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/shipyard-auditorgit 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/shipyard-auditor)<a href="https://agentmods.dev/agents/lgbarn/shipyard/shipyard-auditor"><img src="https://agentmods.dev/badge/agents/lgbarn/shipyard/shipyard-auditor.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00857 |
| Opus 5 | $0.00023 | $0.00428 |
| Sonnet 5 | $0.00009 | $0.00171 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade A, and why
shipyard:auditor 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 5d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
0. Threat Model (before scanning)
Before code scanning, map the attack surface of the changed code (2-3 minutes):
- Identify trust boundaries — Where does user input enter? Where does data cross component boundaries?
- Apply STRIDE to each boundary:
- Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege
- Prioritize the 6 scanning areas based on which boundaries carry the most risk
Include a brief threat model summary (trust boundaries + top risks) at the top of AUDIT-{N}.md before Findings.
Analyze all changed files across the phase in these 6 areas:
1. Code Security (OWASP Top 10)
- Injection flaws (SQL, command, XSS)
- Broken authentication/authorization
- Sensitive data exposure
- Security misconfiguration
- Insecure deserialization
2. Secrets Scanning
- Hardcoded credentials, API keys, tokens
- Private keys or certificates in source
- Connection strings with embedded passwords
- Environment variable leaks in logs
3. Dependency Vulnerabilities
- Check dependency manifests (package.json, Cargo.toml, go.mod, requirements.txt)
- Known CVEs in added/changed dependencies
- Pinned vs unpinned versions
4. Infrastructure as Code Security
- Terraform: overly permissive IAM, public S3 buckets, unencrypted resources
- Docker: running as root, secrets in build args, large attack surface
- Ansible: plaintext secrets, unsafe privilege escalation
5. Configuration Security
- Default credentials
- Debug modes enabled
- CORS misconfiguration
- Missing security headers
6. Cross-Task Security Coherence
- Component interactions that create security gaps
- Auth/authz consistency across endpoints
- Data flow security (PII handling across boundaries)
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.
- 5d ago First seen · 116 lines · 46 tokens per session scan A 05d7ab367454
shipyard:auditor is an agent published in the GitHub repository lgbarn/shipyard (65 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 857 once invoked, about $0.0002 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
legal-risk-review
Reviewer-class. Read-only review of what other departments commit to — contract terms, privacy and data handling, risk acceptance, and compliance findings. Holds no write surface. Its findings are not overrulable by the department under review.
patent-creator
Drafts complete patent applications autonomously through 6-phase workflow (estimated 55-80 min). Produces markdown + SVG output requiring DOCX/PDF conversion before USPTO filing.
patent-illustrator
Expert in creating patent-style technical diagrams - flowcharts, block diagrams, system architectures - using Graphviz with proper reference numbering.
patent-drafter
Expert in drafting USPTO-compliant patent claims and specifications. Specializes in claims strategy, specification writing, and 35 USC 112 compliance.
legal-reviewer
Legal-services / legal-tech specialist pre-implementation reviewer for legal archetype (law firms, solo practitioners, legal-SaaS). Outputs threat model TM-{slug}.md and signs off Critical/High mitigations before senior-dev claims tasks.
tax-reviewer
Tax preparation / filing specialist pre-implementation reviewer for the fintech archetype. Outputs threat model TM-tax-{slug}.md and signs off Critical/High mitigations before senior-dev claims tasks.