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Dashboard Design For Trials

Name: Dashboard Design For Trials
Author: aipoch-ai

作者 AIpoch · GitHub ↗ · v0.1.0 · MIT-0

cross-platform ✓ 安全检测通过

246

总下载

当前安装

版本数

在 OpenClaw 中安装

/install dashboard-design-for-trials

功能描述

Design dashboard layout sketches for clinical trials showing enrollment progress and adverse event rates

使用说明 (SKILL.md)

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

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

# 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:

Study Overview Card - Study ID, name, status
Recruitment Progress - Overall progress bar, site-by-site progress comparison
Subject Distribution - Gender, age distribution pie charts
AE Monitoring - Adverse event incidence rate, severity distribution
Data Quality - CRF completion rate, query count
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

Basic Functionality: Standard input → Expected output
Edge Case: Invalid input → Graceful error handling
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

安全使用建议

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) run in a sandboxed environment if you have concerns about execution. If you need to use real clinical data, ensure compliance with your organization’s data protection policies and consider sanitizing or aggregating inputs first.

功能分析

Type: OpenClaw Skill Name: dashboard-design-for-trials Version: 0.1.0 The skill bundle is a legitimate tool designed to generate HTML dashboard sketches for clinical trial monitoring. The core logic in 'scripts/main.py' uses standard Python libraries to generate mock data and format it into a responsive HTML/CSS layout, which is then saved to a local file. There is no evidence of data exfiltration, malicious command execution, or prompt injection attempts in either the code or the documentation.

能力评估

✓ Purpose & Capability

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.

✓ Instruction Scope

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.

✓ Install Mechanism

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.

✓ Credentials

No environment variables, credentials, or config paths are required. The script accepts CLI parameters only, which is appropriate for a local dashboard generator.

✓ Persistence & Privilege

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.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install dashboard-design-for-trials
安装完成后，直接呼叫该 Skill 的名称或使用 /dashboard-design-for-trials 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v0.1.0

Initial release: generate clinical trial dashboard layout sketches. - Creates HTML dashboards showing enrollment, adverse event rates, and key trial metrics. - Supports multiple chart types (progress bars, line, pie, and bar charts). - Customizable parameters for study details and output path. - Pure Python, no extra dependencies required. - Responsive design for various devices. - Includes security and risk assessment guidelines.

元数据

Slug dashboard-design-for-trials

版本 0.1.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

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