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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.

Install / Use

npx skills add aipoch/medical-research-skills --skill cold-chain-risk-calculator

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

88/100

Category

Operations

Supported Platforms

Universal

Our assessment of cold-chain-risk-calculator

cold-chain-risk-calculator scores 88/100 on our quality scale, 326th of 748 Operations skills we index (top 44%).

Its SKILL.md is 5.8 KB long, well organised into 13 sections with 3 code examples: a solid amount of guidance for an agent.

With 1,916 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 15 days ago, so cold-chain-risk-calculator is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-02. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

cold-chain-risk-calculator compared with similar skills

All 4 of these similar skills score higher than cold-chain-risk-calculator; compare them before choosing.

SkillScoreStarsUpdatedFormat
cold-chain-risk-calculator (this skill)by aipoch881.9k15d agoSKILL.md
Agent-Reachby Panniantong10088.1k17d agoCLAUDE.md
algorithmic-artby anthropics100177.9k10d agoSKILL.md
pptxby anthropics100177.9k10d agoSKILL.md
designby nextlevelbuilder100130.2k11d agoSKILL.md

Frequently asked questions

How do I install cold-chain-risk-calculator?
Run npx skills add aipoch/medical-research-skills --skill cold-chain-risk-calculator. The install tabs above show the steps for each supported agent.
Which AI agents does cold-chain-risk-calculator work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is cold-chain-risk-calculator safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is cold-chain-risk-calculator still maintained?
The repository was last updated 15 days ago, so cold-chain-risk-calculator is actively maintained.

name: cold-chain-risk-calculator description: 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. license: MIT author: AIPOCH

Source: 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

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

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:

{
  "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 Checks

Related Skills

View on GitHub
GitHub Stars1.9k
CategoryOperations
Updated15d ago
Forks175

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions