pcb-library

Manage KiCad footprints with Python scripts for discovery, listing, and inspection.

2|Updated Feb 8, 2026
One-click install
npx skills add https://github.com/pjcau/esp32-emu-turbo --skill pcb-library
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pcb-library
Source: https://github.com/pjcau/esp32-emu-turbo/tree/main/.claude/skills/pcb-library
Command: npx skills add https://github.com/pjcau/esp32-emu-turbo --skill pcb-library

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Footprint library management for KiCad MCP tooling addresses the challenge of efficiently organizing, searching, inspecting, and validating footprints in custom libraries used during hardware design.

Core Features & Use Cases

  • Footprint search, listing, and detailed inspection of pad configurations and design attributes generated by the project's Python scripts.
  • Seamless integration with KiCad CLI and MCP tooling to streamline PCB design workflows.
  • Batch footprint generation and validation to accelerate prototyping and ensure consistency before fabrication.

Quick Start

Run the footprint management workflow to list all footprints or inspect a specific footprint using the provided Python scripts.

Frequently Asked Questions about pcb-library

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

FAQPage Schema
How do I automate KiCad footprint management for large custom libraries?

Automating KiCad footprint management involves using Python scripts to discover, list, and inspect footprints across large custom libraries, streamlining the organization and validation of PCB design data.

Can I inspect pad details and positions for specific KiCad footprints via scripting?

Yes, you can inspect pad details and positions for specific KiCad footprints by running dedicated Python scripts that extract and validate pad configurations from the footprint library data.

What is the best way to validate KiCad footprints before fabrication?

Validating KiCad footprints before fabrication is best achieved through batch generation and validation scripts that check pad configurations and design attributes, ensuring consistency across the library.

Does this footprint validation workflow require KiCad CLI integration?

Yes, the footprint validation workflow requires seamless integration with the KiCad CLI and MCP tooling to execute the Python scripts that generate and inspect footprint data.

Why use Python scripts for KiCad footprint discovery instead of manual inspection?

Using Python scripts for KiCad footprint discovery accelerates prototyping by automating the search and listing process, efficiently handling large footprint libraries that are tedious to inspect manually.