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tinybird-python-sdk-guidelines

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.

68

Quality

81%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

80%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A token-efficient, well-structured index skill that points cleanly to one-level-deep rule files and gives executable CLI commands. Its main weakness is the absence of validation/feedback steps in the implied deploy workflow.

Suggestions

Add an explicit dev→build→deploy workflow with a validation checkpoint (e.g., verify the build succeeds and `tinybird preview` passes before `tinybird deploy`).

Inline one or two short executable examples for the most common task (e.g., defining a datasource or a pipe) so the body is actionable without immediately opening a rule file.

Note in the Quick Reference how to validate/rollback a deploy, given deploy targets production.

DimensionReasoningScore

Conciseness

Lean overview that assumes Claude's competence — no padding, no explanation of what Tinybird is, just triggers, a rule-file index, and copy-paste commands; every token earns its place.

5 / 5

Actionability

Provides concrete executable CLI commands in the Quick Reference, but the actual datasource/pipe coding guidance is delegated to rule files, so the common coding cases are not covered inline.

4 / 5

Workflow Clarity

An init→dev→build→deploy sequence is implied by the command list, but there are no validation checkpoints or feedback loops for the risky deploy step, capping the score at 3.

3 / 5

Progressive Disclosure

Clear overview with a well-signaled, one-level-deep 'Rule Files' index and inline Quick Reference; content is appropriately split and easy to navigate.

5 / 5

Total

17

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A clear, well-structured description that answers both what and when with concrete triggers. It is held back from a perfect score by minor coverage gaps in listed capabilities and a broad trailing trigger phrase that raises slight overlap risk.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions ('defining datasources, pipes, and queries'), but omits scope the body later reveals (endpoints, materialized views, connections, tokens), leaving minor coverage gaps.

4 / 5

Completeness

Explicitly states both what the SDK does ('for defining datasources, pipes, and queries in Python') and when to use it ('Use when working with tinybird-sdk, Python Tinybird projects, or data ingestion and queries in Python') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural trigger terms ('tinybird-sdk', 'Python Tinybird projects', 'data ingestion and queries in Python'), but lacks synonyms or variant phrasings users might say.

4 / 5

Distinctiveness Conflict Risk

The Tinybird niche is clearly distinct, but the trailing 'data ingestion and queries in Python' phrase is broad and could overlap with general Python data-tooling skills.

4 / 5

Total

17

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
MapleTechLabs/maple
Reviewed

Table of Contents

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