Taavi — Metrics & Semantic Layer Engineer AI Skill
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Make one number the number: reconcile the conflicts, specify each metric, and serve it from a governed semantic layer.
- Metric specs: grain, filters, time dimensions, additivity
- Reconciliation ladders that close between conflicting numbers
- dbt Semantic Layer, MetricFlow and Cube implementation
- Metric versioning, deprecation and change control
Companies where finance, product and sales each have a different number for the same thing.A semantic layer engineer charges $120+/hr, this is one file, yours forever.
Drop Taavi into Claude and get a semantic layer engineer who reconciles the three conflicting revenue numbers first, then makes one definition the only one anybody can query.
Taavi owns the single definition of every business metric: semantic layer implementation across the dbt Semantic Layer and MetricFlow, Cube and AtScale; metric specification covering grain, filters, time dimensions, additivity and non-additive measures; dimensional consistency and slowly changing dimensions in metric context; metric versioning and deprecation; headless BI serving the same metric to every downstream tool; governance of who may change a definition; reconciling conflicting numbers between teams step by step until the ladder closes; query pushdown and caching; and the migration path from a pile of hardcoded dashboard SQL to governed metrics.
What you get
- →Metric specs: grain, filters, time dimensions, additivity
- →Reconciliation ladders that close between conflicting numbers
- →dbt Semantic Layer, MetricFlow and Cube implementation
- →Metric versioning, deprecation and change control
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Taavi builds the answer. Includes a full worked example so you see exactly what you get.
# Taavi - Metrics & Semantic Layer Engineer You are Taavi, a metrics and semantic layer engineer. You reconcile before you standardize, and you distinguish a genuine bug from two legitimate definitions that need different names. ## How you work 1. Inventory every query and group them by definitional fingerprint 2. Build a reconciliation ladder until the numbers close exactly 3. Write formal metric specs: grain, filters, time, additivity 4. Implement in the semantic layer with versioning and change control Never silently redefine a metric someone is reporting on; version and deprecate it in the open.
Excerpt from the actual file you'll download.
Four steps. Any AI chat.
- 01Download the file
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
- 02Open your AI chat
Claude, ChatGPT, Gemini, Grok, or Copilot — whichever one you already use.
- 03Paste the file contents
Drop it into the system prompt, Project instructions, or custom instructions field.
- 04Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required. No subscription. Pay once, keep forever.
Works with every major AI chat.
Drop the file into your AI's system prompt, Project instructions, or custom instructions. No setup. No code. No vendor lock-in.
- Claude
- ChatGPT
- Gemini
- Grok
- Copilot
Works with any AI chat that accepts a system prompt or custom instructions.
Ready to specialise your AI?
One drop-in file. Pay once, keep forever — works with Claude & ChatGPT.