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🐱 Paper Search

Find real academic papers across the world's scholarly databases — then read any open-access one in depth. Grounded in real data, never fabricated.

     

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✨ What it does

🔍 Search that means it — one question searches five scholarly databases at once (OpenAlex, Crossref, arXiv, Semantic Scholar, Europe PMC), de-duplicates, and ranks by genuine research fit — not just keyword overlap.

📄 Read, not skim — pick any open-access paper and it resolves the PDF, extracts the text, and gives you a structured reading — research question, method, key findings, and limitations — with page references where the source supports them.

🛡️ No made-up papers, no made-up findings — every result is a real record from a public API, and every reading is built only from the actual extracted text. When a paper is paywalled, it says so — it never invents the contents.

🎬 Demo

Say it in one line — the topic, plus any options inline:

"Find 200 papers on XR experience."

It runs right away — no forms, no back-and-forth — and returns a numbered list of every result, one scannable line each, so you can act on any of them by number. The format is fixed by the tool, identical no matter which model runs the skill:

🔎 5 results for: XR experience

1. PLUME: Record, Replay, Analyze and Share User Behavior in 6DoF XR Experiences — Charles Javerliat et al. · 2024 · cited 23 · 🟢 · PDF
2. A bibliometric analysis of immersive technology in museum exhibitions: exploring user experience — Jingjing Li et al. · 2023 · cited 92 · 🟢 · PDF
3. Two sides of the same coin: accessibility practices and neurodivergent users' experience of extended reality — Tamari Lukava et al. · 2022 · cited 40 · 🟢 · PDF
4. A framework study on the use of immersive XR technologies in the cultural heritage domain — Chiara Innocente et al. · 2023 · cited 144 · 🔒
5. Wayfinding in Virtual Reality Serious Game: An Exploratory Study in the Context of User Perceived Experiences — Shafaq Irshad et al. · 2021 · cited 27 · 🟢 · PDF

Every title links straight to the paper; 🟢 means a free PDF you can read in full. Then just say "deep-read #1" — it opens that paper's PDF and reads it back to you with findings tied to page numbers, grounded entirely in the paper's own text.

Every search also saves the complete list (all results, with abstracts) to a search-results.md file — so the full set is always captured, never cut off.

🔬 Why you can trust it