Usability Testing logo

Usability Testing

Organization
rampstackco
usability-testing

Plan and run usability tests on existing or prototype designs including test design, task scripts, moderation, observation, and findings synthesis. Use this skill whenever the user wants to test usability, run a moderated test, run an unmoderated test, validate a design, find usability issues, or improve task completion. Triggers on usability test, usability testing, moderated test, unmoderated test, task script, think aloud, prototype testing, user testing, design validation, task completion. Also triggers when the user has built something and wants to know if real users can use it before shipping.

Overview

Publisherrampstackco
Repositoryclaude-skills
Skill nameusability-testing
Stars
951
Forks
132
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by rampstackco on GitHub. Read the source before you install it.

Installation

Install the Usability Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/rampstackco/claude-skills/tree/main/skills/usability-testing
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rampstackco/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/usability-testing .claude/skills/usability-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Usability Testing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Usability Testing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Usability Testing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Usability Testing

Plan and run tests that find usability problems before users hit them in production. Stack-agnostic. Tool-agnostic.

This skill is for testing existing designs or prototypes. For broader discovery research, use ux-research. For conversion testing in production, use cro-optimization.


When to use

  • Before launching a new flow or major redesign
  • After a redesign to verify it doesn't introduce new problems
  • When analytics show drop-off but you don't know why
  • When customer support tickets pattern around specific UI areas
  • Pre-launch user validation
  • Comparing two design directions

When NOT to use

  • Discovery / generative research (use ux-research)
  • Live conversion optimization (use cro-optimization)
  • Mapping the broader experience (use journey-mapping)
  • Pure quantitative measurement (use analytics-strategy)

Required inputs

  • The design or prototype to test (functional or near-functional)
  • Specific tasks users would do
  • The audience (who should be tested)
  • Testing infrastructure (moderated tool, unmoderated tool, in-person setup)

The framework: 5 phases

1. Define what to test

Don't test the whole product. Test specific tasks.

Task selection criteria:

  • The task represents a real user goal (not "click around and explore")
  • The task has a clear start and end
  • The task is achievable in 2 to 10 minutes
  • The task is one of: most common, most strategic, most problematic

Examples of testable tasks:

"You want to find a contractor near you who can install a fence. Show me how you'd do that on this site."

"You're a first-time visitor. You want to understand if this product fits your needs. Walk me through how you'd evaluate it."

"Your team needs a new tool to manage projects. Use this site to figure out which plan is right for a 12-person team."

Task framing rules:

  • State the user goal, not the system action ("find a place to stay" not "click the search button")
  • Provide context (why are you doing this?)
  • Don't reveal the path
  • Don't use product terminology in the task framing

2. Choose moderated or unmoderated

Moderated (live, with researcher):

  • Researcher observes and probes in real time
  • Best for early-stage prototypes, complex tasks, novel concepts
  • Higher cost, smaller sample (5 to 8 participants typical)
  • Catches surprises and probe deeper

Unmoderated (recorded, asynchronous):

  • Participant completes alone, often via tool (UserTesting, Maze, Lookback)
  • Best for stable designs, simple tasks, larger sample
  • Lower cost, larger sample (15 to 30 participants typical)
  • Catches patterns at scale, less depth per session

For most teams: moderated for early/critical decisions, unmoderated for ongoing validation.

3. Recruit

Target audience - not just convenience.

Recruit criteria:

  • Match real users (target audience, not just "anyone")
  • Mix of experience levels with the product (new and existing if applicable)
  • Mix of relevant device types (mobile, desktop, tablet if relevant)
  • Exclude friends, family, employees

Sample size:

  • Moderated: 5 to 8 participants (Nielsen's "5 users find 85% of usability issues" for the most common segment)
  • Unmoderated: 15 to 30 participants (more participants compensate for less probing)
  • Multi-segment testing: 5 to 8 per segment

4. Run the test

Pre-task setup:

  • Confirm recording works
  • Brief participant (purpose, anonymity, recording, "no wrong answers")
  • Get verbal consent
  • Have participant share screen if remote

Moderated session structure:

  1. Warm-up (2 to 3 min). Easy questions to put participant at ease.
  2. Pre-test questions (3 to 5 min). Background context, current behavior with similar products.
  3. Task 1 (5 to 10 min). Describe task. Have participant attempt while thinking aloud.
  4. Post-task questions (1 to 2 min). What was easy/hard? Anything confusing?
  5. Repeat for tasks 2, 3, 4 (typically 3 to 5 tasks per 60-minute session).
  6. Overall debrief (5 to 10 min). General reactions, comparisons to alternatives, anything else.
  7. Close (2 min).

