Agent skill

OpenRig Software Factory

by mvschwarz in mvschwarz/openrig

Helps set up a continuing agent software team for a real repository with OpenRig, choosing between manual work, queue handoffs and an explicit Workflow.

Apache-2.0Auto-check passedAgent Workflows

Install OpenRig Software Factory

skills CLI
$ npx skills add mvschwarz/openrig --skill openrig-software-factory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mvschwarz/openrig openrig-software-factory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mvschwarz/openrig.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/_canonical/core/openrig-software-factory .claude/skills/openrig-software-factory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
openrig-software-factory
GitHub stars
5.9k
Token cost
~2.6k tokens
SKILL.md length
1,327 words
Files
2 (incl. references)
Skills in repo
49
Repo updated
First seen
Licence
Apache-2.0

At a glance

Helps set up a continuing agent software team for a real repository with OpenRig, choosing between manual work, queue handoffs and an explicit Workflow.

  • Works in 3 steps: Use the two-agent starter. Keep its… → Add one or two seats to the running rig.… → Author a custom rig when you want a…
  • Setting up a continuing agent team for a real repository
  • SKILL.md covers Choose how the team works, Choose the first team and its…, Establish the working agreement and Grow your factory, plus 2 more sections
  • Calls npm, claude and codex

What it does

The guiding idea is to start with a useful repository outcome and add coordination only when it earns its cost; a beginner can finish reviewed work without Workflow. A table offers three ways to work. Manual team work gives an owner the outcome and obtains an independent check. Queue-supported orchestration uses rig queue create, claiming and rig queue handoff to pass a candidate and evidence to the next owner, recording real blockers. Workflow, via rig workflow compile and instantiate-lifecycle, adds an explicit dependency graph. A roadmap, YAML file or wake does not execute work by itself.

For the first team, the agent asks what you want to build and which accounts you have, Claude Code, Codex or both. It then recommends starter (a Claude builder and a Codex reviewer for one bounded change), workshop (a lead, builder, QA and reviewer, installed as a rig bundle) or factory (seven agents for sustained product work). If you lack a provider, it adapts a copy of the team under the same name, checks only the logins the team needs, and avoids copying credentials or silently switching models. A worked example and getting-started guide are referenced; the excerpt is cut off there.

When your agent uses it

  • Setting up a continuing agent team for a real repository
  • Choosing between the starter, workshop and factory teams
  • Handing work between agents with a queue and evidence
  • Deciding when a project actually needs an explicit Workflow

Example prompts

  • “Set up an OpenRig team for this repo; I have both Claude Code and Codex.”
  • “Hand this change to the reviewer using the rig queue.”
  • “Do we need a Workflow for this project, or is queue handoff enough?”

Requirements

  • OpenRig and its rig CLI
  • A Claude Code or Codex login for the chosen team

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Use the two-agent starter. Keep its builder (the owner) and independent
  2. Add one or two seats to the running rig. This is the usual next step.
  3. Author a custom rig when you want a different structure. Read

What it can do on your machine

Read from SKILL.md and the folder at commit 1f69831. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm
    • claude
    • codex

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

OpenRig Software Factory loads about 2.6k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 47 tokens; SKILL.md has 1,327 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mvschwarz/openrig at commit 1f69831, republished under its Apache-2.0 licence (© mvschwarz). 1,327 words, ~2,629 tokens.

Download SKILL.mdSave it as .claude/skills/openrig-software-factory/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
openrig-software-factory
description
Use when a user wants a continuing software team for a real repository, or has a first OpenRig team and needs a repeatable path for reviewed work and later tasks.
metadata.cli_surfaces_referenced
context get, context list, context show, grow, queue create, queue handoff, workflow compile, workflow instantiate-lifecycle

OpenRig Software Factory

Start with a useful repository outcome and add coordination when it earns its cost. A beginner can complete reviewed work without Workflow. These are choices using existing capabilities, not stages everyone must graduate through.

Choose how the team works

NeedStart hereAdd more when…
One change, close human guidanceManual/team work: give an owner the outcome, use repository instructions, implement and obtain the chosen independent check.Work must survive turns or move between seats.
Continuing work with visible ownershipQueue-supported orchestration: use rig queue create, claim work, then rig queue handoff with the candidate/evidence to the next owner. Record real blockers and the continuation. No Workflow instance is needed.Repeated steps need an explicit dependency graph and permitted exits.
An explicit execution contractWorkflow: inspect rig workflow compile, then deliberately use rig workflow instantiate-lifecycle. Advance its packets through the workflow projection mechanism.The actual project needs reusable profiles, additional roles or gates.

