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Openrig Skills

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mvschwarz
openrig-skills

Use when you're operating OpenRig and need the right skill or context for fleet recovery, seat handover, new-seat orientation, a watchdog wake, cross-host reach to an agent on another machine, rig packaging, an OpenRig upgrade, systematic debugging, queue triage, or implementation planning; also use when you don't know what applies or nothing is projected on cold boot.

Overview

Publishermvschwarz
Repositoryopenrig
Skill nameopenrig-skills
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 Openrig Skills 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/assets/plugins/openrig-core/skills/openrig-skills
  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/assets/plugins/openrig-core/skills/openrig-skills .claude/skills/openrig-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openrig Skills 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 Openrig Skills 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 Openrig Skills 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.

OpenRig skills — the index (start here)

You're running inside OpenRig. OpenRig ships a set of skills — small documents that tell you when to do something and how. This file is the map: what ships, when to reach for each, and how to load it. If you don't know which skill applies, or nothing is projected into your context, start here.

How OpenRig context works (30 seconds)

Skills are progressive disclosure: a skill's name + description sit in your context ambiently (the "hot tier"); its body loads only when you open it. So you don't pre-read everything — you pattern-match a skill's "when" to your moment, then open just that one. This file is the index over the whole shipped set. (For bounded procedures, open agent-operated-workflows; for ongoing agent-backed applications, open agent-operated-software.)

Every row below names how to reach the skill — already-hot, or an exact load path. No row is a dead end.

Loading an entry on demand — rig context get

Don't guess a file path or a name. Go ask → ref → load in three steps:

  1. Discover — run rig context list for every shipped entry's ref and name. The when for each is the index below (or rig context list --json, which carries each entry's purpose) — match your moment there.
  2. Select — match your moment to a row's when and take its ref. Refs are canonical full paths that mirror the library layout — skills/<namespace>/<name> (e.g. skills/core/rig-lifecycle, skills/process/systematic-debugging). A unique bare name (e.g. watchdog) also resolves; any slash-bearing ref is an exact lookup and fails loud if it does not exist.
  3. Load — rig context get skills/<namespace>/<name>:
rig context get skills/core/rig-lifecycle

The router itself is available through both forms it teaches: rig context get openrig-skills and rig context get skills/core/openrig-skills.

The content is served from the installed CLI, so what you load always matches your running version — no path-guessing, no frozen-fork drift. (The daemon assembles the same bundle rig context preview shows an operator — get is the agent-facing pull.)

The index

Membership rule (layout.skills[*].edges.length > 0): every public skill with at least one product edge in the generated edge layout appears exactly once in this index; no other skill appears.

Always loaded — the universal spine (open its body when its moment hits)

These are auto-delivered to every rig; their name+description are already in your context. Open the body when the "when" matches.

  • forming-an-openrig-mental-model — first boot, or you're unsure how the pieces fit. The runtime mental model.
  • openrig-operating-model — you do not know where context or work belongs, or you are about to duplicate knowledge. The two-tree placement and trace-to-root model.
  • openrig-user — you need a rig CLI command (send / queue / ps / whoami / scope / broadcast). The daily CLI surface.
  • applying-a-permission-policy — a rig or seat has a permission policy attached, or you're setting one up: translate it into the live harness configuration.
  • claude-compaction-restore — you just compacted (Claude). Restore from durable evidence before resuming real work.
  • delegating-work — deciding who should do a task: you, a spawned subagent, or a durable peer seat that already holds the context.
  • loading-addressable-markdown — a task names Markdown as path#h2-slug or path#h2-slug/h3-slug outside the context-pack library.
  • session-compaction-and-restore — preparing for, or recovering from, compaction (any runtime). The write- and read-side protocol.
  • queue-handoff — you're passing durable work to another seat or ending your turn. The queue is the work ledger, not chat.
  • refocusing — a long-running seat may have lost the product outcome, crossed a major boundary, or compacted and needs a fresh path-based trace.
  • seat-continuity-and-handover — handing your seat's work across a restart or to another owner.
  • orienting-to-an-inherited-seat — you just inherited an existing seat through a planned handover and need to verify its identity, state, and testimony.
  • retiring-and-inheriting-a-seat — you're planning a seat transition and need to retire the current occupant into a fresh successor without losing continuity.
  • mission-slice-sop — you're working a mission/slice (the SDLC: intent → mini-requirements + proof contract → build → QA → proof). The operating manual.
  • messaging-the-human — composing a message to the human. Plain language, no insider jargon.
  • agent-operated-workflows — a bounded real-world procedure needs an agent to interpret state and operate exact tools, or you are deciding whether ordinary code should own the loop.
  • agent-operated-software — you are designing or operating an ongoing application whose live backend includes OpenRig agents.
  • software-for-agents — compatibility redirect for the former agent-operated-software name; remove in 0.6.0.
  • openrig-skills — this index (you're reading it). Always loaded; the entry point to everything below.

