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 agentmods add commands/lgbarn/shipyard/documentgit clone --depth 1 https://github.com/lgbarn/shipyardWhat 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 | $0.00013 | $0.00660 |
| Opus 5 | $0.00006 | $0.00330 |
| Sonnet 5 | $0.00003 | $0.00132 |
| Haiku 4.5 | $0.00001 | $0.00066 |
Grade A, and why
document 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 2d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/shipyard:document - On-Demand Documentation Generation
You are executing on-demand documentation generation. Follow these steps precisely.
Step 1: Parse Arguments
Extract from the command:
scope(optional): What to document. Accepts:- No argument / "current": Document uncommitted changes (
git diff+git diff --cached) - Diff range (e.g.,
main..HEAD): Document all changes in range - Directory path (e.g.,
src/api/): Document specific module - "." or "all": Document all changed files vs main branch
- No argument / "current": Document uncommitted changes (
If no scope and no uncommitted changes exist, default to documenting changed files against the main branch.
Step 2: Detect Context
- Check if
.shipyard/exists (optional — this command works anywhere). - If
.shipyard/config.jsonexists, readmodel_routing.documentationfor model selection. - Otherwise, use default model: sonnet.
- Follow Worktree Protocol (see
docs/PROTOCOLS.md) — detect worktree context.
Step 3: Gather Scope
Based on the scope argument, collect the code to document:
- Current:
git diff+git diff --cached - Range:
git diff <range> - Directory: List and read all source files in directory
- Full codebase:
git diff main...HEAD
Also gather:
- Existing documentation in
docs/directory (if exists) - README.md (if exists)
.shipyard/PROJECT.md(if exists)
Step 4: Build Agent Context
Assemble context per Agent Context Protocol (see docs/PROTOCOLS.md):
- The diff/file content collected in Step 3
- Existing documentation for update context
.shipyard/PROJECT.md(if exists)- Working directory, current branch, and worktree status
Step 5: Dispatch Documenter
Dispatch a documenter agent (subagent_type: "shipyard:documenter") with:
- Follow Model Routing Protocol — resolve model from
model_routing.documentation(default: sonnet) - max_turns: 20
- All context from Step 4
- Instruction: Analyze changes and generate/update documentation — API docs for public interfaces, architecture updates for structural changes, user-facing docs for new features
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.
- 2d ago First seen · 79 lines · 13 tokens per session scan A bab7fb2cb864
document is a command published in the GitHub repository lgbarn/shipyard (65 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 660 once invoked, about $0.0001 per session on Opus 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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