dr-explore

Collect evidence from global online sources into structured evidence.jsonl files.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/taiyousan15/taisun_agent --skill dr-explore
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dr-explore
Source: https://github.com/taiyousan15/taisun_agent/tree/main/.claude/skills/dr-explore
Command: npx skills add https://github.com/taiyousan15/taisun_agent --skill dr-explore

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the initial phase of deep research by systematically exploring and collecting evidence from diverse online sources, ensuring that all gathered information is reproducible and properly cited.

Core Features & Use Cases

  • Systematic Evidence Collection: Gathers information from news, social media, academic papers, official documentation, and open-source projects.
  • Reproducible Research: Creates a structured evidence.jsonl file with detailed source information, timestamps, and claims, along with raw data in sources/.
  • Use Case: When starting a new research project on a complex topic like "the future of AI in healthcare," use this Skill to collect initial articles, reports, and discussions to build a foundational understanding and a verifiable dataset.

Quick Start

Explore research on the topic of 'quantum computing' with a standard depth and focus on English and Japanese sources.

Frequently Asked Questions about dr-explore

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

FAQPage Schema
How do I automate evidence gathering from online sources for deep research?

Automating evidence gathering collects data from news, social media, academic papers, and open-source projects. It stores raw files alongside a structured evidence log with source URLs and retrieval dates for reproducible research.

What is the best way to organize collected research data for reproducibility?

Organizing research data for reproducibility involves creating a structured evidence log mapping source URLs, retrieval dates, and claims, while storing raw collected data in a dedicated sources directory.

Can I collect information from both academic papers and social media for the same research topic?

Yes, collecting information from academic papers and social media is supported. Systematic evidence collection explores diverse global online sources, including official documentation and open-source projects, to build a foundational understanding.

How do I start a deep dive research project on a complex topic?

Starting a deep dive research project involves initiating automated exploration of global online sources to collect articles, reports, and discussions. This builds a foundational understanding and a verifiable dataset for detailed analysis.

Do I need web search and file system operations to collect raw data for knowledge management?

Yes, web search, web fetching, and file system operations are required to collect and store raw data for knowledge management. These operations systematically gather and save structured evidence from diverse online sources.

What limitations exist when retrieving information from global online sources for research?

Limitations of retrieving information from global online sources include dependencies on web search and fetching capabilities to access diverse platforms, and the necessity of file system operations to store raw data and structured evidence logs properly.