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Cross Host Rig Commands

CommunityPopular
mvschwarz
cross-host-rig-commands

Use when addressing a registered remote OpenRig host, choosing its transport, or interpreting a cross-host result.

Overview

Publishermvschwarz
Repositoryopenrig
Skill namecross-host-rig-commands
Stars
5K
Forks
366
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mvschwarz on GitHub. Read the source before you install it.

Installation

Install the Cross Host Rig Commands AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/mvschwarz/openrig/tree/main/packages/daemon/specs/agents/shared/skills/core/cross-host-rig-commands
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mvschwarz/openrig.git /tmp/openrig
mkdir -p .claude/skills
cp -r /tmp/openrig/packages/daemon/specs/agents/shared/skills/core/cross-host-rig-commands .claude/skills/cross-host-rig-commands
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cross Host Rig Commands in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cross Host Rig Commands on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cross Host Rig Commands is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cross-host rig commands

Use a registered host address and the entry's declared transport. SSH entries run a remote CLI through a single-hop shell; HTTP entries use the remote daemon. These paths have different prerequisites and command coverage. Check the exact command's help and the target installation before a consequential operation.

Choose and inspect the destination

rig host list shows registered hosts. rig host add --help describes registry writes; rig host doctor --help describes reachability checks. Inspect the configured OpenRig home rather than assuming the default ~/.openrig/hosts.yaml. Registry changes affect later routing, so make them within the requested scope.

yaml
hosts:
  - id: test-vm
    transport: ssh
    target: test-vm.local
    user: example-user
  - id: remote-dev
    transport: http
    url: http://remote-dev.example:7433
    bearer_env: REMOTE_RIG_TOKEN

The registry requires a hosts array, unique non-empty ids and a supported transport. SSH needs a non-empty target; user and notes are optional. HTTP needs a URL and accepts at most one of bearer_env or bearer_file. Omitting both is valid for a tokenless target. A configured but unavailable bearer is a permission failure, not anonymous fallback. Host ids also have reserved-name validation; use the actual validator's error rather than inventing an alias that collides.

Address the intended operation

bash
rig send dev-worker@example-rig "check the assigned result" --host remote-dev --verify
rig capture dev-worker@example-rig --host remote-dev
rig ps --host remote-dev --nodes --json
rig whoami --host remote-dev

These coordination commands select SSH or HTTP from the registry entry. They do not silently try another transport when one fails. A host-qualified target can be convenient, but confirm its parsing and any persisted host selection with the particular command. Explicit --host is preferable for consequential cross-host work.

Queue destinations use explicit --host or a supported host-qualified destination; queue writes do not follow persisted host selection. The CLI separates the host from the canonical seat in the routing envelope. Different queue subcommands have different flags: check their help instead of copying a flag from send. A local success message alone does not establish remote persistence or pickup.

Read failures at the layer that failed

SignalWhat to inspect
registry-load-failed / unknown-hostRegistry path, entry and exact destination
ssh-unreachableSSH connection, target and transport diagnostics
permission-gateThe configured SSH or HTTP credentials and target policy
remote-daemon-unreachableTarget listener and actual running daemon identity
remote-command-not-foundRemote CLI installation and executable lookup
remote-command-failedThe remote operation's own status and error

The exact result taxonomy depends on the path. HTTP failures expose the remote status/error; SSH distinguishes the shell transport from the remote command. Do not start or replace a remote daemon merely because a diagnostic suggests it; first establish the target's state and the authority for that lifecycle action. A timed-out write may have reached its destination. Reconcile its durable effect before retrying.

Verification and attribution

Transport success is not delivery verification or agent consumption. SSH forwards --verify and returns the remote CLI result. HTTP preserves the remote transport verdict and explicitly reports that the local pane-effect check did not run cross-host. Inspect that result and the destination effect required by the task; never replace it with “SSH exited zero” or “HTTP returned successfully.”

Cross-host output names the host/target; JSON envelopes carry cross_host metadata. The precise envelope differs by command and transport. Preserve the underlying remote result when passing evidence onward.

A target's host suffix selects a destination; a sender's origin identifies where a reply belongs. Use the rendered reply address and verify its host mapping. Current send derives the sender from the executing seat context, not a caller's --from assertion. It adds origin-host identity at cross-host forwarding; do not assume local sends have the same suffix. Unknown identity remains unknown.

This guide describes the implemented command paths, not proof of a live remote journey on your installation. Forks, handovers and other lifecycle compositions need their own supported command and scoped authority; reading remote state does not authorize them.

See also

  • openrig-user — exact command reference
  • seat-continuity-and-handover — stable seat and occupant outcomes

Frequently asked questions

What does the Cross Host Rig Commands AI skill do?

Use when addressing a registered remote OpenRig host, choosing its transport, or interpreting a cross-host result.

Why use Cross Host Rig Commands on TypingMind?

Because you install it once and use it with any model. Cross Host Rig Commands is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cross Host Rig Commands in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mvschwarz/openrig/tree/main/packages/daemon/specs/agents/shared/skills/core/cross-host-rig-commands. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cross Host Rig Commands?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cross Host Rig Commands?

As many as you like. As long as a model supports skills, you can use Cross Host Rig Commands with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cross Host Rig Commands AI skill free?

Yes. It is published on GitHub by mvschwarz under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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