Design Thinking process—Empathize, Define, Ideate, Prototype, Test. Use for product design, solving ambiguous problems, or when you don't know what users really need.
npx skills add https://github.com/neurofoo/agent-skills --skill design
Work through the full design thinking process—Empathize, Define, Ideate, Prototype, Test.
Move through each phase, building on insights from the previous one. The process is iterative—expect to loop back based on what you learn.
Challenge: [What we're trying to solve]
Users: [Who we're designing for]
*Understand the user and their context*
| Attribute | Description |
|-----------|-------------|
| Who are they? | [Demographics, role] |
| What's their context? | [Environment, circumstances] |
| What are they trying to do? | [Goals, tasks] |
| Pain Point | Severity | Current Workaround |
|------------|----------|-------------------|
| [pain] | High/Med/Low | [how they cope] |
| Quadrant | Observations |
|----------|--------------|
| Say | [Quotes, statements] |
| Think | [Beliefs, concerns] |
| Do | [Actions, behaviors] |
| Feel | [Emotions, reactions] |
*Frame the problem worth solving*
[User] needs [need] because [insight].
> The Challenge: [Specific, actionable problem to solve]
*Generate many possible solutions*
| # | Idea | Type |
|---|------|------|
| 1 | [idea] | Safe / Moderate / Wild |
| 2 | [idea] | Safe / Moderate / Wild |
| 3 | [idea] | Safe / Moderate / Wild |
| Idea | Why This One? | Feasibility |
|------|---------------|-------------|
| [idea] | [rationale] | High/Med/Low |
*Make ideas tangible quickly*
Idea to prototype: [Which idea]
Prototype type: Paper mockup / Wireframe / Physical model / Storyboard
What we're testing:
*Learn from real users*
Who to test with: [User profile]
Questions to answer:
Success indicators: [What would indicate this works]
Failure indicators: [What would indicate this fails]
Based on what we learn, we'll likely need to revisit:
$ARGUMENTS
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Use when implementing any feature or bugfix, before writing implementation code
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Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Take neurofoo/design from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.