Apple LeanUX++ design workflow, journey schema, emotional arc patterns, and CLI UX patterns. Load when transitioning from discovery to visualization or when designing journey artifacts.
npx skills add https://github.com/nWave-ai/nWave --skill nw-design-methodology
PHASE 1 PHASE 2 PHASE 3 PHASE 4
Journey Mapping Emotional Design TUI Prototyping Integration Check
| | | |
v v v v
"What's the flow?" "How should it feel?" "What does it look?" "Does it connect?"
schema_version: 1
journey:
name: "{Goal Name}"
goal: "{What user is trying to accomplish}"
persona: "{User persona reference}"
emotional_arc:
start: "{Initial emotional state}"
middle: "{Journey emotional state}"
end: "{Final emotional state}"
steps:
- id: 1
name: "{Step Name}"
command: "{CLI command or action}"
tui_mockup: |
+-- Step N: {Name} -----------------------------------------+
| {ASCII representation of CLI output} |
| ${variable} <-- tracked artifact |
+------------------------------------------------------------+
shared_artifacts:
- name: "{artifact_name}"
source: "{single source of truth file}"
displayed_as: "${variable}"
consumers: ["{list of places this appears}"]
emotional_state:
entry: "{How user feels entering step}"
exit: "{How user feels after step}"
integration_checkpoint: |
{What must be validated before proceeding}
failure_modes:
- "{What can go wrong at this step — used by DISTILL for error scenario generation}"
- "{Another failure scenario}"
gherkin: |
Scenario: {Step description}
Given {precondition}
When {action}
Then {observable outcome}
And shared artifact "${variable}" matches source
integration_validation:
shared_artifact_consistency:
- artifact: "{name}"
must_match_across: [1, 2, 3]
failure_message: "{Integration error description}"
changelog:
- date: "{YYYY-MM-DD}"
feature: "{feature-id}"
change: "{What changed in this update}"
Start: Anxious/Uncertain | Middle: Focused/Engaged | End: Confident/Satisfied
Use when: Complex multi-step operations
Start: Curious | Middle: Exploring | End: Delighted
Use when: Learning new features
Start: Frustrated | Middle: Hopeful | End: Relieved
Use when: Fixing issues or debugging
tool [noun] [verb] or tool [verb] [noun]crafter agent create or crafter create agentResponsive: print something in <100ms | Progress: show for long operations | Transparent: show what is happening | Recoverable: clear errors with suggested fixes
Implement --help on every command | Make help discoverable | Provide contextual suggestions
Three artifact types produced:
journey-{name}-visual.md): ASCII flow diagram with emotional annotations and TUI mockups per stepjourney-{name}.yaml): Machine-readable journey definition following schema abovejourney-{name}.feature): Testable acceptance scenarios from each journey stepAll artifacts go to docs/feature/{feature-id}/discuss/.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Take nwave-ai/nw-design-methodology 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.