For the concrete queue loop, wake behavior and optional two-slice Workflow, read references/worked-example.md. Installed copy: rig context get skills/core/openrig-software-factory/references/worked-example.md. A roadmap, YAML file or wake does not execute work or authorize a new outcome.

Choose the first team and its providers

Ask what the user wants to build and which working account(s) they have: Claude Code, Codex, or both. Recommend one of three teams: starter (a Claude builder and a Codex reviewer, for one bounded change), workshop (a lead, a builder, QA and a reviewer; a rig bundle installed from its pinned listing) or factory (seven agents for sustained product work). When the user lacks a provider a team needs, write an adapted copy of the team under the same name, as the kernel operator's guidance describes; never offer per-provider variants. first-project is starter's old name. Check only the CLIs/logins the team needs; request claude auth login or codex login once when that selected login is missing. No credential copying, unused provider prerequisite or silent model/provider fallback.

Read the compatible getting-started guide's Choose your providers and Start the kernel and check its state sections before launch. The choice selects the two project agents. Kernel auto-boot independently uses available authenticated accounts, so it may use both even when the project uses one. Do not add an unused-provider login gate or manual kernel setup to this path. An instance-wide provider restriction is a separate request. Preserve an existing kernel and working user rigs.

Show the chosen team, resolved runtimes/models and exact rig up <team> --cwd . --plan / rig up <team> --cwd . commands. Codex seats retain gpt-6-astra; Claude seats use the configured native default without an OpenRig model override. Confirm that model with the user and its availability; verify the native session's actual model before consequential work. Use the chosen rig name in owner/checker addresses (in the starter, dev-build@<rig> and dev-review@<rig>) throughout the same task and return.

Establish the working agreement

Read the repository instructions, current work and desired user-visible result. Verify the intended instance, code/work roots, real seat addresses and native readiness. Reuse a suitable small team; an existing agent can bootstrap it. A kernel operator is optional and is not automatically the project owner.

Agree the work boundary, time/spend limit, who answers unresolved choices, and when to stop: checked result, no authorized next work, exhausted budget, or a real user/permission/provider blocker. Background daemon checks are not themselves model turns, but delivered wakes and resumed work can spend tokens. Prefer an event-driven wait to frequent empty reminders. Wakes cannot answer a user question, clear a permission prompt or guarantee progress.

Ask once before launching or assigning work. For a team with no permission policy, seat choice or named Codex profile, recommend keeping the team default: Claude team seats run ordinary rig commands, project reads and common tests without prompts, and lifecycle commands such as rig up and rig down still ask. Only if they want more, offer: “Remember these selected OpenRig commands in your native settings for this project?” Yes / No — keep the team default. Reuse an existing explicit choice for this scope. Explain that a remembered allowance can cover all rig verbs, but Claude team seats still ask before lifecycle commands, at personal project scope unless the user explicitly chooses user-wide sessions. It is not global YOLO or permission to invent work. On an actual Yes, follow Applying a permission policy to add existing native rules, preserve stricter/unrelated settings, and verify the target conversation. No or no answer leaves settings alone and keeps the team default. Remember the explicit choice and exact additions in the existing onboarding context; “Undo the OpenRig command allowances added by this setup” removes only those additions. Broader access remains a separate opt-in.

Keep purpose, acceptance, decisions and evidence in existing project files. Deliver selected context and obtain each seat's scope reaction; retrieval alone is not peer delivery. The owner carries the candidate through the chosen check and bounded repairs, reports how to try it, and retains the next authorized task or explicitly reports none. Preserve work and custody before a supported stop.

Show full SKILL.md (496 more words)Show less

Grow your factory

Choose the team size separately from the coordination method above:

  1. Use the two-agent starter. Keep its builder (the owner) and independent reviewer (the checker) while that pair meets the workload. The builder can implement and coordinate.
  2. Add one or two seats to the running rig. This is the usual next step. Follow Grow the running team for rig grow commands, readiness/context/work assignment, and saving the expanded topology. Existing sessions need no rebuild or down/up cycle solely to add capacity.
  3. Author a custom rig when you want a different structure. Read OpenRig Architect, available through rig context get skills/core/openrig-architect/SKILL.md. Request: “Design a user-owned rig for [outcome] using the compatible RigSpec/AgentSpec guidance. Reuse suitable agents, define responsibilities and context, and validate the files. Preserve the existing rig and agree any new launch.”

