SUMMARY
Purpose: QA Documentation (Dev Collaboration) ensures alignment between product design and engineering by creating clear, testable documentation that captures edge cases, design intent, and experience expectations.
Design Thinking Phase: Prototype & Test
Time: 60–90 min design-dev sync + 3–5 hours documentation
Difficulty: ⭐⭐
When to use:Before handing off high-fidelity designs to developmentWhen aligning complex interaction models with backend/API constraintsPost-sprint demo to identify UX gaps prior to production release
What it is
QA Documentation is a UX-adjacent process that bridges the gap between product design and engineering. It outlines user expectations, accessibility standards, interaction logic, and known edge cases. The documentation helps developers, QA engineers, and designers collaborate to maintain design integrity during implementation.
📺 Video by NNgroup. Embedded for educational reference.
Why it matters
Thorough QA documentation helps ensure the user experience isn’t compromised during implementation. By aligning design intent and development constraints early, teams reduce rework, avoid misinterpretation, and improve velocity. It also provides an auditable reference for future UX debt triage.
When to use
- When handing off complex microinteractions or logic-heavy flows
- If QA typically flags mismatched UX behaviour late in the sprint
- When deploying across multiple platforms (e.g. web + native)
Benefits
- Rich Insights: Helps clarify real-world edge cases prior to engineering decisions.
- Flexibility: Scales from component-level validation to full user flow documentation.
- User Empathy: Reinforces user scenarios often missed in dev tickets.
How to use it
- Schedule a joint QA planning session with dev + design + product owners during final stages of a sprint.
- Create a documented checklist per flow or component, including visual references, interaction logic, success/error states, and accessibility notes.
- Define “Red Routes” (critical flows) with stricter QA coverage and real-world user expectations.
- Use version-controlled tools (like Notion, Confluence, or integrated Figma QA plugins) to keep docs traceable.
- Tie each documented item to a user story, development ticket, or feature flag where relevant.
Example Output
Feature: Onboarding Flow
- Expected Behaviour – Step 1 (Enter Email):
- Input placeholder text matches empty state guidance
- Error message appears after invalid format entry ("Please enter a valid email address")
- RTL language support verified
- Edge Case: Autofill from password manager may skip focus state — include visual state as part of QA test
- Accessibility: VoiceOver correctly reads label as “Email address, required field”
- Responsiveness: Tested up to min-width 320px
Common Pitfalls
- Over-documenting: Avoid endless edge cases no one will test — focus on Red Routes and known breakpoints.
- Vague language: “Should look right” isn’t testable. Be precise with what constitutes success.
- Stale alignment: Not updating after last-minute dev changes silently breaks UX assumptions. Version and cross-check.
10 Design-Ready AI Prompts for QA Documentation – UX/UI Edition
How These Prompts Work (C.S.I.R. Framework)
Each of the templates below follows the C.S.I.R. method — a proven structure for writing clear, effective prompts that get better results from ChatGPT, Claude, Copilot, or any other LLM.
C.S.I.R. stands for:
- Context: Who you are and the UX situation you're working in
- Specific Info: Key design inputs, tasks, or constraints the AI should consider
- Intent: What you want the AI to help you achieve
- Response Format: The structure or format you want the AI to return (e.g. checklist, table, journey map)
Level up your career with smarter AI prompts.Get templates used by UX leaders — no guesswork, just results.Design faster, research smarter, and ship with confidence.First one’s free. Unlock all 10 by becoming a member.
Prompt Template 1: “Generate QA Scenarios for a Critical UX Flow:”
Generate QA Scenarios for a Critical UX Flow:
Context: You are a Senior UX Designer preparing handoff for a mobile onboarding experience.
Specific Info: The flow has 4 steps (email > password > profile pic > confirmation), and includes form validation and conditional logic.
Intent: Help QA validate UX expectations, including happy path, edge cases, and accessibility.
Response Format: Provide a table listing “Function”, “Expected Outcome”, “Edge Case to Check”, “A11y Check”.
If unsure about device constraints or platform-specific behaviour, ask clarifying questions to guide documentation.
Then, suggest one way to visualise or prototype these states for better dev alignment.
Prompt Template 2: “Document Accessibility Specs for Cross-Platform Components:”
Document Accessibility Specs for Cross-Platform Components:
Context: You’re a UX/UI designer working on a component library with parity across iOS, Android, and Web.
Specific Info: Focus on the toggle switch, radio group, and segmented control components.
Intent: Generate a consistent set of accessibility behaviours (labels, focus order, ARIA roles) across platforms.
Response Format: Output a table: Component | Platform | A11y Expectation | Note
If platform-specific APIs (e.g. VoiceOver vs TalkBack) differ, flag the discrepancy clearly.
Then, suggest tools or heuristics that could help QA verify these.
