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.