As independent work grows, the original owner can concentrate on orchestration, multiple builders can implement separate outcomes, and the checker can retain independent review capacity. Record that division explicitly; adding seats does not assign work, change permissions or create parallelism. Agree file/worktree boundaries and integration ownership, follow the project's existing review policy, and keep active concurrency within the user's time/spend budget. Two seats are an entry point, not a finished factory or a maximum.

Read compatible guidance

Before installation, use this file and companion at the same published tag or commit as the selected package. After installation:

sh
rig --version
rig context list --json
rig context show skills/core/openrig-software-factory --json
rig context get skills/core/openrig-software-factory/SKILL.md

Compare build identity as well as version. Preserve missing, unreadable or older recipe results; do not silently substitute newer main or skip a missing companion.

Find the compatible permission guide

Retrieve the maintained procedure with rig context get skills/applying-a-permission-policy/SKILL.md. For source or archive readers, locate it below; the companion getting-started guide contains optional broader launch-mode recipes under Opt-in permissive operation. These paths are relative to the named root, not this skill:

Reading fromProcedure and guide, at the same version as this recipe
Source checkout, including skills/_canonicalBelow the repository root: packages/daemon/assets/plugins/openrig-core/skills/applying-a-permission-policy/SKILL.md and docs/reference/getting-started.md.
npm installationBelow the matching npm root -g or local npm root: @openrig/cli/daemon/assets/plugins/openrig-core/skills/applying-a-permission-policy/SKILL.md and @openrig/cli/daemon/docs/reference/getting-started.md.
Unpacked npm archiveBelow the extraction directory: package/daemon/assets/plugins/openrig-core/skills/applying-a-permission-policy/SKILL.md and package/daemon/docs/reference/getting-started.md.

For installed guidance, use the npm installation that supplies the selected rig executable; another prefix or local project can contain a different version. If the matching guide or section is missing, report the gap before proceeding; do not substitute current main or guidance from another installation.

Request to give your agent

Help me achieve [observable change] in this repository. Read the compatible Software Factory recipe, choose the lightest useful team/queue/Workflow path, and keep the next owner visible. Preserve existing files and permissions. Agree time/spend limits, perform the authorized work and chosen independent check, and ask only about unresolved decisions or effects outside that scope. Keep publication and destructive changes out of this task.

When commands, defaults or permission semantics change, check this source and companion together and regenerate their existing projections. Website guidance should link to the same versioned recipe, not maintain another procedure.

© mvschwarz, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/_canonical/core/openrig-software-factory of mvschwarz/openrig.

  • SKILL.md
  • references/worked-example.md

Open the folder on GitHubat commit 1f69831

Compare with similar skills

OpenRig Software Factory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

OpenRig Software Factory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
OpenRig Software Factory this skillmvschwarz/openrig5.9k—~2.6kAutomated safety check: PassApache-2.0
MetaBot Agent Teams CLIxvirobotics/metabot991—~693Automated safety check: PassMIT
Run Wavejpicklyk/task-orchestrator207—~4.7kAutomated safety check: PassMIT
Swarm Coordinationdralgorhythm/claude-agentic-framework125—~1.6kAutomated safety check: PassNone
aweb Team Coordinationawebai/aweb115—~4kAutomated safety check: PassMIT
Team Agent Orchestrationaffaan-m/ECC275k1 repos~1.2kAutomated safety check: PassMIT

Similar skills

  • MetaBot Agent Teams CLI

    xvirobotics/metabot

    Documents the metabot teams command surface for creating durable teams, spawning teammates, dispatching tasks and inspecting their runs across engine sessions.

    991 GitHub stars~693 tokensUpdated 23 days ago
    Agent WorkflowsAuto-check passed
  • Run Wave

    jpicklyk/task-orchestrator

    Resolves ready MCP work items into a run plan, shows it to you, then executes it through the Workflow tool or direct subagent dispatch, with post-run verification.

    207 GitHub stars~4.7k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Swarm Coordination

    dralgorhythm/claude-agentic-framework

    Rules for several agents sharing one repository: an orchestrator tracks work in two tiers, workers write to scratch files, and every handoff leaves a pointer to an artifact.

    125 GitHub stars~1.6k tokensUpdated 2 mo ago
    Agent WorkflowsAuto-check passed
  • Guides decisions for agents working in an aweb team: when to check shared state, claim tasks, take locks, read team roles and instructions, and open separate worktrees.

    115 GitHub stars~4k tokensUpdated yesterday
    Agent WorkflowsAuto-check passed
  • Run team-based orchestration for agent squads: work items with owners and scope, agent Kanban state, branch isolation, control pane visibility, and merge gates.

