OpenRig is a software harness that coordinates Claude Code and Codex coding agents as one system, with agent teams defined in YAML and launched together. It is for organizing persistent teams of coding agents that can delegate work to specialists and return results or decisions. The catalogue lists 53 skills and one plugin as add-ons for OpenRig.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mvschwarz/openrig --skill specification-systemgit clone --depth 1 https://github.com/mvschwarz/openrigWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mvschwarz/openrig/specification-system)<a href="https://agentmods.dev/skills/mvschwarz/openrig/specification-system"><img src="https://agentmods.dev/badge/skills/mvschwarz/openrig/specification-system/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mvschwarz/openrig/specification-system"><img src="https://agentmods.dev/badge/skills/mvschwarz/openrig/specification-system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.01081 |
| Opus 5.5 | $0.00038 | $0.00432 |
| Sonnet 5.5 | $0.00019 | $0.00216 |
| Haiku 4.5 | $0.00009 | $0.00108 |
Grade A, and why
specification-system scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Specification System
The declarative primitive family for OpenRig intent: rig specs, agent specs, workflow specs, startup/context fragments, operating-mode declarations, and the user spec library that stores and reuses them.
Specs are how humans and agents describe repeatable topology and behavior without re-explaining it in chat. They are also shareable artifacts: a user should be able to publish a spec or spec family so another user can instantiate the same rig shape, role structure, or workflow pattern.
Without a dependable spec primitive, OpenRig depends on manual startup prompts and tribal memory. That blocks repeatability, product demos, rig bundles, and autonomous rig construction.
Use this when
- Authoring a RigSpec / AgentSpec / workflow spec
- Designing a startup/context fragment
- Reasoning about spec-library lifecycle (validation, sharing, upgrade semantics)
- Auditing a spec for portability (does it run on another host?)
- Distinguishing spec vs bundle vs extension cleanly
Don't use this when
- The work is one-off and won't be reused. Manual rig assembly is fine for one-shot work.
- The intent is to package a topology + workflow as a shareable artifact. That's
rig-bundles-and-shareable-artifacts. - The intent is to add runtime behavior. That's
extension-and-user-workspace.
Failure modes (4)
- A spec can instantiate a topology but not the workflow or operating mode needed to use it. Topology is necessary but not sufficient — workflow and operating mode must be declared too.
- A shared spec depends on local paths or hidden startup fragments and fails on another host. Specs must be self-describing for portability.
- Agents modify specs as one-off files instead of preserving reusable user/library intent. Specs are reusable; treating each instance as one-off destroys the primitive's value.
- Validation proves YAML shape but not whether the declared topology can actually run. Structural validation is not enough; runtime realization is the real proof.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 104 lines · 94 tokens per session scan A 5226d6e8b136
specification-system is a skill published in the GitHub repository mvschwarz/openrig (7,545 stars, last pushed yesterday), licensed Apache-2.0. It adds 94 tokens to every session and 1,081 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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dynamic-resources
Example skill loaded from resourcesdiscover.
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Exercise the real app/API/CLI and collect observable evidence; tests alone do not count as end-to-end verification.
swarm-pr-review
Run a graph-guided, tool-augmented PR review using context packing, parallel exploration, mandatory repository-agnostic risk-family coverage with dispatch scaled to diff size and risk, independent reviewer validation, critic challenge, and metrics writeback. Use for deep pull request review with low false-positive…