mcpField
A
analytics-event-taxonomy

analytics-event-taxonomy

github.com/sylphxaiData & databases153 installsUpdated today
Repository

About analytics-event-taxonomy

A skill for product and data teams designing analytics events around decisions rather than collecting noisy metrics. It produces an event taxonomy and validation plan, with attention to identity, lifecycle, and privacy.

Key features

  1. 01Identify decisions and lifecycle stages
  2. 02Define events, properties, and identity
  3. 03Set guardrail metrics and QA checks
  4. 04Remove vanity and duplicate events
  5. 05Produce taxonomy and validation plan

Use cases

  1. 01Plan instrumentation for a product funnel
  2. 02Align event tracking with product decisions
  3. 03Review analytics for privacy and duplication

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sylphxai/skills --skill analytics-event-taxonomy

After installing, type/analytics-event-taxonomyin Claude Code to confirm it loaded.

Bundled filesagents/openai.yamlreferences/analytics-event-taxonomy-patterns.md

Details

From the project README

Analytics Event Taxonomy

Use this skill to make product analytics answer decisions instead of generating noisy events.

Workflow

  1. Identify product decisions, lifecycle funnel, entities, identity model, and instrumentation surfaces.
  2. Read references/analytics-event-taxonomy-patterns.md.
  3. Define event names, properties, identity, lifecycle stages, guardrail metrics, and QA checks.
  4. Remove vanity or duplicate events.
  5. Produce event taxonomy and validation plan.

When not to use

  • Do not use for generic advice the base model already handles without this skill's specific artifact contract.

Guardrails

  • Do not track sensitive data without purpose and privacy review.
  • Do not create events without a decision they support.
  • Keep names stable, semantic, and versioned when necessary.

Output format

Decision questions:
Identity model:

Event taxonomy:
- <event_name>: trigger, properties, owner, decision supported

Funnels/cohorts:
- <funnel or cohort>

Quality checks:
- <check>

Comments

Markdown supported