What does the Content Review feature specifically check?

It acts as an automated peer-reviewer, checking if conclusions are supported by cited evidence, ensuring statistics are complete, and verifying that figure references are valid.

Can I use this for non-bioinformatics projects?

While the templates are optimized for bioinformatics, the core principles of hypothesis-driven research, phase management, and fact-interpretation separation are applicable to most scientific domains.

How do I start a new project using this skill?

You can use the /research-init command or simply ask Claude to 'initialize project' to generate the recommended folder structure and STEERING.md tracker.

How does this skill help with reproducibility?

It creates a standardized directory structure and provides checklists for documenting software versions, data seeds, and methods to ensure every experiment can be replicated by other researchers.

Bioinformatics Research Project Manager

Name: Bioinformatics Research Project Manager
Author: dakesan

bydakesan

データサイエンスとML

Automates the initialization and lifecycle management of bioinformatics research projects with structured workflows and scientific quality standards.

概要

This skill streamlines the entire lifecycle of bioinformatics research, from initial setup to final publication. It provides a standardized project structure, tracks research phases like exploration and execution, and enforces high scientific standards through proactive content review. By integrating best practices for hypothesis-driven research and reproducibility, it ensures that data analysis remains rigorous, traceable, and well-documented throughout the project's evolution, helping researchers maintain focus on discovery while Claude handles organizational overhead.

主な機能

Scientific quality review for fact-interpretation separation and evidence traceability.
Built-in guidance for reproducibility, hypothesis formulation, and experimental design.
0 GitHub stars
Automated project structure initialization with standardized directories and Jupyter templates.
Real-time status monitoring of experiments, milestones, and next recommended actions.
Lifecycle phase tracking from planning and exploration to integration and publication.

ユースケース

Setting up a new computational biology study with a standardized, reproducible folder structure.
Reviewing lab notebook entries or draft reports against scientific quality and reproducibility standards.
Transitioning a research project from the data exploration phase to systematic execution with updated priorities.

概要

主な機能

Scientific quality review for fact-interpretation separation and evidence traceability.
Built-in guidance for reproducibility, hypothesis formulation, and experimental design.
0 GitHub stars
Automated project structure initialization with standardized directories and Jupyter templates.
Real-time status monitoring of experiments, milestones, and next recommended actions.
Lifecycle phase tracking from planning and exploration to integration and publication.

ユースケース

Setting up a new computational biology study with a standardized, reproducible folder structure.
Reviewing lab notebook entries or draft reports against scientific quality and reproducibility standards.
Transitioning a research project from the data exploration phase to systematic execution with updated priorities.