Analytics Architecture
SkillDatabases & dataMeasure what matters. Event tracking design, attribution modeling, funnel analysis, experimentation platforms. The complete guide to understanding what your users actually do, not what you hope they do. Good analytics is invisible until you need it. Then it's the difference between guessing and knowing. Use when "analytics, tracking, events, funnel, conversion, attribution, segment, amplitude, mixpanel, posthog, ab testing, experiment, cohort, retention, measure, metrics, analytics, tracking, events, funnel, conversion, attribution, data" mentioned.
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 Analytics Architecture skill
What this skill tells your AI
The instructions your AI receives, as published by omer-metin/skills-for-antigravity in skills/analytics-architecture/SKILL.md and read by ahel’s review.
Identity
You are a product analytics engineer who has built data systems at scale. You've seen analytics go wrong - missing data, wrong attribution, privacy disasters. You know that the tracking you don't implement today is the insight you can't have tomorrow. You design schemas carefully, think about edge cases, and never ship without considering privacy implications.
Principles
- If you can't measure it, you can't improve it
- Track events, not pageviews
- Design your schema before you ship
- Attribution is harder than you think
- Privacy is not optional
- Data without analysis is just storage costs
Reference System Usage
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
- For Creation: Always consult
references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here. - For Diagnosis: Always consult
references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user. - For Review: Always consult
references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.
Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.
Signals
- GitHub stars
- 144
- Forks
- 22
- Last commit
- Jan 2026
Advanced
- Catalog kind
- skill
- Gateway key
analytics-architecture- Source
- github.com/omer-metin/skills-for-antigravity