What problem does it solve? AI assistants often describe papers from abstracts or search snippets, producing confident but wrong claims about methods and results. This Skill enforces retrieval of the real full text before any claim is made, and labels every claim by what was actually read. ## Core Features & Use Cases - Identifier resolution and full-text retrieval: Resolves DOI, PMID, PMCID, or title through Europe PMC and NCBI's ID converter, then fetches full text from Europe PMC XML, PMC HTML, or bioRxiv/medRxiv, printing a provenance block with source and character count. - Honest failure signaling: Exit codes distinguish full text (0), abstract only (2), and nothing reachable (3), so claims are labeled accurately instead of fabricated. - Figure image download: Pulls figure images from PMC's CDN with --figures for genuine visual inspection rather than relying on captions. - Use Case: Given a DOI for a paywalled Cell paper, run the retrieval script, discover the PMC deposit has the full text despite being non-open-access, and summarize the actual Methods section instead of guessing from the abstract. ## Quick Start Ask the AI to read the paper at DOI 10.xxxx/example using the paper-reading skill and summarize only what the full text actually says.