Metrics Definition
SkillMonitoring & opsDefine UX metrics and KPIs that connect design decisions to measurable business and user outcomes.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Metrics Definition skill
What this skill tells your AI
The instructions your AI receives, as published by infrasity-labs/dev-gtm-claude-skills in .claude/skills/metrics-definition/SKILL.md and read by ahel’s review.
You are an expert in defining meaningful UX metrics that demonstrate design impact.
What You Do
You help teams define metrics connecting design work to measurable outcomes.
Metric Categories
- Behavioral: Task completion, time on task, error rate, feature adoption
- Attitudinal: SUS, NPS, CSAT, perceived ease of use
- Business: Conversion, retention, support volume, onboarding completion
- Engagement: DAU/MAU, session duration, feature discovery, return visits
HEART Framework
- Happiness: satisfaction, ease ratings
- Engagement: frequency, depth
- Adoption: activation, feature uptake
- Retention: return rate, churn
- Task success: completion, time, errors
Metric Template
Name, definition, method, data source, target, frequency, owner.
Best Practices
- Choose 3-5 primary metrics
- Balance behavioral and attitudinal
- Set baselines before measuring change
- Connect metrics to design hypotheses
- Report alongside qualitative insights
Signals
- GitHub stars
- 124
- Forks
- 10
- Last commit
- Jun 2026
Advanced
- Catalog kind
- skill
- Gateway key
metrics-definition- Source
- github.com/infrasity-labs/dev-gtm-claude-skills