    275k GitHub starsUsed in 1 repo~1.2k tokens
    Agent WorkflowsAuto-check passed
  • Team Dispatch

    LeoYeAI/openclaw-master-skills

    A skill your agent uses when a request requires multi-agent workflow orchestration (task decomposition + dependency/DAG + parallel execution), needs durable task tracking across context compaction…

    2.2k GitHub stars~3.2k tokensUpdated 2 mo ago
    Agent WorkflowsAuto-check passed

More from mvschwarz/openrig

All 49 skills in this repo
  • OpenRig Upgrade Procedure

    mvschwarz/openrig

    Walks an agent through upgrading the OpenRig CLI and daemon one observed step at a time, keeping live seats alive and reconciling managed plugin files.

    5.9k GitHub starsUsed in 1 repo~2.9k tokens
    Auto-check passed
  • Agent Refocusing

    mvschwarz/openrig

    Re-grounds a long-running agent in the current product outcome by running a path-based trace to the root of its topology and work trees.

    5.9k GitHub stars~864 tokensUpdated today
    Auto-check passed
  • Loads one section of a Markdown file by its path#h2-slug address with a bundled resolver script, for use outside OpenRig's context library.

    5.9k GitHub starsUsed in 1 repo~341 tokens
    Auto-check passed
  • Separates a stable agent seat's identity from its changing occupant, and records honest, two-part provenance whenever one occupant replaces another.

    5.9k GitHub stars~2.1k tokensUpdated today
    Auto-check passed
  • Cross Host Rig Commands

    mvschwarz/openrig

    A skill your agent uses when addressing a registered remote OpenRig host, choosing its transport, or interpreting a cross-host result.

    5.9k GitHub starsUsed in 1 repo~1.3k tokens
    Auto-check passed
  • Openrig Herdr

    mvschwarz/openrig

    A skill your agent uses when opening OpenRig fleet terminals as a herdr wall — turning a rig, pod, mission, slice, or saved view into live interactive agent tiles via rig terminal, watching another…

    5.9k GitHub starsUsed in 1 repo~2.1k tokens
    Auto-check passed

Categories

Questions about OpenRig Software Factory

What does OpenRig Software Factory do?

Helps set up a continuing agent software team for a real repository with OpenRig, choosing between manual work, queue handoffs and an explicit Workflow. The guiding idea is to start with a useful repository outcome and add coordination only when it earns its cost; a beginner can finish reviewed work without Workflow. A table offers three ways to work.

When should I use OpenRig Software Factory?

OpenRig Software Factory fits situations like: setting up a continuing agent team for a real repository; choosing between the starter, workshop and factory teams; handing work between agents with a queue and evidence; deciding when a project actually needs an explicit Workflow.

How do I install OpenRig Software Factory in Claude Code?

Run `npx skills add mvschwarz/openrig --skill openrig-software-factory -a claude-code`. Or copy the skill folder (skills/_canonical/core/openrig-software-factory in mvschwarz/openrig) into .claude/skills/openrig-software-factory in your project. Claude Code loads it when a task matches its description.

How do I install OpenRig Software Factory in Codex?

Run `npx skills add mvschwarz/openrig --skill openrig-software-factory -a codex`. Or copy the skill folder (skills/_canonical/core/openrig-software-factory in mvschwarz/openrig) into .agents/skills/openrig-software-factory in your project. Codex loads it when a task matches its description.

Can I use OpenRig Software Factory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mvschwarz/openrig --skill openrig-software-factory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/openrig-software-factory, .gemini/skills/openrig-software-factory, .github/skills/openrig-software-factory and .opencode/skills/openrig-software-factory in your project.

What does OpenRig Software Factory need to run?

Going by SKILL.md and its folder, OpenRig Software Factory needs the command-line tools its instructions call (npm, claude and codex). Our summary lists: OpenRig and its rig CLI; A Claude Code or Codex login for the chosen team.

Does OpenRig Software Factory access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is OpenRig Software Factory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does OpenRig Software Factory use?

OpenRig Software Factory is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does OpenRig Software Factory use?

About 2.6k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.5k tokens, read only when the agent opens those files.

What are the alternatives to OpenRig Software Factory?

Skills that share tags, products or a category with OpenRig Software Factory: MetaBot Agent Teams CLI (xvirobotics/metabot, 991 stars), Run Wave (jpicklyk/task-orchestrator, 207 stars), Swarm Coordination (dralgorhythm/claude-agentic-framework, 125 stars) and aweb Team Coordination (awebai/aweb, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains OpenRig Software Factory?

mvschwarz (a GitHub user) maintains it in mvschwarz/openrig, which has 5,854 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 8, 2026.

Source: mvschwarz/openrig on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.