What Vault Operator can do | Vault Operator

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What Vault Operator can do ​<br>Most AI tools sit outside your knowledge base and wait for you to copy and paste. Vault Operator lives inside it. It reads your notes, follows the graph that ties them together, picks up your habits, and acts on your behalf.<br>This page is the short tour. Each section links out to the guide that goes deep.<br>Prefer to watch? This 7-minute animated explainer walks through the agent from the inside: the loop, the harness with its five gates, tools, skills, and MCP, then one real job crossing every layer.<br>Your browser does not support embedded video. Download the explainer instead. Inline AI chat in the editor ​<br>Available since v3.0.0.<br>You can run a chat directly on the note you are reading. Select text, press Cmd+Shift+I (Ctrl+Shift+I on Windows and Linux) or right-click and pick "Inline AI chat", and a floating panel opens over the editor. From there you ask a question about the selection, look something up, rewrite, translate, summarize, or extract action items without leaving the note.<br>When the panel proposes a change to the file, the Änderungen prüfen modal opens first. You review each edit, apply only the ones you want, and the agent writes a checkpoint marker into the chat so you can undo the change later through the same checkpoint system used elsewhere in Vault Operator.<br>Inline chat guide | Chat interface | Safety and control<br>Capture sources with block-level provenance ​<br>Drop a PDF, web clip, or Office file into the chat. Vault Operator runs a fast triage against your vault's ontology and, if you choose to ingest, walks you through a short dialog before it writes anything.<br>The resulting sense-making note carries a ↗ link at the end of every claim. The link jumps back to the exact block in the source. No more "I have a note about this somewhere" without a path back to where the claim came from.<br>You drive this from chat in plain language: "Ingest this PDF" runs the quick single-pass capture, "Do a deep ingest of this paper" starts the deep path (triage, topic pick, source markup, sense-making note, backlinks). The five-step deep flow stops at each question and waits for you.<br>Example prompt: "Deep-ingest this research paper. Focus on the methodology section."

Quick ingest tutorial | Deep ingest tutorial | Knowledge ingest guide | Block-level provenance<br>Clip web pages into permanent notes ​<br>Available since v3.3.6.<br>Ask the agent to clip an article and it archives the page the way the Obsidian Web Clipper does: the full text converted to Markdown, the images downloaded into your vault with the links rewritten to local embeds, and a header the agent writes on top (frontmatter plus its own summary). This goes further than web_fetch, which reads a page into the conversation, keeps images as remote URLs, and truncates long text. The page URL and every image URL pass the same network guard chain as web_fetch.<br>Example prompt: "Clip this article into Sources/ and write a short summary into the header: https://example.com/article"

Vault operations | Safety and control<br>Three-layer memory across sessions ​<br>Vault Operator remembers what matters across chats, not only inside one chat.<br>Soul holds long-lived preferences (writing style, project conventions, recurring choices).<br>Facts hold structured statements about people, projects, and topics.<br>History is a searchable transcript of past conversations.<br>The agent retrieves from all three layers when a new chat starts, and you can mark any note as a memory source so its content stays in scope.<br>Example prompt: "Summarize this meeting note like last time." (It remembers your preferred format.)

Memory and personalization | How memory works | Mastery and recipes<br>Find notes by meaning ​<br>When you ask "what do I know about X?", Vault Operator does not grep filenames. It searches by meaning over a local semantic index, walks wikilinks and frontmatter, and surfaces connections you may have missed.<br>The semantic index is opt-in. Turn it on once and pick when it builds: never (default), on startup, or on agent switch. After that, search behaves like a librarian who has read every note.<br>Example prompt: "Find all notes related to behavioral economics and show me how they connect."

Search by meaning tutorial | Knowledge discovery | How the knowledge layer works<br>Build Word, Excel, and PowerPoint files (PPTX in beta) ​<br>Vault Operator writes .docx, .xlsx, and .pptx files from your vault content.<br>DOCX and XLSX output is clean and reliable for everyday use. PPTX runs as a single pipeline: the agent first calls plan_presentation to turn your source notes into a constrained outline, then create_pptx builds the deck. PPTX is in beta, treat the output as a draft you finish manually for client-facing decks.<br>Example prompts: "Turn this note into a Word document with proper headings and a table of contents." "Build a five-slide internal status presentation from my...