Turn Obsidian into ChatGPT context

Why Obsidian needs preparation before ChatGPT

An Obsidian vault can be a deep knowledge base, but pasting one note at a time loses links, folder context, and the supporting notes around an idea.

ChatGPT is useful for general analysis, writing, coding help, and iterative work when the context is packaged into a readable file. The result depends heavily on how cleanly your source material is grouped, labeled, and filtered before it reaches the model.

Step-by-step workflow

Point Riflet at your vault folder and select the notes, MOCs, and project folders that should shape the answer.

• Add Obsidian vaults as a Riflet source.
• Select MOCs, project notes, evergreen notes, research summaries, source notes, and short instruction files that explain naming conventions.
• Use filters to remove stale exports, generated files, and unrelated background material.
• Export one Markdown or text bundle and use it in ChatGPT Projects.

What to include

For this workflow, prioritize MOCs, project notes, evergreen notes, research summaries, source notes, and short instruction files that explain naming conventions. Add a short instruction file at the top if the AI needs naming conventions, project goals, or constraints.

A full-vault dump is rarely the best context. Curate topical folders, current notes, and project maps so the model does not spend tokens on unrelated daily notes.

Getting the bundle into ChatGPT Projects

ChatGPT Projects keeps uploaded material in project files. Create a project and attach the bundle to it, so every chat started inside that project can read the file without you pasting anything. It accepts text, Markdown, PDF, and Office documents, so a Markdown or plain-text export from Riflet needs no further conversion.

ChatGPT retrieves passages from attached files rather than reading each one end to end. Explicit file-path headers and section markers matter more here than anywhere else: a bundle with clear boundaries gets retrieved reliably, an undifferentiated wall of text does not.

Project files persist until you remove them, so a stale bundle keeps answering with outdated facts long after the sources moved. Replace it on the same schedule as the work.

Token budget advice

Riflet lets you check the bundle against GPT-6 Astra's 1,050,000-token context window before export. Keep room for your actual question and for the model's answer.

If the bundle is too large, remove files that merely repeat what another file already explains. Context quality usually beats context volume.

Honest limitation

Riflet does not push live updates into ChatGPT. It creates the context file. When the source changes, re-export and upload the new bundle yourself.