Prompt Template 3: “Create QA-Handoff Checklists from Figma Designs:”
Create QA-Handoff Checklists from Figma Designs:
Context: You are a product designer prepping QA documentation at the end of a sprint.
Specific Info: The design file includes 12 screens for a logged-in dashboard experience.
Intent: Automatically generate testable documentation based on layers, variants, and interaction prototypes.
Response Format: Provide a bullet list grouped by screen ID with focus on clickable items, data states, and error handling.
If interactivity or flow dependencies are vague, ask for clarification before generating output.
Then, recommend how to track coverage during testing sessions.
Prompt Template 4: “List Edge Cases for a Logged-In Checkout Flow:”
List Edge Cases for a Logged-In Checkout Flow:
Context: You're a UX lead reviewing an e-commerce feature during QA planning.
Specific Info: Applies to cart total, shipping address, applied rewards, and failed payment.
Intent: Pre-empt common failure points specific to logged-in users with saved data.
Response Format: List edge cases with a short rationale and test suggestion.
If assumptions are unclear (e.g., reward expiry logic), ask questions to surface intent.
Then, propose one critical test to simulate broken logic.
Prompt Template 5: “Translate UX Behavior into QA Acceptance Criteria:”
Translate UX Behavior into QA Acceptance Criteria:
Context: You're working with QA to convert prototype interactions into testable criteria.
Specific Info: The interaction is a scrollable tab nav with sticky headers and dynamic content.
Intent: Make visible behaviours explicit so QA can validate them systematically.
Response Format: Use Given / When / Then format for each microinteraction.
If any interaction logic isn’t captured in the prototype, note it as needing design clarification.
Suggest applying this format to one other component for consistency.
Prompt Template 6: “Summarise Known Gaps Between Design and Build:”
Summarise Known Gaps Between Design and Build:
Context: Your team just did a sprint demo but differences between Figma and build are emerging.
Specific Info: The gap exists in spacing, animation timing, and visual hierarchy on two key templates.
Intent: Draft concise QA notes spelling out divergences to align product/dev/design.
Response Format: Provide a per-template list: “Observed”, “Expected”, “Impact”, “Fix Plan”.
If some fixes are deferred to post-MVP, indicate clearly to reduce ambiguity.
Then, suggest a recurring QA checkpoint that might prevent similar issues.
Prompt Template 7: “Create Accessibility Test Scenarios:”
Create Accessibility Test Scenarios:
Context: You’re developing QA guidance for a marketing microsite.
Specific Info: Design includes Lottie animations, embedded forms, and timed onboarding text.
Intent: Ensure accessibility concerns (users with motion sensitivity, screen readers, keyboard nav) are validated.
Response Format: Provide scenarios framed as test actions with expected results.
If any external scripts/plugins are known to interfere with a11y, flag them for review.
Then, suggest a checklist to integrate into dev QA cycles.
Prompt Template 8: “Compare QA Docs Across Environments:”
Compare QA Docs Across Environments:
Context: You’re reviewing version discrepancies from staging vs production as a product designer.
Specific Info: Components tested OK in staging but degrade visually in prod (likely due to CSS conflicts).
Intent: Build an audit of what was documented, what was shipped, and what changed.
Response Format: Provide a diff-style checklist with severity, origin, and resolution path.
If original staging screenshots or tokens are missing, ask for input before comparing.
Then, suggest how to track design parity sustainably.
Prompt Template 9: “QA Evaluation Map for Multi-Step Flows:”
QA Evaluation Map for Multi-Step Flows:
Context: You’re the UX lead creating evaluation plans for an application process flow.
Specific Info: The flow has branching logic depending on user category (3 types), auto-save, and progressive disclosure.
Intent: Help QA map decision points and verify that logic executes as expected.
Response Format: Flow map or nested list: Step > Logic > UX Intent > Expected Outcome > QA Note
If logic documentation is outdated, ask the PM for current specs to proceed.
Recommend one visual tool for clarifying such conditional logic.
Prompt Template 10: “Draft QA Summary Notes Post-Design QA Review:”
Draft QA Summary Notes Post-Design QA Review:
Context: You just ran a final pre-launch design QA of a new feature set.
Specific Info: Teams noted visual inconsistencies, missing alt text, and layout shifts on Safari.
Intent: Summarise feedback into a consistent, testable doc for QA and dev.
Response Format: Categorised list: Visual, Functional, Accessibility, Browser-Specific.
If any items are unclear or subjective, recommend a design token or doc reference to align.
Then, suggest how to incorporate this format into routine QA meetings.
Recommended Tools
- Figma + FigJam (with QA handoff plugins like “Dovetail QA”)
- Notion or Confluence for structured, linkable QA docs and test cases
- Axe DevTools or Lighthouse for automated accessibility tests
- Zeplin or Zeroheight for bridging design tokens into dev
