data-analyst

Connect to BigQuery and Snowflake for exploratory data analysis and visualizations.

345|12|Updated Apr 14, 2026

Search Tags:#visualization #data-analysis #bigquery #eda #snowflake #marimo

Ready to run

npx skills add https://github.com/minicoohei/ai-agent-camp --skill data-analyst-minicoohei

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analyst
Source: https://github.com/minicoohei/ai-agent-camp/tree/main/.claude/skills/data-analyst
Command: npx skills add https://github.com/minicoohei/ai-agent-camp --skill data-analyst-minicoohei

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Sub-Agents manage data analysis tasks by coordinating BigQuery/Snowflake connections, EDA, visualization, and Marimo notebook creation in a dedicated context, reducing context switching and ensuring consistent governance across analyses.

Core Features & Use Cases

Connect to BigQuery and Snowflake, run Exploratory Data Analysis, and generate visualizations within a contained environment.
Create and enforce four integrated rules (data_analysis, visualization, notebook, marimo_variable_naming) to standardize data workflows.
Use cases include BigQuery EDA workflows, time-series analyses, cohort analyses, and dashboard-style reporting.

Quick Start

Analyze a dataset by connecting to BigQuery/Snowflake, perform an EDA, generate visualizations, and create a Marimo notebook in the sub-agent.

Frequently Asked Questions about data-analyst

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

FAQPage Schema

How do I run exploratory data analysis on BigQuery?▼

Run exploratory data analysis on BigQuery by connecting to your dataset, executing queries within a sub-agent context, and generating visualizations. This process applies standardized rules for data analysis and notebook creation to return a concise summary with visuals.

Can I use Snowflake for time-series analysis and cohort analysis?▼

Yes, you can use Snowflake for time-series analysis and cohort analysis. The workflow connects to Snowflake to run exploratory data analysis, generates visualizations, and creates Marimo notebooks while enforcing standardized data workflows.

Do I need GCP authentication to connect to BigQuery for EDA?▼

Yes, GCP authentication is required to connect to BigQuery for exploratory data analysis. The workflow ensures end-to-end compliance with GCP authentication standards to securely access your datasets and generate visualizations.

What's the best way to standardize data visualization workflows in a notebook?▼

Standardize data visualization workflows by applying four integrated rules: data_analysis, visualization, notebook, and marimo_variable_naming. This ensures consistent governance across analyses and generates standardized Marimo notebooks within a contained sub-agent environment.

Does this approach support dashboard-style reporting with BigQuery and Snowflake?▼

Yes, this approach supports dashboard-style reporting with BigQuery and Snowflake. It coordinates database connections, performs exploratory data analysis, and generates visualizations to produce concise analysis summaries and dashboard reports within a dedicated sub-agent context.