Depends on payment gateway; Stripe and PayPal most common | Same as WooCommerce equivalent above |
| Custom / Headless | Stripe Radar + Stripe dispute webhooks for automation | Build automated evidence collection triggered by charge.dispute.created webhook |
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/dispute-data-model-and-webhook-ingestion/criteria.json 3.1 KB
- evals/dispute-data-model-and-webhook-ingestion/task.md 1.9 KB
- evals/evidence-scoring-ce-3-0-and-auto-submiss/criteria.json 2.8 KB
- evals/evidence-scoring-ce-3-0-and-auto-submiss/task.md 2.4 KB
- evals/ratio-monitoring-alerting-and-prevention/criteria.json 3.1 KB
- evals/ratio-monitoring-alerting-and-prevention/task.md 2.5 KB
- tile.json 331 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 · 156 lines · 34 tokens per session scan A 463bbfd7b1d5
chargeback-management-prevention is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 34 tokens to every session and 2,248 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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