cold-chain-risk-calculator
Calculate temperature excursion risks for cold chain transport. Assesses route risk, packaging suitability, and monitoring requirements for biological samples and pharmaceuticals requiring controlled-temperature shipping.
Best use case
cold-chain-risk-calculator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Calculate temperature excursion risks for cold chain transport. Assesses route risk, packaging suitability, and monitoring requirements for biological samples and pharmaceuticals requiring controlled-temperature shipping.
Teams using cold-chain-risk-calculator 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/cold-chain-risk-calculator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cold-chain-risk-calculator Compares
| Feature / Agent | cold-chain-risk-calculator | 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?
Calculate temperature excursion risks for cold chain transport. Assesses route risk, packaging suitability, and monitoring requirements for biological samples and pharmaceuticals requiring controlled-temperature shipping.
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
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# Cold Chain Risk Calculator
Assess temperature excursion risk for cold chain transport routes. Evaluates packaging type, transit duration, and route conditions to produce a structured JSON risk score and mitigation recommendations.
## Quick Check
```bash
python -m py_compile scripts/main.py
python scripts/main.py --help
```
## When to Use
- Evaluating shipping risk for biological samples, vaccines, or temperature-sensitive pharmaceuticals
- Selecting appropriate packaging (dry ice, liquid nitrogen, gel packs) for a given route and duration
- Generating risk documentation for regulatory or QA purposes
## Workflow
1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.
**Fallback template:** If `scripts/main.py` fails or required inputs are absent, report: (a) which parameter is missing, (b) what partial assessment is still possible, (c) the manual risk-scoring approach.
## Parameters
| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `--route`, `-r` | string | Yes | Transport route description (e.g., "NYC-Boston") |
| `--duration`, `-d` | int | Yes | Transport duration in hours (must be > 0) |
| `--packaging`, `-p` | string | No | Packaging type: `dry-ice`, `liquid-nitrogen`, `gel-packs` (default: `dry-ice`) |
| `--output`, `-o` | string | No | Output JSON file path (default: stdout) |
## Usage
```text
python scripts/main.py --route "NYC-Boston" --duration 48 --packaging dry-ice
python scripts/main.py --route "LAX-London" --duration 120 --packaging liquid-nitrogen --output risk_report.json
```
## Output Format
The script outputs a structured JSON object:
```json
{
"route": "NYC-Boston",
"duration_hours": 48,
"packaging": "dry-ice",
"risk_score": 19.2,
"risk_level": "Medium",
"mitigation_recommendations": [
"Add temperature logger to shipment",
"Pre-condition dry ice 2h before packing",
"Notify recipient of expected arrival window"
]
}
```
The `mitigation_recommendations` field is always present and contains at least one actionable item. Recommendations are generated based on risk level and packaging type.
## Risk Model
Risk score = `duration_hours × 0.5 × packaging_factor`
| Packaging | Factor | Notes |
|-----------|--------|-------|
| `dry-ice` | 0.8 | Standard for -70°C samples |
| `liquid-nitrogen` | 0.6 | Best for cryogenic samples |
| `gel-packs` | 1.2 | Suitable for 2–8°C only |
Risk levels: Low (< 15), Medium (15–30), High (> 30)
**Model limitations:** The formula does not account for route complexity, number of transit legs, or ambient temperature variability. A 120-hour international flight may score lower than a 48-hour domestic route due to packaging factor alone. Document these assumptions in every response.
## Features
- Route risk assessment based on duration and packaging type
- Structured JSON output with risk score, level, and mitigation recommendations
- Input validation: rejects negative or zero duration (exit code 1)
- Mitigation action list generated per risk level and packaging type
## Output Requirements
Every response must make these explicit:
- Objective and deliverable
- Inputs used and assumptions introduced (ambient temperature assumed standard; no transit-leg complexity modeled)
- Workflow or decision path taken
- Core result: risk score, risk level, and mitigation recommendations
- Constraints, risks, caveats (e.g., model does not account for route complexity or number of transit legs)
- Unresolved items and next-step checks
## Input Validation
This skill accepts: cold chain transport scenarios defined by a route, duration, and optional packaging type.
