paper-interview

paper-interview is an Audio, music & podcasts skill for AI agents, published by hyeshik in the qbio-skills repository on GitHub. Skillspace rates paper-interview C (72/100) and it passed the safety scan; the rating is based on static analysis only.

Generate a podcast-style in-depth scientific interview that introduces an academic paper. Uses multi-agent analysis (field expert, methods specialist, context historian, critical reviewer, accessibility translator, impact assessor) to prepare rich source material, then an editor agent curates the narrative, and a writer agent composes the final interview between a professional science interviewer and the paper's author. The user drops a PDF of the paper; all supplementary context is gathered via web search and PubMed/bioRxiv. MANDATORY TRIGGERS: "paper interview", "podcast interview for paper", "introduce this paper", "generate interview for this paper", "paper podcast", "deep dive interview", "interview about this paper", "논문 인터뷰", "논문 소개 인터뷰", "paper introduction interview". Also trigger when the user uploads a PDF and asks for a podcast, interview, deep dive, or accessible introduction of a scientific paper.

Grade

C

Quality

72 / 100

Safety

Passed

GitHub stars

27

Unproven: rated by static analysis only, not yet compared head-to-head.

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