data-analyst

Analyze organizational metrics to generate a RO-PNA confidence score across contributors.

17|1|Updated Feb 3, 2026
One-click install
npx skills add https://github.com/Adelie-Squad/solosquad --skill data-analyst-adelie-squad
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: data-analyst
Source: https://github.com/Adelie-Squad/solosquad/tree/main/agents/specialists/data-analyst
Command: npx skills add https://github.com/Adelie-Squad/solosquad --skill data-analyst-adelie-squad

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Data-driven decision making is often hampered by fragmented metrics and opaque confidence signals. This skill provides a RO-PNA-based confidence score, per-contributor breakdown, and shipping streak insights to clarify where metrics stand and how teams should act.

Core Features & Use Cases

  • Define metrics and track KPIs across product, engineering, and marketing.
  • Analyze experiments (A/B tests), cohorts, and retention to compute a RO-PNA confidence score.
  • Provide per-contributor shipping streak (gstack) to monitor momentum and delivery cadence.
  • Leverage amplitude-pattern-inspired automation to surface actionable recommendations.

Quick Start

Ask the Chief to run a metrics analysis for a new KPI and generate a RO-PNA confidence score with contributor breakdown.

Frequently Asked Questions about data-analyst

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

FAQPage Schema
How do I calculate a confidence score for A/B test analysis?

A/B test analysis uses a RO-PNA-based confidence score to evaluate experiment significance and provide actionable metric recommendations. It calculates significance checks across product, engineering, and marketing teams to clarify where metrics stand.

What is a RO-PNA confidence score in metrics tracking?

A RO-PNA confidence score is a structured metric calculation method used to evaluate organizational KPIs and cohorts. It surfaces opaque confidence signals to clarify metric performance and indicate how teams should act on the data.

How do I track cohort retention and North Star metrics across teams?

Cohort retention and North Star metrics are tracked by analyzing organizational data to generate a RO-PNA confidence score. This approach monitors momentum and delivery cadence across product, engineering, and marketing teams.

Can I use Amplitude-inspired automation for KPI monitoring and contributor breakdowns?

Yes, Amplitude-pattern-inspired automation is implemented to monitor KPIs and generate per-contributor breakdowns. This surfaces actionable recommendations and tracks a per-contributor shipping streak to measure delivery momentum.

What is the best way to analyze fragmented metrics and per-contributor shipping streaks?

Analyzing fragmented metrics involves generating a RO-PNA confidence score with a per-contributor shipping streak breakdown. This method clarifies where metrics stand and monitors team delivery cadence to drive data-driven decisions.

Does this metric analysis approach work for product, engineering, and marketing teams?

Yes, metric definition, A/B test analysis, and North Star monitoring are applicable across product, engineering, and marketing teams. It provides structured significance checks and per-contributor shipping streaks for all these groups.