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- Implemented a status bar item for LexAI with dynamic status updates (ready, processing, notReady). - Created a suggestion panel for displaying and interacting with AI-generated suggestions. - Added functionality for accepting, regenerating, and discarding suggestions within the suggestion zone. - Introduced configuration options for writing style, prompt patterns, personas, and formats. - Integrated progress indicators for long-running tasks and improved user feedback. - Established TypeScript configuration for the vscode package.
20 lines
4.5 KiB
Markdown
20 lines
4.5 KiB
Markdown
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name: ux-psych-audit
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description: Behavioral-psychology audit of an implemented user journey — decision cost, effort, momentum, value-before-ask, investment, framing, emotional arc, and trust, grounded in evidence-backed principles. Returns P0–P3 findings with evidence and smallest fix; dark patterns are always defects. Owner — ux-psychologist; read-only. Use on implemented UX; pre-build psychology enters as design-spec constraints.
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---
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Audit what users actually experience against how people actually decide. Read-only: findings and smallest fixes, never patches. First name the journey, then walk it end to end in the implementation (templates, widgets, copy, defaults, prices): **first-run/onboarding · core task loop · return visit · upgrade/checkout · exit (cancel, error, uninstall)**. Grep for real option counts, defaults, and progress states — never assume them.
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1. **Decision cost.** Count simultaneous choices at each decision point (Hick's law; in the classic jam study 24 options converted ~3%, 6 options ~30%). Every extra option, field, or setting must earn its place; prefer progressive disclosure, and exactly one visually primary action per screen (Von Restorff).
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2. **Effort & defaults.** Most users never change defaults and read them as recommendations: are forms pre-filled with the most common choice so the task is scan-and-adjust, not create-from-scratch? Is irreducible complexity absorbed by the system rather than the user (Tesler)? Primary targets large and reachable (Fitts).
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3. **Momentum.** Never start a user at zero: endowed progress (pre-stamped loyalty cards complete at roughly double the rate) and the goal-gradient effect (effort rises near completion) reward visible head starts. Visible incomplete steps pull users back (Zeigarnik); feedback within ~400 ms keeps flow (Doherty threshold).
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4. **Value before ask (reciprocity).** Deliver a real sample of value before signup, permission, or payment walls — partial results, previews, trial access (Cialdini's reciprocity). A wall before first demonstrated value is at least P1.
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5. **Investment & ownership.** Early personalization and building (name it, pick goals, assemble the first artifact) raise perceived value (IKEA and endowment effects) and make each return visit richer — the investment step of the Hooked loop. Ask: what does a user own after two minutes?
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6. **Motivation & framing.** At each conversion moment check Fogg's B=MAP: are motivation, ability, and a well-timed prompt all present, and which one is missing where users drop? Losses weigh roughly twice as much as gains (Kahneman) — frame genuinely at-risk value honestly, never invent risk. Prices and plans need deliberate context and anchors, not isolation (contrast effect).
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7. **Emotional arc.** People judge an experience by its peak and its end (peak-end rule): audit the best moment and every exit — success, error, empty, and cancellation paths — because the end of a bad journey is where trust is decided. Familiar patterns lower load (Jakob's law); visual polish buys perceived usability (aesthetic-usability effect) but never substitutes for it.
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8. **Trust screen — always run last.** Dark patterns are defects, not tactics: fake urgency/scarcity, confirmshaming, roach-motel cancellation, hidden costs or drip pricing, forced continuity without warning, disguised ads, guilt loops, nagging re-prompts. Any of these is P0–P1 with the trust and regulatory risk named. Persuasion aligned with the user's chosen goal is good design; persuasion against the user's interest is a defect regardless of conversion lift.
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Rank findings **P0** (trust-destroying mechanic, or the user's job/value blocked before value is demonstrated), **P1** (principle violated on a core conversion/retention path with likely drop-off), **P2** (missed momentum/framing reinforcement), **P3** (polish). Each finding: evidence (file/line or reproduction) · principle · expected behavioral impact · smallest fix · where analytics exist, the metric that would confirm it. Findings are hypotheses about behavior — recommend the measurement, don't promise the lift. Do not invent findings to seem thorough; `none` after meaningful checks is a valid result. Route accepted fixes to the orchestrator as task contracts; durable copy/pattern rules go to the ux-ui-designer for `DESIGN_SYSTEM.md`.
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Return exactly: **Verdict** (behaviorally sound / needs work / trust risk) · **Findings** (P0–P3 or `none`) · **Journey audited** (stages walked, screens/files inspected, lenses applied) · **Top opportunities** (≤ 3: principle → smallest change → metric).
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