data-analyst

Create formal measurement plans with event schemas, dashboards, guardrails, and data pipelines.

Updated Apr 4, 2026

Search Tags:#analytics #metrics #dashboard #instrumentation #data-pipeline #funnel #ab_test

Ready to run

npx skills add https://github.com/asalhamed/dev-agents --skill data-analyst-asalhamed

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analyst
Source: https://github.com/asalhamed/dev-agents/tree/main/data-analyst
Command: npx skills add https://github.com/asalhamed/dev-agents --skill data-analyst-asalhamed

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Define success metrics, analytics instrumentation, and data pipeline requirements for new features so teams can measure impact from day one.

Core Features & Use Cases

Define primary and secondary metrics for new features and identify guardrails.
Specify event schemas, data requirements, and instrumentation points for frontend and backend.
Produce measurement plans, dashboards, and data pipelines to guide product and engineering teams.

Quick Start

Draft a measurement plan for a hypothetical feature that outlines the objective, key metrics, events, and data pipelines to be emitted, collected, and analyzed.

Frequently Asked Questions about data-analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I define success metrics and guardrails for a new product feature?▼

To define success metrics and guardrails for a product feature, identify primary and secondary metrics that align with your objective. You then specify event schemas and instrumentation points to track these metrics across frontend and backend systems.

What is a measurement plan and what should it include for analytics instrumentation?▼

A measurement plan is a formal document detailing event schemas, dashboards, guardrails, and data pipelines for a feature. It includes success metrics, instrumentation points, and data requirements to guide engineering teams in collecting and analyzing impact data.

How do I create an analytics schema for frontend and backend data pipelines?▼

You create an analytics schema by specifying event schemas, data requirements, and instrumentation points across frontend and backend systems. This schema guides the data pipelines that emit, collect, and analyze events for your feature dashboards.

Can I use a measurement plan to guide A/B test instrumentation and funnel analysis?▼

Yes, a measurement plan defines the event schemas and data requirements needed to instrument A/B tests and analyze user funnels. It outlines the specific metrics, dashboards, and data pipelines required to measure feature impact from day one.

What's the best way to outline data pipeline requirements for product discovery and delivery?▼

The best way to outline data pipeline requirements is to produce a formal measurement plan integrated into product discovery and delivery workflows. This plan specifies event schemas, data requirements, and dashboards to guide both backend and frontend teams.

Do I need a formal measurement plan before engineering teams build feature dashboards?▼

Yes, you need a formal measurement plan before building dashboards to ensure data pipelines and event schemas are correctly specified. It provides the necessary instrumentation points and data requirements for frontend and backend implementation.