Agents Schema Analyst Bigquery

dbt-labs/agents_schema/examples/skills/agents-schema-analyst-bigquery

analysisOfficial

Official Provider SkillView repo

Use when answering a business data question (revenue, MRR, ARR, churn, customer or connector counts, etc.) against a BigQuery warehouse that has an AGENTS metadata schema. Triggers on questions like "what is our current MRR", "net revenue year-to-date", "how many active customers", or any ask for a governed metric instead of a guessed one.

Files1 files

SKILL.md1 lines

Loading editor…

Install

Recommended

One command — your agent picks it up automatically.

Select AI agent

Select an AI agent above to see the install command.

Manual Install

More steps

Download the file and paste it into your agent's system prompt.

Skill details

Versionv1.0.0

Authordbt Labs

Categoryanalysis

Skill IDdbt-labs/agents_schema/examples/skills/agents-schema-analyst-bigquery

Related skills

Agents Schema Analyst DatabricksUse when answering a business data question (revenue, MRR, ARR, churn, customer or connector counts, etc.) against a Databricks warehouse that has an AGENTS metadata schema. Triggers on questions like "what is our current MRR", "net revenue year-to-date", "how many active customers", or any ask for a governed metric instead of a guessed one.Agents Schema Analyst SnowflakeUse when answering a business data question (revenue, MRR, ARR, churn, customer or connector counts, etc.) against a Snowflake warehouse that has an AGENTS metadata schema. Triggers on questions like "what is our current MRR", "net revenue year-to-date", "how many active customers", or any ask for a governed metric instead of a guessed one.Answering Natural Language Questions With DbtWrites and executes SQL queries against the data warehouse using dbt's Semantic Layer or ad-hoc SQL to answer business questions. Use when a user asks about analytics, metrics, KPIs, or data (e.g., "What were total sales last quarter?", "Show me top customers by revenue"). NOT for validating, testing, or building dbt models during development.Migrating Dbt Project Across PlatformsUse when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.Troubleshooting Dbt Job ErrorsDiagnoses dbt Cloud/platform job failures by analyzing run logs, querying the Admin API, reviewing git history, and investigating data issues. Use when a dbt Cloud/platform job fails and you need to diagnose the root cause, especially when error messages are unclear or when intermittent failures occur. Do not use for local dbt development errors.Using Dbt For Analytics EngineeringBuilds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes.