What problem does it solve?
Building a reusable Holoscan Module involves many error-prone steps: choosing a layout, keeping naming identities consistent, scaffolding from templates, testing at honest scope, packaging DEB/WHEEL artifacts, and proving a clean consumer can actually install them. This Skill guides an AI agent through that entire producer-to-consumer lifecycle with the ./holohub CLI, enforcing preview-before-action safety and evidence-based verification.
Core Features & Use Cases
- Module Scaffolding: Create external self-contained holoscan-<name> repositories from modules/template or in-tree descriptors under modules/, with consistent module, operator, and package identities.
- Consumer & Packaging Proof: Declare immutable dependencies, iterate with mounted-source overrides or editable installs, build DEB/WHEEL packages, and validate each artifact in a clean artifact-only consumer.
- Safe Command Discipline: Preview every mutating ./holohub command with --dryrun, preserve checkout state, and route failures to the appropriate debug skill instead of guessing.
- Use Case: Ask your agent to create a Python Holoscan Module with one reusable operator, a finite demo, tests, and Debian and wheel packaging confirmed installable by a clean consumer.
Quick Start
Ask your agent to scaffold a new Python Holoscan Module from the HoloHub template, build and test it, then package it as a wheel and Debian package with clean-consumer proof.