ai intermediate

Jido.AI Skills Runtime Foundations

Real skill manifest loading, registry setup, prompt rendering, and builder-skill catalog walkthroughs with checked-in `SKILL.md` fixtures.

primary showcase ai l2 ai-tool-use skills runtime jido_ai

Related guides and notebooks

What you’ll learn

  • How Jido.AI.Skill.Loader.load/1 parses checked-in SKILL.md files into runtime manifests
  • How Jido.AI.Skill.Registry.load_from_paths/1 and Jido.AI.Skill.Registry.register/1 populate one deterministic registry
  • How Jido.AI.Skill.Prompt.render/2 turns those registered skills into reusable prompt instructions
  • Where the builder-skill catalog lives under priv/skills/builder-*/SKILL.md
  • How the same builder skills can support Jido.AI, jido_skill, and Codex-oriented contributor workflows
  • How one real workbench task for jido_skill is assembled from checked-in builder skills

How this demo stays truthful

This page runs real skills runtime code.

  • One skill is defined as an Elixir module with use Jido.AI.Skill.
  • Two skills are loaded from checked-in priv/skills/.../SKILL.md files.
  • Seven builder skills are loaded from checked-in priv/skills/builder-*/SKILL.md files.
  • The demo uses those builder skills to render a real contributor workflow for refreshing the jido_skill ecosystem package coverage in this repo.
  • The demo renders prompts and workflow plans only. It does not call external services or mutate package repos.

No API keys, LLM providers, or network access are required for this example.

Builder catalog included here

The checked-in builder catalog currently includes:

  • builder-action-scaffold
  • builder-agent-scaffold
  • builder-plugin-scaffold
  • builder-adapter-package
  • builder-ecosystem-page-author
  • builder-example-tutorial-author
  • builder-package-review

The catalog is intentionally split across package-repo and workbench-repo boundaries:

  • package repos own implementation modules, tests, changelog updates, and release work
  • this workbench owns ecosystem pages, examples, tutorials, and contributor-facing guidance

Pull the pattern into your own app

Keep the same runtime steps in your own project:

  • define stable module-backed skills for core workflows
  • add file-backed SKILL.md assets when you want editable runtime instructions
  • register those skills into the runtime registry
  • render the combined prompt text once your agent or workflow needs it
  • keep boundary notes inside the skill metadata so package-repo work and workbench follow-up stay explicit