Load when your role or task calls for it (repo-shipped, profile-selected)

These ship in the OpenRig repo and reach a seat when its profile selects them. To use one, select it in your profile's uses.skills, or open it directly at packages/daemon/specs/agents/shared/skills/core/<skill>/SKILL.md.

  • openrig-software-factory — a user wants continuing reviewed work: manual/team, queue-only orchestration or an explicit Workflow; add one or two seats to the running starter when useful, with context, ownership, concurrency, spend and permission limits. Load rig context get skills/core/openrig-software-factory/SKILL.md.
  • openrig-architect — authoring a rig or topology (NOT for changing OpenRig itself — that's openrig-builder).
  • openrig-cmux — driving the cmux terminal provider.
  • openrig-herdr — opening/managing seat terminals via the default proof-gated provider.
  • agent-startup-and-context-ingestion — a seat is booting and ingesting its startup context.
  • topology-mutation-and-seat-management — adding, removing, renaming seats or otherwise mutating rig topology.
  • rig-lifecycle — rig up / down / pause / resume lifecycle operations.
  • rig-bundles-and-shareable-artifacts — packaging or installing a rig bundle / shareable artifact.
  • cross-host-rig-commands — reaching seats or queues on another host (--host).
  • openrig-upgrade — upgrading OpenRig or the daemon.
  • agent-starters — composing an agent's starter context / priming packs.
  • specification-system — authoring or reading AgentSpecs and rig specs.
  • human-in-the-loop — deciding when to involve the human vs. proceed on your own authority.
  • watchdog — monitoring or recovering a seat (health, restore, stuck state).
  • session-source-fork — forking a session's source/context.
  • context-engineering — designing context systems. Provisional and non-normative: current OpenRig skills, explicit rulings, and measured practice outrank it on any conflict.

Pod handbooks (load when you're in that pod):

  • orchestration-team — you're orchestrating a rig: dispatching, monitoring, keeping the loop moving.
  • development-team — you're on the dev pod: building and shipping product changes.
  • review-team — you're reviewing: fresh scrutiny, anti-slop, empirical verification.
  • oversight-team — you're in an oversight pod: monitor boundaries and route findings without taking over the work.

Product-management craft (load when shaping/reviewing work):

  • requirements-writer — turning intent into clear requirements.
  • plan-review — reviewing a plan before it's built.
  • exec-summary — writing a decision-ready summary for a human.
  • office-hours — running a structured advisory / decision session.
  • context-builder — assembling the context a task or seat needs.
  • backlog-capture — capturing and shaping backlog items.
  • ui-mockup — producing a UI mockup for a slice.

Vendored craft — load when you're coding (ships with upstream provenance)

General engineering skills OpenRig ships as vendored copies. Open when the task matches; they carry "modified by OpenRig" provenance.

  • test-driven-development — implementing a feature or bugfix: write the failing test first.
  • verification-before-completion — about to claim done / passing / fixed: run the check and read the output first.
  • systematic-debugging — debugging: find the root cause before the fix.
  • agent-browser — driving a browser (screenshot / screencast) from an agent.
  • frontend-design — designing frontend / UI.
  • dogfood — web-QA / dogfooding a shipped UI.

When OpenRig itself misbehaves

Run rig context get help: the one help guide for your installed version, from symptom to next step, known problems, and a useful report to the OpenRig team if you are still stuck. If rig won't run, read daemon/docs/reference/help.md inside the installed @openrig/cli package, or https://www.openrig.dev/help/agents (the same text).

Developing OpenRig itself

If you're changing OpenRig's own source in a clone of the openrig repository, use that repository's developing-openrig skill (in the checkout's .claude/skills/ or .agents/skills/). It maps the architecture, the areas where a small change has a large effect, and which tests to run before a pull request.

Need more than what ships here?

This index covers the shipped surface. Your project, rig or machine may add its own skills and routers. Check the skills your working directory loads before concluding that something doesn't exist.

Frequently asked questions

What does the Openrig Skills AI skill do?

Use when you're operating OpenRig and need the right skill or context for fleet recovery, seat handover, new-seat orientation, a watchdog wake, cross-host reach to an agent on another machine, rig packaging, an OpenRig upgrade, systematic debugging, queue triage, or implementation planning; also use when you don't know what applies or nothing is projected on cold boot.

Why use Openrig Skills on TypingMind?

Because you install it once and use it with any model. Openrig Skills 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 Openrig Skills in TypingMind?

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

Which AI models can use Openrig Skills?

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 Openrig Skills?

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

Is the Openrig Skills 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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