portal-synthetic-users

Pre-validates wireframes and prototypes with LLM evaluators conditioned on research personas.

Updated Jul 27, 2026
One-click install
npx skills add https://github.com/ArthurZizumbo/karisma-data --skill portal-synthetic-users-arthurzizumbo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: portal-synthetic-users
Source: https://github.com/ArthurZizumbo/karisma-data/tree/main/.claude/skills/portal-synthetic-users
Command: npx skills add https://github.com/ArthurZizumbo/karisma-data --skill portal-synthetic-users-arthurzizumbo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Recruiting real users for early design iteration is slow and expensive, so wireframes and prototypes often go untested until late-stage validation. This Skill runs PerceptUI-style synthetic user sessions where LLM evaluators are conditioned on the 8 personas from prior UX research, producing natural-language rationales that expose usability issues before human testing. ## Core Features & Use Cases - Persona-Conditioned Evaluation: One LLM evaluator per persona from the A1 research matrix, answering a fixed question battery in first person with grounded rationales. - Activity-Specific Batteries: Distinct protocols for A3 (taxonomy and wireframe review supporting card sorting) and A4 (seven real prototype screens covering access, exploration, governance, assistant, and export). - Documented Design Iteration: Findings are synthesized by severity and frequency across the 8 personas, requiring at least one documented design change with before/after evidence. - Use Case: Before running the A5 SUS test with real participants, pre-validate the high-fidelity prototype screens with the 8 synthetic evaluators, capture their rationales, fix the top consensus findings, and report the process as complementary pre-validation. ## Quick Start Run a synthetic pre-validation of the A4 prototype screens using the 8 personas from A1 and produce a findings report with at least one documented design iteration.

Frequently Asked Questions about portal-synthetic-users

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I pre-validate a prototype with synthetic users before real usability testing?▼

Condition one LLM evaluator per persona using the full persona file (demographics, goals, pain points, habits), show each the interface screens, and run a fixed question battery. Collect first-person answers with natural-language rationales, then synthesize findings by severity and frequency across personas.

What is PerceptUI-style persona conditioning for UX evaluation?▼

PerceptUI is a method that predicts how a specific user would respond to interface questions, conditioned on a persona profile, producing natural-language rationales. This Skill adopts its conditioning protocol with an available LLM rather than retraining the original framework.

Can synthetic user evaluation replace SUS testing with real participants?▼

No. Synthetic pre-validation is strictly complementary and never substitutes the human SUS test with at least 5 real participants. Every report must declare this limitation, and synthetic findings are kept separate from field data and never counted toward sample size.

How many personas should condition synthetic UX evaluators?▼

This protocol uses the 8 personas delivered in the A1 research phase, reusing real research as conditioning rather than inventing ad-hoc profiles. Counts are reported in absolutes over 8, never percentages, since that sample size would exaggerate evidence strength.

What are the limitations of LLM-based synthetic user testing?▼

Evaluators inherit biases from the LLM and from how personas were written, so their answers are plausible predictions, not field data. Reports must include a mandatory bias and limitations declaration, and idiosyncratic findings are separated from cross-persona consensus.

When should I use real UX research instead of synthetic evaluators?▼

Use real fieldwork (surveys, interviews, SUS tests) for the human validation required by the rubric, handled by the portal-ux-research skill. Synthetic evaluators are design tooling for early iteration, not a feature of the product or a replacement for participant data.