Purpose
Evaluate a user flow screen-by-screen against seven friction lenses and return a ranked list of specific problems with concrete fixes — so a design review produces defensible, actionable feedback instead of subjective reactions. Replaces "this feels off" with named friction points, severity ratings, and a prioritized remediation list.
When to Use
Invoke this skill when the user asks to:
- Critique or review a user flow, journey, or task path
- Diagnose why users are dropping off or abandoning a task
- Prepare structured feedback for a design review or critique session
- Evaluate an onboarding, checkout, signup, or activation flow
- Compare a proposed flow against best-practice usability standards
- Turn a Figma flow or prototype walkthrough into written review notes
Inputs Required
Before starting, collect:
- Flow name and goal: What flow this is (e.g., "checkout," "account setup") and the single task the user is trying to complete
- Step-by-step description: The screens/states in order, with what the user sees and does at each — pasted, described, or listed
- Target user: Who moves through this flow and their level of familiarity with the product
- Entry context: Where the user comes from and what they expect when they arrive
- Success definition: What counts as completing the flow
- Known problems (optional): Any drop-off data, complaints, or hypotheses already in hand
- Constraints (optional): Technical, brand, or platform limits the fixes must respect
If drop-off data is missing, critique based on heuristic friction; if the target user isn't specified, assume a first-time user and note the assumption.
Instructions
Step 1: Map the Flow into Discrete Decision Points
Restate the flow as an ordered list of steps. For each step, identify:
- The user's job at this step: The one thing they're trying to do
- The decision or action required: What they must choose, input, or confirm
- The system's response: What happens next
Flag any step where the user's job isn't obvious from the screen alone — these are early friction candidates.
Step 2: Evaluate Against the Seven Friction Lenses
Run every step through these seven lenses. For each lens, note where the flow holds and where it breaks.
Lens 1 — Entry Clarity Does the user understand where they are and what this flow will accomplish within 5 seconds of arriving?
- Check for orientation: title, progress indicator, expectation-setting
- Friction signal: user must infer the flow's purpose or scope
Lens 2 — Decision Confidence At each choice point, does the user have enough information to decide without hesitation?
- Check for labeled options, sensible defaults, and consequence clarity
- Friction signal: two options that look equally valid with no guidance; irreversible actions without confirmation
Lens 3 — Cognitive Load Is the user asked to hold too much in memory or process too much at once?
- Check for step count, fields per screen, jargon, and simultaneous decisions
- Friction signal: more than ~5 new decisions on one screen; requiring recall instead of recognition
Lens 4 — Error Prevention & Recovery Does the flow prevent mistakes before they happen and let users recover gracefully?
- Check for inline validation, forgiving inputs, clear undo/back paths
- Friction signal: errors surfaced only after submit; dead ends with no way back
Lens 5 — Momentum Does each step pull the user forward, or does it introduce hesitation, distraction, or exit ramps?
- Check for competing CTAs, premature asks (payment/permissions too early), and unnecessary interruptions
- Friction signal: a single clear "next" action is missing or buried
Lens 6 — Task Completion Does the flow deliver the user to their goal, and do they know they succeeded?
- Check for explicit success confirmation, clear next step, and value delivery
- Friction signal: flow ends without acknowledgment or leaves the user unsure what to do next
Lens 7 — Drop-off Risk Rank each step by likelihood of abandonment, weighing effort, friction density, and value received so far.
- Friction signal: high-effort steps positioned before the user has experienced value
Step 3: Catalog and Rank Friction Points
Compile every friction point found. For each, record:
- Location: Which step
- Lens: Which of the seven lenses it violates
- Severity: Critical (blocks or loses users) / High (causes hesitation, some loss) / Medium (adds effort) / Low (polish)
- Why it hurts: One sentence connecting the friction to abandonment or confusion
- Recommended fix: A specific, implementable change — not "improve clarity"
Rank the full list by severity, then by proximity to the flow's entry (early friction compounds).
Step 4: Identify the One Highest-Leverage Fix
Name the single change that would most improve completion. Be opinionated and justify it against the ranked list.
Step 5: Note What's Working
Call out 2–3 things the flow does well — so the critique is balanced and the team knows what not to break.
Output Format
- Structure: Flow map → seven-lens evaluation → ranked friction table → highest-leverage fix → what's working
- Length: 800–1,200 words
- Format: Structured document; friction points as a ranked table (Location | Lens | Severity | Why it hurts | Fix)
- Sections: Flow Map, Seven-Lens Findings, Ranked Friction Points, Highest-Leverage Fix, What's Working
- Tone: Lead product designer in critique — direct, specific, evidence-based; critiques the flow, not the designer
Quality Checklist
Before delivering output, verify:
- [ ] Every step in the provided flow is mapped with the user's job stated
- [ ] All seven lenses are applied — none skipped
- [ ] Each friction point has a location, lens, severity rating, and a specific fix (no "improve UX" placeholders)
- [ ] The friction table is ranked by severity, not listed in random order
- [ ] Exactly one highest-leverage fix is named and justified
- [ ] At least 2 things the flow does well are called out
Notes
- Severity should reflect impact on completion, not personal preference — a critical rating means users are lost or blocked, not that a designer would style it differently
- Early-flow friction is disproportionately costly: a confusing entry screen loses users before they've invested effort, so weight it accordingly
- When drop-off data exists, reconcile it against the heuristic findings — the step users actually abandon should correspond to a high-severity friction point; if it doesn't, dig deeper there
- This framework critiques the flow as designed; it does not replace usability testing, but it sharpens what to test
How to use this skill
This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.
Installing in Claude Code:
~/.claude/skills/<folder-name>/SKILL.md— auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)<your-project>/.claude/skills/<folder-name>/SKILL.md— auto-loads only when working in that project (recommended for project-specific skills)
Restart Claude Code or open a new session to register.
Using in Claude.ai, ChatGPT, Gemini, or other AI tools:
- Drag this file into a new chat, or copy and paste its contents
- Send your task or request as your next message — the AI will apply the skill where it fits
For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills