What problem does it solve? Finding and obtaining full-text academic papers requires querying many fragmented sources (Semantic Scholar, PubMed, CrossRef, arXiv, OpenAlex) with different APIs, keys, and failure modes, and downloaded PDFs are often corrupted or wrong files. This Skill unifies multi-source literature search, PDF download, and integrity verification into one pipeline with built-in diagnostics. ## Core Features & Use Cases - Multi-source aggregated search: Query 5+ scholarly sources (Semantic Scholar, PubMed, CrossRef, arXiv, OpenAlex) via the jabkit unified entry point to cross-validate results and avoid single-source bias. - Verified PDF download pipeline: Download full-text PDFs (primarily via bban.top CDN direct links) and validate every file with %PDF- magic-byte checks plus pdfinfo title matching to reject corrupted or mismatched files. - Three-stage diagnostics: Run literature diagnose to test 7 search sources, DOI resolution, and 12 download channels, producing structured JSON reports on source availability. - Use Case: A researcher needs 100 papers on "pupil light reflex ODE" with verified full texts. The Skill searches CrossRef and PubMed, downloads the PDFs into an output directory, and confirms each file passes magic-byte and title verification. ## Quick Start Ask the agent to search CrossRef and PubMed for papers on your topic and download the verified full-text PDFs into an output folder.