技能详情（站内镜像，无评论）
作者：AIpoch @AIPOCH-AI
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v0.1.0
统计：⭐ 0 · 35 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：aipoch-ai/cold-chain-risk-calculator-2
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill is internally consistent with its stated purpose: a small, local Python risk-calculation script with no external dependencies, credentials, or network calls.
目的
Name/description match the included code: scripts/main.py implements a simple cold-chain risk calculation based on route, duration, and packaging. No external APIs, credentials, or unexpected binaries are required. Minor mismatch: the SKILL.md references file I/O and 'Temperature monitoring' features and a security checklist for input file handling, but the provided script only reads CLI arguments and does not read or write files.
说明范围
SKILL.md usage directs the agent to run the local Python script with CLI args, which is exactly what the code does. The SKILL.md's risk table and checklist mention file reads/writes and prompt-injection protections; those are good hygiene but are not required by the current script. No instructions request environment variables, system-wide config, or external endpoints.
安装机制
No install spec is present; this is instruction-only plus a small included Python file. No downloads, package installs, or archive extraction are requested.
证书
The skill declares no required environment variables, credentials, or config paths. The code does not access environment variables or secrets.
持久
The skill does not request always:true and does not modify system or other-skill configuration. It runs as a local command when invoked.
综合结论
This skill is a lightweight, local Python script and appears coherent for calculating simple cold-chain risk scores. Before installing/running: (1) Inspect the included scripts (you already have them); they only use argparse and simple math. (2) Run it in a sandbox or with non-sensitive test inputs to confirm behavior. (3) Note that SKILL.md mentions file I/O and monitoring features that the current script does not implement — if you expect fi…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Cold Chain Risk Calculator」。简介：Calculate cold chain transport risks。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/aipoch-ai/cold-chain-risk-calculator-2/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: cold-chain-risk-calculator
description: Calculate cold chain transport risks
version: 1.0.0
category: Operations
tags: []
author: AIPOCH
license: MIT
status: Draft
risk_level: Medium
skill_type: Tool/Script
owner: AIPOCH
reviewer: ''
last_updated: '2026-02-06'
---
# Cold Chain Risk Calculator
Calculate temperature excursion risks for cold chain transport.
## Parameters
| Parameter | Type | Default | Required | Description |
|-----------|------|---------|----------|-------------|
| `--route`, `-r` | string | - | Yes | Transport route description |
| `--duration`, `-d` | int | - | Yes | Transport duration in hours |
| `--packaging`, `-p` | string | dry-ice | No | Packaging type (dry-ice, liquid-nitrogen, gel-packs) |
## Usage
```bash
python scripts/main.py --route "NYC-Boston" --duration 48 --packaging dry-ice
```
## Features
- Route risk assessment
- Packaging optimization
- Temperature monitoring
## Risk Assessment
| Risk Indicator | Assessment | Level |
|----------------|------------|-------|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
## Security Checklist
- [ ] No hardcoded credentials or API keys
- [ ] No unauthorized file system access (../)
- [ ] Output does not expose sensitive information
- [ ] Prompt injection protections in place
- [ ] Input file paths validated (no ../ traversal)
- [ ] Output directory restricted to workspace
- [ ] Script execution in sandboxed environment
- [ ] Error messages sanitized (no stack traces exposed)
- [ ] Dependencies audited
## Prerequisites
No additional Python packages required.
## Evaluation Criteria
### Success Metrics
- [ ] Successfully executes main functionality
- [ ] Output meets quality standards
- [ ] Handles edge cases gracefully
- [ ] Performance is acceptable
### Test Cases
1. **Basic Functionality**: Standard input → Expected output
2. **Edge Case**: Invalid input → Graceful error handling
3. **Performance**: Large dataset → Acceptable processing time
## Lifecycle Status
- **Current Stage**: Draft
- **Next Review Date**: 2026-03-06
- **Known Issues**: None
- **Planned Improvements**:
- Performance optimization
- Additional feature support