survey-pipeline

Automate end-to-end survey construction from topic refinement to final draft.

1|Updated Mar 25, 2026
One-click install
npx skills add https://github.com/HeXiao-55/Auto-SurveyMind --skill survey-pipeline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: survey-pipeline
Source: https://github.com/HeXiao-55/Auto-SurveyMind/tree/main/skills/survey-pipeline
Command: npx skills add https://github.com/HeXiao-55/Auto-SurveyMind --skill survey-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the entire process of turning a fuzzy research idea into a structured survey document, coordinating brainstorming, literature discovery, analysis, taxonomy, gap identification, and writing.

Core Features & Use Cases

  • End-to-end pipeline from idea to SURVEY_DRAFT.md
  • Integrates brainstorming, arXiv literature discovery, paper analysis, taxonomy building, gap identification, and survey writing
  • Generates standardized outputs and traceable citations for reproducibility

Quick Start

Begin by sharing a topic and issuing the /survey-pipeline command to start the end-to-end workflow.

Frequently Asked Questions about survey-pipeline

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

FAQPage Schema
How do I automate an arXiv literature review from a fuzzy research idea to a final draft?

Yes, you can automate survey writing through a staged pipeline that handles brainstorming, arXiv literature discovery, paper analysis, taxonomy building, gap identification, and draft generation. It outputs structured markdown files like SURVEY_DRAFT.md for final review.

How does taxonomy and gap analysis work when constructing a research survey?

Creating a literature-backed survey requires defining a research topic, executing the pipeline for arXiv discovery, and reviewing generated outputs including SURVEY_SCOPE.md, paper_analysis, taxonomy.md, gap_analysis.md, and SURVEY_DRAFT.md. No specific prerequisites are needed beyond an initial research idea.

Can I use this automated survey pipeline for complex topics like graph neural networks or multimodal reasoning?

Using an automated survey pipeline distinguishes itself from manual literature reviews by coordinating brainstorming, arXiv discovery, taxonomy building, and gap analysis end-to-end. It generates standardized, machine-readable outputs with traceable citations, ensuring reproducibility that manual methods often lack.

What's the best way to identify research gaps for a literature review automatically?

Limitations of automated survey generation include the reliance on arXiv literature discovery, meaning non-arXiv publications might be excluded from the analysis. Additionally, while it generates a SURVEY_DRAFT.md, researchers must still manually review the taxonomy and gap analysis to ensure academic accuracy.