Rig Bundles and Shareable Artifacts

SkillDev tools

Use when authoring or installing a rig bundle (packaged, shareable artifact that instantiates an opinionated OpenRig topology + workflow), reasoning about the bundle vs extension boundary, or auditing a bundle for portability. Covers the 4 failure modes that prevent bundles from working anywhere but the operator's machine, and the inspect-before-install discipline.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Rig Bundles and Shareable Artifacts skill

What this skill tells your AI

The instructions your AI receives, as published by mvschwarz/openrig in skills/_canonical/core/rig-bundles-and-shareable-artifacts/SKILL.md and read by ahel’s review.

A rig bundle is a packaged, shareable artifact that can instantiate an opinionated OpenRig topology and workflow. It may include:

  • rig specs
  • agent specs
  • workflow specs
  • startup files
  • skills or skill references
  • operating-mode declarations
  • proof expectations
  • supporting fragments

Shareable artifact is broader than bundle: specs, bundles, skills, workflows, and extensions can all be shared. A bundle is the packaged form for "load this topology and way of working."

Use this when

  • Authoring a bundle from a proven lab pattern
  • Installing a bundle (rig bundle install <path>)
  • Inspecting a bundle before install (rig bundle inspect <path>)
  • Reasoning about bundle vs extension boundary (bundle declares topology + workflow; extension adds behavior)
  • Auditing a bundle for portability — does it work on a clean OpenRig environment, or only the author's machine?

Don't use this when

  • The work is a one-off topology you won't reuse. Specs alone are sufficient.
  • The intent is to add runtime behavior (commands, views, dashboards). Use extension-and-user-workspace, not bundles.
  • You want to ship a workflow as a daemon feature. Bundle is the path before daemon promotion.

The bundle vs extension boundary (load-bearing)

ConceptDeclaresExample
BundleRig shape + workflow ("load this topology and way of working")A Velocity Team bundle
ExtensionBehavior added to user workspace/runtimeA custom command, view, or dashboard

Don't confuse them. A bundle is opinionated content; an extension is added behavior. Both can be shareable artifacts, but they're structurally distinct.

Failure modes (4)

  1. A bundle works only on the operator's machine because paths, providers, or credentials are implicit. Bundles must be self-describing for a clean OpenRig environment.
  2. A bundle includes too much local state and becomes a backup archive instead of a reusable artifact. Bundle is the intended shape, not the current state of one specific install.
  3. A bundle declares topology but omits proof expectations or workflow mode. Topology alone doesn't tell users what "working as advertised" means.
  4. Users cannot inspect what a bundle will create before installing it. rig bundle inspect must show what will be created without side effects.

Proof standard

Proof should:

  1. Install the bundle into a clean OpenRig environment
  2. Instantiate it
  3. Verify the expected seats and workflow mode
  4. Run a small smoke proof that the topology behaves as advertised

Bundle path → product

Bundles are how proven lab patterns become reusable product experiences:

local dogfood pattern
  → bundle (with manifest, parameterization, proof expectations)
  → installed by another user on clean OpenRig
  → opinionated workflow shipped without becoming a daemon feature
  → if dependable, graduate parts into core daemon

This is also how OpenRig can ship opinionated workflows without making every workflow a daemon feature.

See also

  • extension-and-user-workspace skill — sibling primitive for user-owned behavior added to runtime; bundle vs extension boundary
  • specification-system skill — rig specs / agent specs / workflow specs that bundles package
  • agent-starters skill — bundles can include or reference Agent Starters
  • composable-priming-packs skill — bundles can package priming packs
  • openrig-user skill — rig bundle create / inspect / install CLI surface

Signals

GitHub stars
67
Forks
12
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
rig-bundles-and-shareable-artifacts
Source
github.com/mvschwarz/openrig