tinybird

Overview of tinybird skill

What tinybird does

The tinybird skill helps you create and edit Tinybird project files with fewer SQL and modeling mistakes. It focuses on Tinybird file formats, SELECT-only SQL rules, endpoint definitions, datasources, materialized views, copy pipes, and optimization patterns. If you are working on Tinybird for Backend Development, this is the skill to use when you need the file shape and query behavior to be correct, not just syntactically plausible.

Who should use it

Use this tinybird skill if you are building analytics APIs, real-time pipelines, or data products in Tinybird and need a prompt that understands Tinybird’s file-based workflow. It is most useful for engineers who are creating or refactoring .datasource, .pipe, and .connection files, or who need help deciding whether logic belongs in a pipe, endpoint, MV, or copy flow.

What matters most

The main value is practical guardrails: project files are the source of truth, tinybird.config.json controls build targeting, and Tinybird SQL has stricter conventions than generic SQL. The skill is strongest when you want installation-ready guidance for repo structure, build/deploy flow, and optimization choices that affect endpoint performance and data freshness.

How to Use tinybird skill

Install and scope the skill

Use the repository install flow to add the skill, then point the agent at the Tinybird workspace you want to change. A typical tinybird install starts with:
npx skills add tinybirdco/tinybird-agent-skills --skill tinybird
For best results, tell the agent whether you are editing local files, a Cloud branch, or production-bound artifacts before asking for changes.

Give the skill the right input

The tinybird skill works best when your prompt includes the file type, goal, and operating target. Good inputs sound like: “Update this .pipe endpoint to reduce scan cost,” “Create a .datasource for this Kafka feed,” or “Refactor this Tinybird project to use a materialized view for the daily rollup.” Weak inputs like “optimize this” force guesswork and usually produce generic advice.

Read these files first

Start with SKILL.md, then inspect the rule files that match your task. High-value paths in this repo are:

• rules/build-deploy.md
• rules/project-files.md
• rules/datasource-files.md
• rules/pipe-files.md
• rules/endpoint-files.md
• rules/sql.md
• rules/endpoint-optimization.md
• rules/deduplication-patterns.md

Use the workflow Tinybird expects

The skill is designed around local project files, not ad hoc SQL snippets. In practice, you should identify the target file type, confirm whether dev_mode is local or branch, then validate the result against Tinybird’s build and deploy rules. For backend work, prefer prompts that specify input schema, freshness needs, and whether the output is an endpoint, datasource, or intermediate transform.

tinybird skill FAQ

Is this better than a normal prompt?

Yes, when the task touches Tinybird-specific file rules, build targets, or optimization constraints. A normal prompt may write acceptable SQL, but the tinybird skill helps enforce project conventions such as SELECT-only transformations, endpoint file placement, and the difference between tb build and tb deploy.

Can beginners use tinybird?

Yes, if they already know the business goal and can describe the source data. Beginners benefit most when they ask for one artifact at a time, such as a datasource, endpoint, or pipe. The skill is less useful if you want a broad Tinybird tutorial with no repo context.

When should I not use it?

Do not use the tinybird skill for unsupported connection types, vague platform-agnostic analytics design, or tasks that do not involve Tinybird file generation or refactoring. It is also the wrong choice if you need a pure cloud-ops answer without touching project files.

What is the main Tinybird fit?

Use it for Tinybird for Backend Development when you need fast, queryable APIs backed by well-formed project files. It is especially relevant when performance, schema correctness, and deploy safety matter more than writing a one-off query.

How to Improve tinybird skill

Give stronger constraints up front

The biggest quality jump comes from specifying data source, target file, and success criteria. For example: “Build an endpoint from this pipe with p95 under 100 ms,” “Use MergeTree and keep only these columns,” or “Refactor this datasource to support JSON paths and backfill safely.” These details help the tinybird skill choose the right file pattern instead of producing a generic transformation.

Share the repo context that changes the answer

Include tinybird.config.json, the relevant .pipe or .datasource file, and any rule file that already governs the area you are changing. If you are asking about deduplication, mention whether you need query-time dedupe, ReplacingMergeTree, or a snapshot/copy approach. That avoids the common failure mode where the output is correct in theory but wrong for your build target.

Review for common failure modes

Check whether the result accidentally uses SELECT *, chooses the wrong engine, or assumes production deployment when you only wanted a build. Also verify whether the endpoint should be optimized with materialization, filtering earlier, or smaller data types. These are the places where tinybird outputs usually need a second pass.

Iterate with a concrete next prompt

If the first answer is close, ask for one specific revision: “make it branch-safe,” “convert this to an endpoint file,” “remove unsupported connection settings,” or “rewrite for lower read bytes.” That style of iteration gives the tinybird skill a narrow correction target and usually produces a better final file than asking for a full rewrite.