Moderation principles:

  • Encourage think-aloud ("What's going through your mind?")
  • Don't help unless they're truly stuck (and even then, only after a long pause)
  • Don't lead ("Are you looking for the menu?" - bad)
  • Note where they hesitate, scroll, or backtrack
  • Note their language vs the product's language
  • Note emotional reactions

Anti-patterns:

  • Talking too much (researcher should talk maybe 20% of the time)
  • Defending the design when participants struggle
  • Helping prematurely
  • Asking participants to predict their future behavior
  • Treating participant suggestions as features ("Users want X" - test demand for X separately)

5. Synthesize and report

Patterns across participants are signal. Single-participant complaints are weaker (but worth investigating).

Synthesis steps:

  1. Issue inventory. Every issue observed, with which participant, which task, severity.
  2. Cluster. Issues that are the same root problem.
  3. Severity.
    • Critical: Blocks task completion. Most users hit this.
    • Major: Significantly slows task. Many users hit this.
    • Minor: Friction. Some users hit this. Workaround exists.
    • Cosmetic: Polish. Doesn't affect task.
  4. Recommendations. For each issue, propose specific fixes.
  5. Prioritize. By severity and effort.

Report structure:

markdown
# Usability Test: [Design / flow]

## Summary
[2 to 3 paragraphs covering: what was tested, headline findings, top 3 priorities]

## Method
[Moderated/unmoderated, sample size, audience, dates, tasks]

## Critical findings
[Each with description, frequency, supporting evidence (quotes/clips), recommendation. Where evidence was not obtained, state the gap per the data-availability rule]

## Major findings
[Same structure]

## Minor findings
[Brief]

## Cosmetic findings
[Briefest]

## What worked well
[Calibration: capture successes too]

## Recommendations
[Prioritized list with effort estimates]

## Next steps
[Test re-run schedule, design iteration plan]

Workflow

  1. Define the goals. What decisions hinge on this? What tasks matter most?
  2. Design tasks. 3 to 5 specific, realistic, goal-framed tasks.
  3. Choose moderated vs unmoderated. Match to stage and depth needed.
  4. Recruit. Specific to audience.
  5. Pilot. 1 to 2 sessions before main batch. Refine tasks if needed.
  6. Run. Follow the protocol. Stay disciplined.
  7. Synthesize during, not just after. Patterns emerge by session 4 or 5.
  8. Report. Multiple formats - written report + highlight clips.
  9. Track fixes. Every critical issue should have an owner and date.
  10. Re-test after fixes. Verify the fix worked, didn't introduce new issues.

Failure patterns

  • Testing the whole product instead of specific tasks. Vague results.
  • Tasks that reveal the path. ("Click the menu and find...")
  • Friends and family as participants. Biased, not representative.
  • Researcher leading the participant. Findings reflect the researcher.
  • Defending the design when participants struggle. Misses real issues.
  • Helping too quickly. Participant doesn't experience the friction.
  • Treating participant suggestions as features. Users solve their problem; product team designs the solution.
  • One participant = data point. A single strong opinion isn't a finding.
  • Skipping severity scoring. All findings treated equally; team can't prioritize.
  • Reports no one reads. Highlight clips and live walkthroughs work better than 80-page decks.
  • Testing once, never re-testing. Fixes that introduce new problems go undetected.

Output format

Default outputs:

  1. Test plan (before testing) - usability-test-plan-[topic].md
  2. Task script (per session) - usability-tasks-[topic].md
  3. Findings report (after synthesis) - usability-findings-[topic].md
  4. Highlight clips (separately produced)

If required data is unavailable

This skill's output depends on data, measurements, or tool results it cannot generate on its own. When a required input, tool, or data source is unavailable or unverifiable, the sanctioned output is the deliverable with the gap stated: what was needed, what was actually obtained or verified, and which parts of the output are affected. Fabricating, estimating, or interpolating a required number to complete the deliverable is never sanctioned. A stated gap is a complete answer.


Reference files

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Usability Testing AI skill do?

Plan and run usability tests on existing or prototype designs including test design, task scripts, moderation, observation, and findings synthesis. Use this skill whenever the user wants to test usability, run a moderated test, run an unmoderated test, validate a design, find usability issues, or improve task completion. Triggers on usability test, usability testing, moderated test, unmoderated test, task script, think aloud, prototype testing, user testing, design validation, task completion. Also triggers when the user has built something and wants to know if real users can use it before...

Why use Usability Testing on TypingMind?

Because you install it once and use it with any model. Usability Testing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Usability Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rampstackco/claude-skills/tree/main/skills/usability-testing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Usability Testing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Usability Testing?

As many as you like. As long as a model supports skills, you can use Usability Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Usability Testing AI skill free?

Yes. It is published on GitHub by rampstackco under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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