---
name: user-flow-critique-framework
description: "Delivers a structured critique of a user flow across seven diagnostic lenses — entry clarity, decision confidence, cognitive load, error prevention, momentum, task completion, and drop-off risk — surfacing friction points step-by-step and ranking them by severity with specific fixes. Use when reviewing a user flow, running a design critique, diagnosing why users abandon a task, or preparing design review feedback for a team."
argument-hint: "[flow-name] [user-goal]"
allowed-tools: ["Read"]
---

# User Flow Critique Framework

## 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

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## How to use this skill

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Restart Claude Code or open a new session to register.

**Using in Claude.ai, ChatGPT, Gemini, or other AI tools:**

1. Drag this file into a new chat, or copy and paste its contents
2. Send your task or request as your next message — the AI will apply the skill where it fits

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