---
name: tryghost-tinybird
description: "Tinybird file formats, SQL rules, optimization patterns, and best practices for datasources, pipes, endpoints, and materialized views."
license: "MIT"
metadata:
  decimalai-skill-id: "41b1223c-093c-4018-b909-2d343fa4b3a7"
  decimalai-version-id: "ddd8b669-a79f-4112-86b2-652773ff5d33"
  decimalai-version: "1"
  decimalai-body-sha256: "d7051faa119373260287d2aa411a5d78959a4936cf9ff54e2ce3e0b4e25a82e6"
  decimalai-name: "tryghost/tinybird"
  decimalai-format: "1"
  decimalai-invocation: "model"
  decimalai-category: "data"
  decimalai-source: "https://app.decimal.ai/s/tryghost-tinybird@1/SKILL.md"
---
# Tinybird Best Practices

Guidance for Tinybird file formats, SQL rules, optimization patterns, and data modeling. Use this skill when creating or editing Tinybird datafiles.

## When to Apply

- Creating or updating Tinybird resources (.datasource, .pipe, .connection)
- Writing or optimizing SQL queries
- Designing endpoint schemas and data models
- Organizing project structure and data layers
- Working with materialized views or copy pipes
- Implementing deduplication patterns
- Reviewing or refactoring Tinybird project files

## Rule Files

- `rules/project-files.md`
- `rules/build-deploy.md`
- `rules/datasource-files.md`
- `rules/pipe-files.md`
- `rules/endpoint-files.md`
- `rules/materialized-files.md`
- `rules/materialized-join-prefilter.md`
- `rules/sink-files.md`
- `rules/copy-files.md`
- `rules/connection-files.md`
- `rules/sql.md`
- `rules/endpoint-optimization.md`
- `rules/tests.md`
- `rules/deduplication-patterns.md`

## Quick Reference

- Project local files are the source of truth.
- Build target comes from `tinybird.config.json` `dev_mode` (`local` or `branch`).
- `tb deploy` targets Tinybird Cloud production.
- Commands like `tb sql` and `tb logs` default to local unless `--cloud` or `--branch=<branch-name>` is set.
- SQL is SELECT-only with Tinybird templating rules and strict parameter handling.
- Use MergeTree by default; AggregatingMergeTree for materialized targets.
- Filter early, select only needed columns, push complex work later in the pipeline.