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 · 32 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：aipoch-ai/dashboard-design-for-trials
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill's code and instructions are consistent with its stated purpose (generating local HTML dashboard sketches) and do not request unrelated credentials, installs, or network access.
目的
Name/description match the code and SKILL.md. The included Python script generates mock clinical-trial dashboard HTML from CLI arguments; no unrelated services, binaries, or credentials are required.
说明范围
SKILL.md instructs only to run the local Python script with CLI parameters to produce an HTML file. The instructions do not request reading unrelated files, accessing environment secrets, or sending data to external endpoints.
安装机制
No install spec is provided and there are no external downloads. The skill includes a single Python script that uses only the standard library, which is proportionate to the stated task.
证书
No environment variables, credentials, or config paths are required. The script accepts CLI parameters only, which is appropriate for a local dashboard generator.
持久
Skill is not always-on and does not request persistent system privileges or modify other skills. It writes an output HTML file to the workspace (as expected) but does not request elevated permissions.
综合结论
This appears to be a straightforward local dashboard generator. Before installing/running: (1) review the full script yourself (or have an engineer do so) if you plan to feed it sensitive patient data — the tool writes files to the workspace; (2) run it first with non-sensitive sample inputs to confirm behavior; (3) open the generated HTML offline and inspect it for any external resource links (CDNs or trackers) before viewing in a browser; (4…
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「Dashboard Design For Trials」。简介：Design dashboard layout sketches for clinical trials showing enrollment progres…。
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/dashboard-design-for-trials/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: dashboard-design-for-trials
description: Design dashboard layout sketches for clinical trials showing enrollment
progress and adverse event rates
version: 1.0.0
category: Visual
tags: []
author: AIPOCH
license: MIT
status: Draft
risk_level: Medium
skill_type: Tool/Script
owner: AIPOCH
reviewer: ''
last_updated: '2026-02-06'
---
# Dashboard Design for Trials
Design layout sketches for clinical trial data monitoring panels, displaying recruitment progress, AE incidence rates, and other key metrics.
## Features
- Generate HTML layout sketches for clinical trial Dashboards
- Support multiple chart types: progress bars, line charts, pie charts, bar charts, etc.
- Customizable study protocol, site count, key metrics
- Responsive design, adaptable to different screen sizes
## Usage
```bash
python scripts/main.py [options]
```
## Parameters
| Parameter | Type | Default | Required | Description |
|-----------|------|---------|----------|-------------|
| `--study-id` | string | STUDY-001 | No | Study ID |
| `--study-name` | string | Clinical Trial A | No | Study Name |
| `--sites` | int | 10 | No | Number of sites |
| `--target-enrollment` | int | 100 | No | Target enrollment count |
| `--current-enrollment` | int | 45 | No | Current enrollment count |
| `--ae-count` | int | 12 | No | Adverse event count |
| `--output` | string | dashboard.html | No | Output HTML file path |
### Examples
```bash
# Generate default Dashboard
python scripts/main.py
# Customize study parameters
python scripts/main.py
--study-id "PHASE-III-2024"
--study-name "Phase III Clinical Trial of New Drug for Type 2 Diabetes"
--sites 15
--target-enrollment 300
--current-enrollment 120
--ae-count 25
--output my_dashboard.html
```
## Output
Generates an HTML Dashboard containing the following modules:
1. **Study Overview Card** - Study ID, name, status
2. **Recruitment Progress** - Overall progress bar, site-by-site progress comparison
3. **Subject Distribution** - Gender, age distribution pie charts
4. **AE Monitoring** - Adverse event incidence rate, severity distribution
5. **Data Quality** - CRF completion rate, query count
6. **Timeline** - Study milestones, estimated completion date
## Dependencies
- Python 3.7+
- No additional dependencies (pure standard library generates HTML/CSS/JS)
## Author
Skill ID: 194
## 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