lgbarn/shipyard/shipyard-codex-orchestration
Claude Code and agent skill by lgbarn/shipyard
- community
Checking that the SKILL.md file is still in the repository.
Use when running any multi-step Shipyard workflow under Codex — build, audit, plan, ship, review, research, or map. Explains how Shipyard's parallel-agent workflows degrade to inline sequential execution in Codex, and routes intent to the right workflow skill. Trigger when the user says "build the plan", "audit this", "ship it", "review the code", "run the shipyard build", or asks how Shipyard works in Codex.
Install
npx vskill@latest install lgbarn/shipyard/shipyard-codex-orchestrationSKILL.md
Shipyard orchestration under Codex
Shipyard was built for Claude Code, where workflows dispatch fresh subagents in parallel (builder, reviewer, auditor, architect, verifier, researcher, mapper, …) via the Task tool. Codex has no equivalent — it runs in a single context.
So under Codex, Shipyard workflows run as inline sequential personas: instead of dispatching a separate agent, you adopt each role yourself, one after another, in this same conversation.
Honest degradation — what you lose
- No parallelism. Roles run one at a time, so multi-agent phases are slower.
- No context isolation. In Claude Code a fresh reviewer can't be biased by the
builder's reasoning. Here the same context does both, so a review is less independent. Compensate by being deliberately skeptical when you switch into a review/verify role — re-read the actual artifact, don't trust your own prior step.
What you keep: the discipline — the review and verify gates still run, just sequentially.
The inline-sequential pattern
When a workflow calls for "dispatch the X agent", instead:
- State which role you're entering ("Now acting as the reviewer…").
- Adopt that role's mandate fully — including its MUST-NOT constraints (a reviewer
makes no code edits; a mapper only documents).
- Produce the role's deliverable.
- Exit the role and continue the workflow.
Routing — which skill for which intent
| Intent | Skill / behavior | |
|---|---|---|
| Implement a plan | shipyard-executing-plans skill, run builder→reviewer→verifier inline | |
| Security/compliance audit | security-audit skill, adopting the auditor mandate | |
| Create a plan | shipyard-writing-plans skill (+ shipyard-brainstorming first) | |
| Code review after a build | shipyard-review skill | |
| Domain/technology research | shipyard-research skill | |
| Map/onboard a codebase | shipyard-map skill | |
| Ship/release a completed phase | shipyard-ship skill | |
| TDD a feature | shipyard-tdd skill | |
| Debug a failure | shipyard-debugging skill |
If a workflow has a dedicated skill, use it and apply the inline-sequential pattern above to any agent dispatch it describes. The shipyard-review, shipyard-research, shipyard-map, and shipyard-ship skills exist because those roles have no other skill home in Codex.
State
Codex has no SessionStart hook, so Shipyard state is not auto-loaded. When a workflow needs project state, run scripts/state-read.sh yourself at the start (see the state/utility skills).
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingcodex/skills-extra/shipyard-codex-orchestration/SKILL.md
Popularity
- Repository stars
- 63
- Repository forks
- 3
- 7-day trend score
- 21
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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