light-research-ethics

Audit scientific research artifacts for ethics and compliance risks.

514|67|Updated Jun 7, 2026
One-click install
npx skills add https://github.com/Light0305/Light-skills --skill light-research-ethics
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: light-research-ethics
Source: https://github.com/Light0305/Light-skills/tree/main/skills/light-research-ethics
Command: npx skills add https://github.com/Light0305/Light-skills --skill light-research-ethics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a persistent ethics and compliance auditing backbone for scientific work, continuously scanning across manuscripts, data releases, software, patents, and competition materials to identify risks such as misrepresentation, privacy violations, copyright concerns, and inappropriate authorship practices, delivering auditable guidance.

Core Features & Use Cases

  • Backbone for ongoing ethics checks that run across the full research lifecycle (from drafting to submission).
  • Automated ethics review templates and risk logs derived from assets such as assets/ethics_review_template.md and assets/risk_checklist.md.
  • Decision trees and CN compliance references to guide users through common risk scenarios (e.g., IRB/ethics approvals, data privacy, authorship disputes, and publishing ethics).
  • Self-contained tooling for offline checks including retraction verification, text overlap screening, and quantitative consistency checks, all with auditable outputs.

Quick Start

Trigger this Skill at project milestones to automatically perform ethics & compliance checks on manuscripts, data, and software artifacts.

Frequently Asked Questions about light-research-ethics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate ethics and compliance review for research manuscripts?

Automate ethics and compliance review by triggering checks at project milestones to scan manuscripts, data releases, and software for risks like misrepresentation and privacy violations. The Skill applies formal IRB approvals, ICMJE authorship criteria, and data privacy checks across the research lifecycle.

What does an IRB ethics compliance check cover for data releases?

An IRB ethics compliance check for data releases covers risk flags for privacy violations, copyright concerns, and data retention requirements. It applies formal checks using structured templates and decision trees to ensure data privacy and licensing rules are met before publication.

How do I resolve authorship disputes using ICMJE and CRediT criteria?

Resolve authorship disputes by applying formal ICMJE and CRediT criteria checks to research artifacts. The Skill enforces these authorship standards during automated reviews, identifying inappropriate authorship practices and providing structured ethics outputs for correction.

Can I check publishing ethics compliance offline for multiple research artifacts?

Yes, you can check publishing ethics compliance offline across manuscripts, software, and patents. The Skill provides self-contained tooling for offline checks including retraction verification, text overlap screening, and quantitative consistency checks with auditable outputs.

When do I need to run an ethics risk audit during the research lifecycle?

Run an ethics risk audit continuously from drafting to submission at key project milestones. The Skill acts as a persistent backbone, scanning artifacts to identify copyright concerns, misrepresentation, and privacy violations, delivering risk logs and mandatory templates.

What are the limitations of automated research ethics compliance checks?

Automated research ethics compliance checks rely on applying formal rules like COPE guidelines and IRB criteria to provided artifacts. They generate risk flags and mandatory templates but require human judgment for final decisions on complex authorship disputes or nuanced data privacy scenarios.