Turn papers, notes, and source folders into one AI-ready research bundle

Why researchers need prepared AI context

Research work gets scattered across PDFs, annotated notes, Zotero exports, spreadsheets, and web pages. Uploading one paper at a time makes the model miss cross-paper patterns and wastes time before every session.

A good AI session starts before the first prompt. The model needs the stable facts, source documents, constraints, and vocabulary that shape the work. When those inputs are scattered, the output becomes generic or incomplete.

Workflow

Use Riflet as the assembly step before opening your AI chat.

• Add the folder that contains your PDFs and notes.
• Add supporting web pages or exported citation notes when they matter.
• Remove papers that are only tangential to the question.
• Check the token count before exporting to your target AI.

Best-fit work

Riflet is strongest for literature reviews and evidence synthesis, paper comparison and methodology critique, grant, thesis, and manuscript planning because those workflows depend on multiple files being visible at once.

For scanned PDFs, run OCR first so the bundle contains actual text. Riflet is the context assembly step, not a citation manager or academic database.

Token budgeting

Do not treat a context window as a storage closet. The more unrelated material you include, the harder it is for the model to keep the important parts in focus.

Use the token counter as an editing tool. If the bundle is too large, remove background files first, then duplicates, then low-signal references.