risk-assessment
Perform probabilistic risk assessment with Monte Carlo simulations for offshore marine operations
Best use case
risk-assessment is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Perform probabilistic risk assessment with Monte Carlo simulations for offshore marine operations
Teams using risk-assessment 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/risk-assessment/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How risk-assessment Compares
| Feature / Agent | risk-assessment | 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?
Perform probabilistic risk assessment with Monte Carlo simulations for offshore marine operations
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
# Risk Assessment
## When to Use This Skill
Use this skill when you need to:
- Perform Monte Carlo simulations for uncertainty quantification
- Calculate system reliability and failure probabilities
- Conduct sensitivity analysis to identify critical parameters
- Create risk matrices for hazard assessment
- Perform probabilistic design and analysis
- Quantify uncertainties in marine operations
- Make decisions under uncertainty with risk metrics
- Validate designs against reliability targets
## Core Knowledge Areas
### 1. Monte Carlo Simulation
Basic Monte Carlo framework:
```python
import numpy as np
from scipy import stats
from dataclasses import dataclass
from typing import Callable, Dict, List, Tuple, Optional
import pandas as pd
@dataclass
*See sub-skills for full details.*
### 2. Reliability Analysis
Calculate reliability and failure probability:
```python
def calculate_reliability(
response_data: np.ndarray,
limit_state: float,
mode: str = 'less_than'
) -> dict:
"""
Calculate reliability from Monte Carlo results.
*See sub-skills for full details.*
### 3. Sensitivity Analysis
Identify critical parameters:
```python
def sensitivity_analysis_correlation(
inputs: Dict[str, np.ndarray],
output: np.ndarray
) -> pd.DataFrame:
"""
Sensitivity analysis using correlation coefficients.
*See sub-skills for full details.*
### 4. Risk Matrices and Hazard Assessment
```python
from enum import Enum
class Severity(Enum):
"""Consequence severity levels."""
NEGLIGIBLE = 1
MINOR = 2
MODERATE = 3
MAJOR = 4
CATASTROPHIC = 5
*See sub-skills for full details.*
### 5. Extreme Value Analysis
```python
from scipy.stats import genextreme
def fit_extreme_value_distribution(
data: np.ndarray,
method: str = 'gev'
) -> dict:
"""
Fit extreme value distribution to data.
*See sub-skills for full details.*
## Complete Examples & Well Planning Context
See [references/examples.md](references/examples.md) for complete mooring system risk assessment examples and well planning risk context (actionability gap, risk authority tiers, structured escalation, risk influence maps).
## Resources
See [references/resources.md](references/resources.md) for textbooks, standards, and software references.
---
**Use this skill for:** Expert probabilistic risk assessment and reliability analysis for marine and offshore systems with comprehensive uncertainty quantification.
## Sub-Skills
- [1. Sample Size Selection (+1)](1-sample-size-selection/SKILL.md)Related Skills
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