deepsearch

Name: deepsearch
Availability: InStock
Author: huangrt01

Coordinate iterative web searches to synthesize structured research reports on complex topics.

4.0k|479|Updated Apr 16, 2020

Search Tags:#web-search #report-generation #research-workflow #knowledge-synthesis #deepsearch #llm-analysis #topic-iteration

Ready to run

npx skills add https://github.com/huangrt01/CS-Notes --skill deepsearch-huangrt01

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: deepsearch
Source: https://github.com/huangrt01/CS-Notes/tree/main/.trae/openclaw-skills/deepsearch
Command: npx skills add https://github.com/huangrt01/CS-Notes --skill deepsearch-huangrt01

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

DeepSearch provides a workflow blueprint to perform multi-round web searches and integrated analysis for complex topics, enabling up-to-date, structured research without requiring executable scripts.

Core Features & Use Cases

Multi-round search: Iteratively refines search topics and gathers information across depth levels.
Workflow-driven analysis: Uses an LLM to synthesize findings into a comprehensive final report.
Non-executable blueprint: Serves as a guide for external skills (web-search, LLM) to execute the research process in real environments.
Use Case: Imagine you need to study a fast-evolving topic like quantum networking; DeepSearch orchestrates searches and compiles a detailed report.

Quick Start

Provide a research topic and depth to start the multi-round web-search workflow and generate a final report.

Frequently Asked Questions about deepsearch

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

FAQPage Schema

How do I generate a detailed research report on a complex topic using web search?▼

You can generate a detailed research report by providing a complex topic to trigger a multi-round web-search workflow, which iteratively refines search topics and synthesizes findings into a structured final report using an LLM.

What is iterative web-search driven analysis and when do I need it?▼

Iterative web-search driven analysis is a research workflow that performs multi-round searches across depth levels to synthesize up-to-date information. You need it when studying fast-evolving topics requiring structured conclusions and knowledge synthesis.

Can I use this deep research workflow without installing any executable scripts?▼

Yes, this deep research workflow operates as a non-executable blueprint, serving as a guide for external web-search and LLM skills to execute the research process in real environments without requiring installed scripts.

Do I need external tools to perform multi-round web-search driven topic analysis?▼

Yes, you need external web-search execution and an LLM for reasoning. The workflow coordinates inputs, iterations, and reporting as a description, requiring these external skills to execute the actual research process.

How do I start a multi-round web search workflow for knowledge synthesis?▼

To start the multi-round web-search workflow, provide a research topic and specify the desired depth to begin gathering information across iterative search cycles and generate a final comprehensive report.

What distinguishes iterative topic refinement from a single web search?▼

Iterative topic refinement distinguishes itself by gathering information across multiple depth levels and search cycles, using an LLM to synthesize findings into a comprehensive final report, unlike a single static web search.