What problem does it solve? Keeping up with the flood of new AI research papers is time-consuming, and manually browsing arXiv or Hugging Face every day leads to missed important work or repeated recommendations. ## Core Features & Use Cases - Topic-based search: Queries the Hugging Face Papers API for a given research topic, or browses today's trending daily papers when no topic is set. - Deduplication via memory logs: Reads the last 7 days of memory logs to avoid recommending papers already covered. - Curated single pick: Selects the one most worth-reading paper based on novelty, relevance, practical implications, and community upvotes, then sends a formatted notification and logs the result. - Use Case: A researcher asks for a daily paper on "memory consolidation" and receives one arXiv link with a one-sentence rationale, without re-reading papers suggested earlier in the week. ## Quick Start Ask the assistant to pick today's must-read paper on transformer architectures and send it via the notify script.