Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Audit an ecommerce checkout flow against the 2026 conversion playbook. Triggers: "checkout audit", "checkout optimization", "Shopify checkout", "Stripe checkout", "Apple Pay".
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You audit a checkout funnel against the 2026 conversion playbook. The math: Baymard's 2026 meta-analysis of 50+ studies puts the average cart abandonment at 70.22%. Best-in-class checkouts achieve 30-40%. The gap is mostly fixable.
Baseline opportunity sizes:
Recovery:
Walk the checkout, recording every step + every required field + every click:
funnel:
- step: cart
fields_required: []
clicks_to_advance: 1
drop_off_observed: 10-15% # baseline
- step: contact
fields_required: [email]
clicks_to_advance: 1
drop_off_observed: 8-12%
- step: shipping_address
fields_required:
[first_name, last_name, address1, city, state, zip, country, phone]
clicks_to_advance: 1
drop_off_observed: 15-25% # biggest leakage in poor flows
- step: shipping_method
fields_required: []
clicks_to_advance: 1
drop_off_observed: 5-10%
- step: payment
fields_required: [card_number, exp, cvc, billing_address]
clicks_to_advance: 1
drop_off_observed: 10-15%
- step: review_and_pay
fields_required: []
clicks_to_advance: 1
Each step = a drop-off opportunity. Goal: ≤ 3 steps mobile, ≤ 4 steps desktop.
VALIDATION: Step map captures real flow, not assumed. Field count per step is exact.
| Express Method | Required for | Position |
|---|---|---|
| Apple Pay | All Safari/iOS users (60%+ of US mobile) | ABOVE shipping form, not "or pay another way" |
| Google Pay | All Android Chrome users | Adjacent to Apple Pay |
| Shop Pay | Shopify stores (massive returning-customer lift) | Top of checkout |
| PayPal | Cross-platform; older demo + cross-border | Express button OR payment-method |
| Amazon Pay | Amazon-loyal demo (saves 2-step) | Optional, evaluate per AOV |
| Klarna / Afterpay / Affirm | AOV > $50 | Both cart AND payment step (cart messaging boosts add-to-cart) |
Audit checks:
VALIDATION: Express checkout available at the FIRST point of checkout, not buried at the bottom.
Forced account creation is the #2 abandonment cause (24% per Baymard).
Required:
VALIDATION: Guest checkout is at least as prominent as account checkout in the UI.
Every additional field drops conversion ~7% (Baymard). Audit each field:
Eliminate:
Auto-fill / inference:
Smart validation:
VALIDATION: Total checkout field count ≤ 8 for a US guest flow.
Region-aware payment menu:
| Region | Must-have methods |
|---|---|
| US | Card (Visa/MC/Amex/Discover), Apple Pay, Google Pay, Shop Pay (if Shopify), PayPal, ACH for high-AOV |
| EU | Card, Apple/Google Pay, iDEAL (NL), Bancontact (BE), SOFORT (DE/AT), Giropay (DE), Klarna, SEPA Direct Debit |
| LatAm | Card, OXXO (MX), Boleto (BR), Pix (BR), MercadoPago |
| APAC | Card, Apple/Google Pay, Alipay (CN), WeChat Pay (CN), GrabPay (SEA), PayNow (SG), UPI (IN) |
| MENA | Card, Apple Pay, COD prominent (for trust) |
VALIDATION: Region detection (IP / billing country) drives payment menu. Don't show iDEAL to US buyers; don't show Pix to EU.
Unexpected shipping costs = #1 abandonment cause (48% per Baymard). Audit:
VALIDATION: Order total shown at checkout matches order total shown on cart. No surprise additions > 5%.
Mobile checkout has different failure modes:
inputmode (numeric for card, email for email, tel for phone)font-size: 16px minimum)autocomplete attributes correct per WHATWG)VALIDATION: Test on actual iOS Safari + Android Chrome, not desktop dev tools.
Generate checkout_audit_{date}.md:
# Checkout Audit — {site} — {date}
## Current state
- Steps: N
- Express checkout: Apple Pay {present/missing}, Google Pay {present/missing}, Shop Pay {present/missing}
- Guest checkout: {prominent/buried/missing}
- Field count: N
- Mobile checkout: {smooth/issues}
- Estimated current abandonment: {x}%
## P0 — Highest impact
- [ ] Add Apple Pay above fold. Expected lift: +22% conversion. Effort: 2 hours via Stripe Payment Element.
- [ ] Enable guest checkout. Expected lift: +25% from forced-account abandonment population. Effort: 4 hours.
## P1 — High impact
- [ ] Reduce form fields from 14 to 8. Expected lift: +35%. Effort: 8 hours UX + backend.
- [ ] Show shipping estimate on cart page. Expected lift: +20% (eliminates #1 abandonment cause). Effort: 6 hours.
## P2 — Medium
- [ ] Move from 4-step to 1-page checkout. Expected lift: +20%. Effort: 2-4 days.
- [ ] Add Klarna/Afterpay/Affirm for AOV > $50. Expected AOV lift: +15%. Effort: 1 week.
## P3 — Polish
- [ ] Sticky bottom CTA on mobile. Effort: 2 hours.
## Re-audit after fixes
Re-run `/checkout-audit` after each P0/P1 ships.
VALIDATION: Each item has expected lift (numeric) + effort + concrete fix.
Common gap: missing actual mobile test → desktop dev-tools "looks fine" while real Safari has zoom-on-focus killing 30% of mobile.
~/.claude/skills/checkout-audit/LEARNINGS.md.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..
日本語の概要は準備中です。原文の説明を表示しています。
Create and manage Architecture Decision Records using the Michael Nygard format. Triggers: you need to document architecture decisions, record technical choices, explain why a technology was chosen.
日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。
Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
日本語の概要は準備中です。原文の説明を表示しています。