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review-data-source

Validate data source configurations for compliance and quality.

21.2k|8.6k|Updated Jan 26, 2013
Search Tags:#workflow#validation#compliance#review#connector#data source
One-click install
npx skills add https://github.com/elastic/kibana --skill review-data-source
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-data-source
Source: https://github.com/elastic/kibana/tree/main/x-pack/platform/plugins/shared/data_sources/.claude/skills/review-data-source
Command: npx skills add https://github.com/elastic/kibana --skill review-data-source

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the review process for data source configurations, ensuring accuracy, consistency, and adherence to best practices before deployment.

Core Features & Use Cases

  • Comprehensive Checklist: Guides users through critical checks for connector specs, workflows, data source definitions, documentation, and security.
  • Targeted Validation: Provides specific guidance for both standard and MCP-based data sources.
  • Use Case: When preparing a pull request for a new data source connector, use this Skill to systematically verify all aspects of the implementation against established standards, catching potential issues early.

Quick Start

Use the review-data-source skill to validate the changes in the current pull request.

Frequently Asked Questions about review-data-source

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate data source connector configurations before submitting a pull request?▼

Validating data source configurations requires checking connector specifications, workflows, and definitions against schema requirements, ID alignment, auth format, and security best practices to ensure compliance before deployment.

What is data source compliance review for connector workflows?▼

Data source compliance review is the process of verifying connector specifications, workflow parameter descriptions, and definitions to ensure they adhere to schema, ID alignment, auth format, and security best practices before deployment.

Does data source validation check both standard and MCP-based connector specifications?▼

Data source validation supports both standard and MCP-based data sources, applying specific compliance checks to connector specifications, workflows, and definitions to verify quality and adherence to established standards.

What security best practices should I check during data source configuration review?▼

During data source configuration review, verify adherence to security best practices by checking auth format, schema compliance, ID alignment, and workflow parameter descriptions across connector specifications and definitions.

How do I review post-creation data source definitions for quality and compliance?▼

Review post-creation data source definitions by validating connector specifications, workflows, and definitions against schema requirements, ID alignment, auth format, and security best practices to ensure ongoing compliance and quality.

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