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metadata-extractor

metadata-extractor

Process metadata extractor operations. Auto-activating skill for Data Pipelines. Triggers on: metadata extractor, metadata extractor Part of the Data Pipelines skill category. Use when working with metadata extractor functionality. Trigger with phrases like "metadata extractor", "metadata extractor", "metadata".

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: "metadata-extractor" description: | Process metadata extractor operations. Auto-activating skill for Data Pipelines. Triggers on: metadata extractor, metadata extractor Part of the Data Pipelines skill category. Use when working with metadata extractor functionality. Trigger with phrases like "metadata extractor", "metadata extractor", "metadata". allowed-tools: "Read, Write, Edit, Bash(cmd:*), Grep" version: 1.0.0 license: MIT author: "Jeremy Longshore jeremy@intentsolutions.io"

Metadata Extractor

Overview

This skill provides automated assistance for metadata extractor tasks within the Data Pipelines domain.

When to Use

This skill activates automatically when you:

  • Mention "metadata extractor" in your request
  • Ask about metadata extractor patterns or best practices
  • Need help with data pipeline skills covering etl, data transformation, workflow orchestration, and streaming data processing.

Instructions

  1. Provides step-by-step guidance for metadata extractor
  2. Follows industry best practices and patterns
  3. Generates production-ready code and configurations
  4. Validates outputs against common standards

Examples

Example: Basic Usage Request: "Help me with metadata extractor" Result: Provides step-by-step guidance and generates appropriate configurations

Prerequisites

  • Relevant development environment configured
  • Access to necessary tools and services
  • Basic understanding of data pipelines concepts

Output

  • Generated configurations and code
  • Best practice recommendations
  • Validation results

Error Handling

ErrorCauseSolution
Configuration invalidMissing required fieldsCheck documentation for required parameters
Tool not foundDependency not installedInstall required tools per prerequisites
Permission deniedInsufficient accessVerify credentials and permissions

Resources

  • Official documentation for related tools
  • Best practices guides
  • Community examples and tutorials

Related Skills

Part of the Data Pipelines skill category. Tags: etl, airflow, spark, streaming, data-engineering

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