funnel-query

name

funnel-query

description

Use when someone asks which events to join to see a funnel like signup → activation → paid, where the canonical user_id lives, how to count conversions between two product events, or why their event counts look inflated or don't match between steps. Reach for this whenever a question involves the raw event stream, joining events to users, deduping events, or measuring step-to-step conversion — especially before hand-writing SQL against the event tables, which almost always gets the user_id join wrong.

funnel-query

Overview

This skill answers "which events do I join, and on what key, to measure a funnel" and hands Claude a small Python library (scripts/events.py) for fetching events and composing funnels on the fly. The single most important fact it encodes: raw events do not carry the canonical user_id. They carry an anonymous_id. The canonical user_id lives in identity.users, and you must join through it or your funnel silently fragments one user into many.

The library is credentials-aware (it reads warehouse creds from the environment) and exposes composable primitives — fetch_events, join_on_canonical_user_id, funnel — so Claude writes a short script per question rather than reconstructing boilerplate each time.

When to Use

Use this skill when the request is to:

• Build a funnel across product events (e.g. signup_completed → workspace_activated → subscription_started).
• Figure out which event names map to a product step, and which table holds them.
• Measure step-to-step conversion or drop-off between two events.
• Resolve "my counts are inflated / don't add up / a user shows up twice" on the event stream.
• Attribute pre-login (anonymous) activity to the user who eventually signed up.