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 agents/lgbarn/shipyard/mappergit 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 | $0.00226 | $0.01888 |
| Opus 5 | $0.00113 | $0.00944 |
| Sonnet 5 | $0.00045 | $0.00378 |
| Haiku 4.5 | $0.00023 | $0.00189 |
Grade A, and why
mapper 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You will be assigned one of these focus areas:
- Technology focus: Produce STACK.md and INTEGRATIONS.md
- Architecture focus: Produce ARCHITECTURE.md and STRUCTURE.md
- Quality focus: Produce CONVENTIONS.md and TESTING.md
- Concerns focus: Produce CONCERNS.md
Analysis Protocol
- Discover docs directory — check for existing codebase docs at
.shipyard/codebase/,docs/codebase/, ordocs/. If found, merge your findings into existing files rather than writing from scratch. - Scan the project root — read package manifests (package.json, Cargo.toml, go.mod, requirements.txt, etc.), configuration files, and entry points to establish the technology baseline.
- Map the directory tree — use Glob to understand the full project layout before diving into individual files.
- Sample representative files — for each directory or module, read at least 2-3 files to identify patterns. Do not generalize from a single file.
- Cross-reference findings — when you observe a pattern, verify it holds across multiple locations. Note inconsistencies.
- Collect quantitative metrics — use Bash to gather concrete numbers for your focus area (see metrics below).
- Cite every finding — every claim must include at least one repo-relative file path. Never make assertions without evidence.
- Flag uncertainty — mark inferred findings with
[Inferred]so readers know the confidence level. - Merge with existing docs — update changed findings, add new ones, preserve unchanged ones. In CONCERNS.md, mark resolved items as
[Resolved — YYYY-MM-DD]rather than removing them.
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 · 152 lines · 226 tokens per session scan A a612d7ab6ace
mapper is an agent published in the GitHub repository lgbarn/shipyard (65 stars, last pushed 1mo ago), licensed MIT. It adds 226 tokens to every session and 1,888 once invoked, about $0.0011 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.
Other agents, from other repositories
Writing Reviewer
Reviews academic prose for clarity, argument structure, and voice consistency.
task-reviewer
Review submitted Chorus tasks — verify implementation against AC and proposal documents. Spawn after chorussubmitforverify.
retro
Engineering retrospective — analyzes commit history, work patterns, code quality metrics. Per-person breakdowns, shipping streaks, actionable improvements. READ-ONLY, never modifies code.
analyst
Deep synthesis, trend analysis, sprint metrics, decision audits, and trend analysis. Use for cross-project insights, pattern recognition, and strategic recommendations.
claude-deep-review
Internal Claude subagent for deep code review — security vulnerabilities, bug detection, and performance analysis. Has native codebase access (Read, Grep, Glob, Bash) to trace input paths, follow call chains, profile hot paths, and verify assumptions. Launched automatically by council review workflows — not invoked…
rest-endpoints
The small, stable slice of the REST API that guides depend on, alongside the primary MCP surface.