Claude Skill

rig-bundles-and-shareable-artifacts

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

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Part of mvschwarz/openrig — 47 skills

Install

skills CLI npx skills add https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/core/rig-bundles-and-shareable-artifacts
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install mvschwarz-openrig@llmmart
Git git clone https://github.com/mvschwarz/openrig.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole mvschwarz/openrig collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Rig Bundles and Shareable Artifacts

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)

Concept Declares Example
Bundle Rig shape + workflow ("load this topology and way of working") A Velocity Team bundle
Extension Behavior added to user workspace/runtime A 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
Files (openrig)
  • SKILL.md 4.3 KB
    ---
    name: rig-bundles-and-shareable-artifacts
    description: 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.
    metadata:
      cli_surfaces_referenced:
        - bundle create
        - bundle inspect
        - bundle install
      openrig:
        stage: factory-approved
        sibling_skills:
          - rig-lifecycle
          - topology-mutation-and-seat-management
          - seat-scaling-and-specialization
          - cross-host-rig-commands
          - sidecar-operator
          - specification-system
          - extension-and-user-workspace
    ---
    
    # Rig Bundles and Shareable Artifacts
    
    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)
    
    | Concept | Declares | Example |
    |---|---|---|
    | **Bundle** | Rig shape + workflow ("load this topology and way of working") | A Velocity Team bundle |
    | **Extension** | Behavior added to user workspace/runtime | A 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
    

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