If the request does not involve temperature-controlled shipping risk — for example, asking to track a shipment in real time, calculate drug dosing, or assess non-temperature logistics — do not proceed. Instead respond:
> "`cold-chain-risk-calculator` is designed to assess temperature excursion risk for cold chain transport. Your request appears to be outside this scope. Please provide a route, duration, and packaging type, or use a more appropriate tool for your task."
## Error Handling
- If `--duration` is ≤ 0, print `Error: --duration must be a positive integer (hours).` to stderr and exit with code 1.
- If `--packaging` is not one of `dry-ice`, `liquid-nitrogen`, `gel-packs`, reject with a clear error listing valid options.
- If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If `scripts/main.py` fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
- Do not fabricate files, citations, data, search results, or execution outcomes.
## Response Template
1. Objective
2. Inputs Received
3. Assumptions
4. Workflow
5. Deliverable
6. Risks and Limits
7. Next ChecksRelated Skills
ebm-calculator
Evidence-Based Medicine diagnostic test calculator. Computes sensitivity, specificity, PPV, NPV, likelihood ratios, NNT, and pre/post-test probability from 2x2 contingency table inputs.
date-calculator
Calculate medical date windows including gestational age, estimated delivery dates, and follow-up visit scheduling. Produces structured JSON output for clinical research and trial coordination workflows.
buffer-calculator
Calculate precise buffer recipes with accurate mass and volume measurements for molecular biology and biochemistry. Supports PBS, RIPA, and TAE with concentration scaling, stock solution preparation, pH adjustment guidance, and step-by-step protocols.
bmi-bsa-calculator
Calculate Body Mass Index (BMI) and Body Surface Area (BSA) for clinical assessment, obesity screening, and chemotherapy dosing. Supports multiple BSA formulas (DuBois, Mosteller, Haycock), WHO weight classification, pediatric calculations, and metric/imperial input.
sds-msds-risk-scanner
Extract hazard codes and safety info from chemical safety datasheets.
survival-curve-risk-table
Analyze data with `survival-curve-risk-table` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
sample-size-power-calculator
Advanced sample size and power calculations for complex study designs including survival analysis, clustered designs, and multiple comparisons.
meta-results-risk-of-bias
Generates the "Risk of Bias" results section for a meta-analysis based on assessment tables and statistics. Use when the user wants to draft the risk of bias analysis text from provided data tables.
limitation-and-risk-writer
Acknowledges limitations in sample, design, measurement, and validation in a professional way that improves credibility without undermining the whole paper. Use when writing the limitations paragraph of a Discussion section, preparing a grant risk assessment, responding to reviewers about study weaknesses, or framing scope boundaries for a paper. Also triggers on "write my limitations", "how should I address the limitation of", "reviewer said my sample is too small", or "help me word this limitation".
skill-auditor
A comprehensive auditor for any agent skill — including Manus, OpenClaw/ClawHub, Claude, LobeHub, or custom SKILL.md-based skills. Use this skill whenever a user wants to evaluate, audit, review, score, or quality-check an agent skill before publishing, updating, or deploying. Covers two hard veto gates (structural redlines + research integrity redlines), static quality scoring across 25 criteria (ISO 25010 + OpenSSF + Agent), dynamic test input generation, multi-mode execution testing, multi-layer output evaluation with five specialized category rubrics (Evidence Insight / Protocol Design / Data Analysis / Academic Writing / Other), a Research Veto that applies to all four research categories, human eval viewer generation, actionable P0/P1/P2 optimization recommendations, and automatic skill improvement that outputs a polished, production-ready SKILL.md. Also use whenever a user says "audit my skill", "evaluate my skill", "improve my skill", or wants a corrected version after evaluation.
two-sample-mr-research-planner
Generates complete two-sample Mendelian randomization (MR) research designs from a user-provided research direction. Use when users want to design, plan, or build a study using two-sample MR to test causal relationships. Triggers:"design a two-sample MR study", "build a publishable MR paper", "test whether this biomarker causally affects this disease", "generate Lite/Standard/Advanced MR plans", "screen multiple exposures with MR", "bidirectional MR design", "causal inference using GWAS summary statistics", or "I want to study X and Y using MR". Always outputs four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, and publication upgrade path.
research-proposal-generator
Generates a comprehensive research proposal design based on input literature, including hypothesis, mechanism verification, and budget. Use when the user wants to design a research project from a paper.