maritime-legal
AI-assisted maritime legal and casualty consulting — engineering-technical interface with admiralty proceedings
Best use case
maritime-legal is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
AI-assisted maritime legal and casualty consulting — engineering-technical interface with admiralty proceedings
Teams using maritime-legal should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/maritime-legal/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How maritime-legal Compares
| Feature / Agent | maritime-legal | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
AI-assisted maritime legal and casualty consulting — engineering-technical interface with admiralty proceedings
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Maritime Legal Engineering Skill > Engineering-technical interface with maritime legal proceedings. Covers casualty investigation, expert witness support, admiralty law reference, and regulatory compliance. > > **Scope boundary:** This skill covers engineering-technical analysis only. It does NOT provide legal advice. All outputs require review by qualified maritime attorneys. ## Casualty Investigation Support Analyze marine casualty reports (MAIB, NTSB, USCG) to: - Identify ISM Code non-conformities (SMS failures, inadequate procedures) - Map findings to root-cause taxonomy: - **Equipment failure** — material defect, maintenance lapse, design inadequacy - **Human factors** — situational awareness, fatigue, communication breakdown - **Weather/environment** — sea state beyond design basis, visibility, ice - **SMS failure** — procedure not followed, not written, or inadequate - Cross-reference `worldenergydata.MAIBLoader` + `NTSBMarineLoader` for comparable incidents ## Expert Witness Report Structure For admiralty proceedings produce reports in this order: 1. **Qualifications** — credentials, relevant experience, publications 2. **Scope and instructions** — what was asked; documents reviewed 3. **Technical background** — relevant standards and vessel type overview 4. **Factual findings** — timeline reconstruction; condition of equipment 5. **Standard of care analysis** — what a competent operator would have done 6. **Causation** — proximate cause chain; contributing factors 7. **Opinion** — engineering conclusion framed for legal use 8. **Limitations** — what could not be determined; data gaps Framing standard: Daubert (US federal/USDC) or Civil Evidence Act 1995 (UK) as applicable. ## Admiralty Law Reference | Instrument | Scope | |-----------|-------| | COLREGs 1972 | Collision regulations — Rules of the Road | | Jones Act (46 USC 30104) | US seaman negligence claims | | Limitation of Liability Act (46 USC 30505) | Shipowner liability cap | | Hague-Visby Rules | Bill of lading cargo claims | | MLC 2006 | Seafarer working and living conditions | | P&I Club process | Third-party liability; club letters of undertaking | ## Incident Database Query ```python # Example: find comparable propulsion casualties from worldenergydata import MAIBLoader, NTSBMarineLoader maib = MAIBLoader() results = maib.query(vessel_type="bulk carrier", cause_category="propulsion", year_range=(2015, 2024)) # Returns: incident_id, vessel, date, cause_summary, outcome ``` ## Liability Framing Translate engineering findings into legal causation language: - **Proximate cause** — "The immediate cause of the allision was the failure of the bow thruster, which directly caused loss of maneuverability in confined waters." - **Standard of care** — "A prudent operator would have tested thruster response before entering the channel per port authority standing instructions." - **Damages estimation** — hull repair quote + cargo loss + wreck removal + third-party property; reference comparable settlements where available ## Regulatory Framework | Regulation | Applicability | |-----------|--------------| | 46 CFR Parts 90–196 | US vessel inspection requirements | | 33 CFR Parts 160–173 | US navigation and waterways safety | | SOLAS Chapter II-1/II-2 | Construction, subdivision, machinery, fire | | MARPOL Annex I–VI | Pollution prevention | | ISM Code (SOLAS IX) | Safety management systems | | USCG MISLE | US marine casualty reporting (CG-2692) | | BSEE 30 CFR 250 | OCS incident notifications (offshore) |
Related Skills
legal-sanity-scan
Mandatory legal compliance gate for document intelligence, data catalogs, and code porting — scans for client names, proprietary references, and sensitive paths
legal-risk-assessment
Assess and classify legal risks using a severity-by-likelihood framework with escalation criteria
legal-sanity-review
Legal Sanity Review Workflow — mandatory pre-gate in the cross-review cycle
legal-risk-assessment-severity-x-likelihood-matrix
Sub-skill of legal-risk-assessment: Severity x Likelihood Matrix (+2).
legal-risk-assessment-risk-assessment-memo-format
Sub-skill of legal-risk-assessment: Risk Assessment Memo Format.
legal-risk-assessment-mandatory-engagement
Sub-skill of legal-risk-assessment: Mandatory Engagement (+3).
legal-risk-assessment-green-low-risk-score-1-4
Sub-skill of legal-risk-assessment: GREEN -- Low Risk (Score 1-4) (+3).
legal-risk-assessment-1-risk-description
Sub-skill of legal-risk-assessment: 1. Risk Description (+10).
test-oversized-skill
A test fixture skill that exceeds 200 lines with multiple H2/H3 sections for split testing.
interactive-report-generator
Generate interactive HTML reports with Plotly visualizations from data analysis results. Supports dashboards, charts, and professional styling.
data-validation-reporter
Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.
agent-os-framework
Generate standardized .agent-os directory structure with product documentation, mission, tech-stack, roadmap, and decision records. Enables AI-native workflows.