Begin with the research question
A literature review, gap analysis, and methods critique need different source selections. Start by writing the question the bundle should answer.
Then choose papers and notes that directly support that question.
Balance full papers and notes
Full papers are useful when details matter. Annotated summaries are useful when you need breadth.
If the bundle is too large, keep full text for primary sources and summaries for secondary sources.
Label source authority
Distinguish peer-reviewed papers, preprints, your notes, and web references. The AI should know what kind of evidence it is using.
Riflet workflow
Add paper folders, notes, and supporting pages. Trim irrelevant sources, check tokens, and export one bundle for synthesis in your chosen AI.
Build better AI context with Riflet
Collect the files, notes, websites, and docs that matter. Export one portable bundle for any AI.
Download Riflet freeFrequently asked questions
Is context engineering for research only useful for developers?
No. The same context principles apply to research, writing, legal review, client work, product planning, and any workflow where the AI needs project-specific source material.
Does more context always produce better AI output?
No. Relevant, well-structured context usually beats a large dump of loosely related files. Large context windows make preparation more important, not less important.
Where does Riflet fit in this workflow?
Riflet is the assembly step. It helps gather source material, filter it, estimate the token budget, and export one portable file for the AI tool you choose.
Does Riflet replace RAG or AI project features?
Not always. RAG is useful for large retrieval systems. AI project features are useful inside one platform. Riflet is best when you want explicit, portable context you can inspect before using.