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bigquery-report

Inspect BigQuery datasets and execute SELECT queries with cost controls.

Updated Aug 23, 2026
Search Tags:#sql#data-analysis#bigquery#dataset#bq#data-security#ga4
One-click install
npx skills add https://github.com/takimoto-sketch/medica-agent --skill bigquery-report
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bigquery-report
Source: https://github.com/takimoto-sketch/medica-agent/tree/main/.claude/skills/bigquery-report
Command: npx skills add https://github.com/takimoto-sketch/medica-agent --skill bigquery-report

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes the manual, error-prone steps of exploring BigQuery datasets, building safe SQL, and controlling query cost so analysts can get actionable insights quickly without risking unexpected billing or out-of-scope data access.

Core Features & Use Cases

  • Dataset & Table Discovery: List projects, datasets, and tables to understand data surface area before querying.
  • Schema Inspection: Retrieve table schemas (including nested fields) to build correct SQL and avoid runtime errors.
  • SELECT-only SQL Execution with Guardrails: Construct and run read-only queries with project/dataset scope validation, secret detection, row and byte limits, and dry-run cost estimates.
  • Common Use Cases: GA4 export analysis (event trends, page views), e-commerce revenue and product ranking reports, ad-hoc trend and top-N aggregations.
  • Result Interpretation: Parse JSON output into a concise, actionable Japanese summary with trend insights, rankings, anomalies, and improvement suggestions.

Quick Start

Ask the agent to show datasets in project my-project and then summarize daily page_view counts from analytics.events for the past 7 days.

Frequently Asked Questions about bigquery-report

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

FAQPage Schema
How do I run safe SQL queries on BigQuery datasets without unexpected billing?▼

To run safe BigQuery queries without unexpected billing, you can enforce SELECT-only SQL validation with project and dataset scope restrictions. Use dry-run cost estimates and set max-bytes along with row and byte limits to control query execution costs.

How do I inspect BigQuery table schemas before running SQL queries?▼

To inspect BigQuery table schemas before running SQL queries, perform dataset and table discovery to list available projects and datasets. Retrieve table schemas, including nested fields, to build correct SQL and avoid runtime errors during data analysis.

Can I analyze GA4 export data in BigQuery to find daily page view trends?▼

Yes, you can analyze GA4 export data in BigQuery to find daily page view trends. Construct SELECT SQL queries to aggregate event trends from analytics tables, then parse the JSON output into a concise summary with trend insights and improvement suggestions.

What is the best way to explore an unfamiliar BigQuery dataset for ad hoc reporting?▼

The best way to explore an unfamiliar BigQuery dataset for ad hoc reporting is to list datasets and tables to understand the data surface area. Inspect schemas to build valid SQL, then execute read-only queries with row limits to surface actionable metrics safely.

How do I prevent out-of-scope data access when executing BigQuery data analysis?▼

To prevent out-of-scope data access during BigQuery data analysis, enforce project and dataset scope restrictions before executing queries. Apply SELECT-only SQL validation and secret detection to ensure only authorized data is queried within the defined boundaries.

Are there limitations on SQL execution for large BigQuery tables?▼

Yes, limitations on SQL execution for large BigQuery tables include strict SELECT-only query validation and secret detection. You must work within enforced row and byte limits, and use dry-run cost estimates with max-bytes options to prevent excessive data scanning.

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