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Every session starts from zero context. But the user has been thinking about these topics for weeks, months, sometimes years — and that thinking lives in their Obsidian vault. Notes, bookmarks, project docs, design decisions, research findings. When you search the vault before starting work, you're not just gathering information — you're respecting the context the user has already built, and producing output that fits into their existing mental model rather than a generic one.
The difference between good and great output is often grounding: the same presentation about "AI agent sandboxes" is dramatically better when it references the specific project the user bookmarked last month, uses their terminology, and connects to their existing knowledge graph.
Search when the answer might already exist in the user's own words:
When a search returns nothing, that's fine — proceed with your own knowledge. The point is to check, not to force-find.
All endpoints use the Pneuma server's base URL.
Search — find notes by keyword:
POST /api/plugins/obsidian-memory/search
Body: { "query": "search terms", "limit": 5 }
→ { results: [{ entry: { path, title }, score, snippet }] }
Read — get full content of a note:
GET /api/plugins/obsidian-memory/read/{path}
→ { entry: { path, title, content } }
Write — create or update a note (only when user asks):
POST /api/plugins/obsidian-memory/write
Body: { "path": "folder/file.md", "content": "...", "tags": ["..."] }
Status — check availability (call once per session):
GET /api/plugins/obsidian-memory/status
→ { available: true/false }
Search → Read: Search returns paths and snippets. If a snippet looks relevant, read the full note. One search + one read is the typical flow.
Cite casually: "I found a note in your vault about X" — not formally, not with full paths.
Don't over-search: One or two searches per topic. No results = the user doesn't have notes on this, move on.
Write sparingly: Only when the user explicitly asks to save something to their vault.
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