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.
git clone --depth 1 https://github.com/dmytri/shipshapeWrote 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/rules/dmytri/shipshape/captain)<a href="https://agentmods.dev/rules/dmytri/shipshape/captain"><img src="https://agentmods.dev/badge/rules/dmytri/shipshape/captain/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/rules/dmytri/shipshape/captain"><img src="https://agentmods.dev/badge/rules/dmytri/shipshape/captain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00011 | $0.00226 |
| Opus 5.5 | $0.00004 | $0.00090 |
| Sonnet 5.5 | $0.00002 | $0.00045 |
| Haiku 4.5 | $0.00001 | $0.00023 |
Grade A, and why
captain 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.
What it actually says
Captain, before dispatching or returning:
- Write only Captain-custodied durable artifacts:
.featurespecs, referencedassets/**,CAPTAIN.md, and optionalwatchbill.json, per the "Write scopes are strict" Article. - Dispatch thin to QM in clear context: role and base commit;
watchbill.jsonat its home is the only channel that creates QM targets, per the dispatch contract and the Watchbill policy. - Review
@captainskeletons in harbour: promote by removing the tag, or discard by retagging@shipwright; unresolved@captainscenarios do not block resuming the voyage. - Strike a spent
watchbill.json; absent at rest is the healthy state, per the Watchbill policy. - Outbound needs a clean Boatswain report and explicit user approval, in the human-facing main session, per the Outbound verification policy.
Doctrine lives in skills/captain/SKILL.md; when this rule and the skill disagree, the skill wins.
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 · 14 lines · 11 tokens per session scan A 4e8a1cbea056
captain is a cursor rule published in the GitHub repository dmytri/shipshape (7 stars, last pushed 2mo ago), licensed 0BSD. It adds 11 tokens to every session and 226 once invoked, about $0.0000 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 2026-08-31.
Other cursor rules, from other repositories
handoff
Export a Waybill Bundle by default, or import one when explicitly requested.
dreamd-recall
Recall lessons, decisions, and prior context from the .agent/ memory daemon. Use when starting work in a project that has a .agent/ folder, when the user references a past decision, or when you are about to make a choice that has a documented prior.
agentic-loops
Use when building multi-turn agents, tool-calling systems, agent orchestration, or autonomous workflows — covers loops, tool calling, branching, reflection patterns.
lemoncrow.execute
LemonCrow execute mode reference for Cursor.
ui-motion-workflow
Orchestrate motion-aware UI work by sequencing direction, provider choice, implementation, and browser validation.
commits
Conventional Commits standards for clear, semantic commit messages.