What problem does it solve?
Helps researchers and knowledge workers quickly locate relevant papers and matching passages within a curated collection of Markdown paper notes, removing the need to manually open and scan many files.
Core Features & Use Cases
- Flexible search modes: supports title, author, keyword, field, and tag searches with case-insensitive matching.
- Metadata extraction & ranking: extracts title, authors, date, and file path from frontmatter, captures matching context lines, and computes a heuristic relevance score based on title, content, author, field, and tag matches.
- Organized output: groups results by research field and presents ranked entries including relevance, authors, date, link, and match location for quick review.
- Use case: find all papers on "quantization" in the large-models folder, ranked by relevance and showing matching excerpts and links to notes.
Quick Start
Search the Papers directory for "large models quantization" and return ranked results with titles, authors, dates, file paths, relevance scores, and the matching context.