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 checkout-flow-optimizationgit 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/checkout-flow-optimization)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/checkout-flow-optimization"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/checkout-flow-optimization/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/checkout-flow-optimization"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/checkout-flow-optimization.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 | $0.00028 | $0.02371 |
| Opus 5 | $0.00014 | $0.01185 |
| Sonnet 5 | $0.00006 | $0.00474 |
| Haiku 4.5 | $0.00003 | $0.00237 |
Grade A, and why
checkout-flow-optimization 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 8d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Checkout Flow Optimization
Overview
Checkout abandonment averages 70% across ecommerce. The biggest friction points — too many form fields, no guest checkout, hidden fees revealed late, and no express payment options — are all fixable through platform settings and apps without custom code. Best-in-class stores achieve 50–60% checkout completion by applying a handful of high-impact changes.
When to Use This Skill
- When checkout abandonment rate exceeds 70% and you need to diagnose the cause
- When redesigning checkout as part of a storefront rebuild
- When integrating express checkout (Apple Pay, Google Pay, PayPal Express) into an existing flow
- When A/B testing checkout layout changes
Core Instructions
Step 1: Determine your platform and the available optimization levers
| Platform | Checkout Control Level | Best Optimization Approach |
|---|---|---|
| Shopify | Limited (Shopify controls the core flow) | Use Checkout Extensibility apps + Settings to configure; no custom HTML/CSS without Plus |
| Shopify Plus | Full control via Checkout Extensibility | Use checkout.liquid customizations + Shopify Functions + checkout extension apps |
| WooCommerce | Full control | Configure settings + use checkout optimization plugins |
| BigCommerce | Moderate control via Stencil theme | Theme customization + One Page Checkout configuration |
| Custom / Headless | Full control | Build optimized flow using Stripe Elements or platform Storefront API |
Step 2: Apply the highest-impact checkout optimizations
Shopify
Enable one-page checkout (Shopify's default as of 2023):
- Go to Settings → Checkout
- Under Checkout layout, select One-page checkout — this combines contact, shipping, and payment on a single page instead of 3 steps
- If you are on an older theme, update to Dawn or another OS 2.0 theme that supports one-page checkout natively
Enable express checkout buttons:
- Go to Settings → Payments
- Under Wallets, enable Shop Pay, Apple Pay, Google Pay, and Meta Pay
- Shop Pay has the highest conversion rate of any express payment method on Shopify — enable it first
- Go to Online Store → Themes → Customize and add express checkout buttons to your cart page and product pages
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/collapsible-checkout-steps-and-sticky-or/criteria.json 2.9 KB
- evals/collapsible-checkout-steps-and-sticky-or/task.md 1.8 KB
- evals/express-checkout-button-placement-and-av/criteria.json 2.3 KB
- evals/express-checkout-button-placement-and-av/task.md 1.6 KB
- evals/form-validation-timing-and-state-preserv/criteria.json 2.8 KB
- evals/form-validation-timing-and-state-preserv/task.md 1.6 KB
- tile.json 246 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.
- 8d ago First seen · 200 lines · 28 tokens per session scan A aff8b7076547
checkout-flow-optimization is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 28 tokens to every session and 2,371 once invoked, about $0.0001 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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