| name | ux-writing |
| description | Voice, tone, and content guidelines for data/ML dashboards. Covers microcopy, error messages, success states, and data presentation language. Auto-invokes on copy, messaging, content, labels, error messages keywords. |
| allowed-tools | Read |
UX Writing (Core)
Voice
- Professional yet Accessible - Technical precision without jargon
- Educational - Explain complex concepts clearly
- Evidence-Based - Data-driven with context
- Progress-Oriented - Focus on forward momentum
Tone by Context
| Context | Tone | Example |
|---|
| Executive | Strategic, narrative | "ML models require quality data for production performance" |
| Analyst | Precise, data-rich | "Retention: discovery → silver dataset" |
| Error | Calm, solution-focused | "Unable to load metrics. Check connection and refresh." |
| Success | Confirming, brief | "Pipeline completed successfully." |
Microcopy Patterns
Buttons
- Primary: "View Dashboard" (not "Click to View")
- Secondary: "Learn More" (not "Read Documentation")
- Destructive: "Delete Dataset" (not just "Delete")
Errors
Structure: Problem + Solution
- "Unable to connect. Check URL and try again."
- "File exceeds 10MB. Compress or split."
Empty States
Structure: Explanation + Action
- "No datasets yet. Upload your first dataset to get started."
Loading
Be specific: "Loading dashboard..." not "Loading..."
Data Presentation
Numbers
- Use commas: 1,234,567
- One decimal for %: 45.2%
- Context: "1,234 records (+12% from last month)"
Trends
- Positive: "+12.5%" or "↑ 450 records"
- Negative: "-8.2%" or "↓ 120 records"
Accessibility
Alt Text
Describe: "Bar chart showing training data distribution"
Not: "Image of chart"
Links
Specific: "View dataset documentation"
Not: "Click here"
Preferred Terms
| Use | Avoid |
|---|
| Dataset | Data set |
| Pipeline | ETL process |
| Real-time | Realtime |
| Training data | Train data |
Version: 2.0.0
