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/lgbarn/shipyardWrote 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/agents/lgbarn/shipyard/mapper)<a href="https://agentmods.dev/agents/lgbarn/shipyard/mapper"><img src="https://agentmods.dev/badge/agents/lgbarn/shipyard/mapper/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/agents/lgbarn/shipyard/mapper"><img src="https://agentmods.dev/badge/agents/lgbarn/shipyard/mapper.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 | $0.00226 | $0.01888 |
| Opus 5.5 | $0.00090 | $0.00755 |
| Sonnet 5.5 | $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 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 — 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.
- 1mo 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 6d ago), licensed MIT. It adds 226 tokens to every session and 1,888 once invoked, about $0.0009 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.
Other agents, from other repositories
specwright-architect
Strategic architecture advisor. Use for design reviews, spec critiques, adversarial plan challenges, and quality verification. READ-ONLY.
specwright-reviewer
Code quality and spec compliance reviewer. Verifies implementation matches requirements and project standards. Read-only for source files; Bash restricted to verification commands.
code-reviewer
Code reviewer. Delegate only when the user explicitly starts an Octopus workflow.
edge-case-explorer
Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…
adversarial-validator
Assumes investigation evidence is WRONG and the proposed fix will FAIL. Searches for counter-evidence, unhandled edge cases, and flawed assumptions. Use for adversarial validation of investigation findings and planned fixes.
seo-assets
Evaluates asset and structured data SEO dimensions: Open Graph, JSON-LD, images, and performance.