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".
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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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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
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.
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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".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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..
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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..
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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.
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Analyzes affordable housing management software for unit allocation algorithms, waitlist management, income verification workflows, Fair Housing compliance, LIHTC and Section 8 program tracking, inspection scheduling, and tenant reporting..
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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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.