paper-interview

Extract key insights from scholarly papers into structured interview drafts.

27|3|Updated Feb 20, 2026
One-click install
npx skills add https://github.com/hyeshik/qbio-skills --skill paper-interview
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paper-interview
Source: https://github.com/hyeshik/qbio-skills/tree/main/paper-interview
Command: npx skills add https://github.com/hyeshik/qbio-skills --skill paper-interview

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, PyMuPDF, Pillow, playwright, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the creation of an in-depth, interview-style exploration of a scholarly paper by orchestrating multi-agent analyses, editorial planning, and a final writer's draft. It enables science communicators to generate a magazine-ready interview that captures nuances, tensions, and context for a target audience of domain researchers.

Core Features & Use Cases

  • Multi-Agent Analysis: six specialized perspectives (field expert, methods specialist, context historian, critical reviewer, accessibility translator, and impact assessor) synthesize a comprehensive view.
  • Editorial Curation & Visual Planning: an editor consolidates analyses into a 4-5 act narrative with embedded diagrams and figure references.
  • Production Pipeline: end-to-end flow from paper text ingestion to final interview draft and typeset-ready PDF.
  • Use Case: a science journalist wants to rapidly produce a rigorous, citation-backed interview that can be published in a high-end science magazine.

Quick Start

Provide a ready-to-publish 3,000-5,000 word interview draft for a given paper, including editor's plan and visual plan.

Frequently Asked Questions about paper-interview

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

FAQPage Schema
How do I turn a research paper into an interview article?

Multi-agent analysis converts a research paper into a 3000-5000 word interview article by extracting insights through six specialized perspectives and structuring them into a publication-ready draft with a clear editorial arc.

Can I generate a science communication interview in Korean from an English paper?

Yes, the pipeline operates in English or Korean, processing ingested paper text and background research to produce a structured, publication-ready interview draft in the selected language.

What is multi-agent analysis for science communication?

Multi-agent analysis for science communication uses six specialized perspectives, including a field expert and critical reviewer, to synthesize a comprehensive view of a scholarly paper and capture its nuances, tensions, and context.

Does this interview writing pipeline support PDF text extraction?

Yes, the pipeline supports PDF text extraction using PyMuPDF, ingesting paper text directly from documents to feed into the multi-agent analyses and editorial planning stages for interview generation.

How do I plan visual diagrams for a magazine-ready interview article?

An editor consolidates multi-agent analyses into a 4-5 act narrative with embedded diagrams and figure references, providing a visual plan that aligns with the editorial arc for typesetting.

What is the best way to automate editorial planning for scholarly papers?

A multi-agent pipeline automates editorial planning for scholarly papers by consolidating six specialized analyses into a structured 4-5 act narrative, producing a typeset-ready interview draft for publication.