By tinybirdco
Build and manage Tinybird real-time analytics resources—datasources, pipes, endpoints, materialized views—directly from Claude Code, including CLI workflows, SQL optimization, and SDK integration for Python and TypeScript.
Tinybird file formats, SQL rules, optimization patterns, and best practices for datasources, pipes, endpoints, and materialized views.
Tinybird CLI commands, workflows, and operations. Use when running tb commands, managing local development, deploying, or working with data operations.
Tinybird Python SDK for defining datasources, pipes, and queries in Python. Use when working with tinybird-sdk, Python Tinybird projects, or data ingestion and queries in Python.
Tinybird TypeScript SDK for defining datasources, pipes, and queries with full type inference. Use when working with @tinybirdco/sdk, TypeScript Tinybird projects, or type-safe data ingestion and queries.
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimnpx claudepluginhub joshuarweaver/cascade-data-analytics --plugin tinybirdco-tinybird-agent-skillsBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
A collection of skills for AI coding agents. Skills are packaged instructions that extend agent capabilities for working with Tinybird.
Skills follow the Agent Skills format.
Install with
npx skills add tinybirdco/tinybird-agent-skills
Update with
npx skills update
Use these for day-to-day Tinybird project work. They are safe defaults to keep enabled.
Tinybird project guidelines from Tinybird Engineering. Contains 18 rule files covering datasources, pipes, endpoints, SQL, deployments, and testing.
Use when:
Categories covered:
Use these when operating Tinybird with the CLI (local dev, deployments, data ops) and the datafile (.pipe, .connection, .datasource) format
Tinybird CLI commands, workflows, and operations. Use when running tb commands, managing local development, deploying, or working with data operations.
Use when:
tb commandUse these when working with the @tinybirdco/sdk package and type-safe projects.
Tinybird TypeScript SDK for defining datasources, pipes, and queries with full type inference. Use when working with @tinybirdco/sdk, TypeScript Tinybird projects, or type-safe data ingestion and queries.
Use when:
Use these when working with the tinybird-sdk package and Python projects.
Tinybird Python SDK for defining datasources, pipes, and queries in Python. Use when working with tinybird-sdk, Python Tinybird projects, or data ingestion and queries in Python.
Use when:
Skills are automatically available once installed. The agent will use them when relevant tasks are detected. You can use the agent cli to check, e.g., amp skill list, or directly ask the agent to tell you what skills are available.
Recommended defaults:
tinybird-best-practices for general Tinybird project work.tinybird-cli-guidelines whenever you plan to run tb commands.tinybird-typescript-sdk-guidelines for TypeScript SDK projects.tinybird-python-sdk-guidelines for Python SDK projects.Examples:
Each skill contains:
SKILL.md - Instructions for the agentrules/ - Individual guidance filesMotherDuck skills for connecting, exploring live schemas, writing DuckDB SQL, using the REST API, and building dashboards, Dives, pipelines, and analytics apps.
Treasure Studio-specific skills including workspace document management, skill creation, scheduled task management, and UI rendering formats for grid dashboards and action reports
Editorial "Data & Analytics" bundle for Claude Code from Antigravity Awesome Skills.
Quick insights from dlt pipeline data. Connect to a pipeline, profile tables, plan charts, and assemble marimo dashboards.
Data engineering and time series analysis mastery. Expert in jq, SQL, pandas, time series forecasting, ETL pipelines, streaming, and analytics visualization.
ETL pipeline construction, data warehouse design, batch processing workflows, and data-driven feature development