tools/obsidian/SKILL.md
Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.
npx skillsauth add letta-ai/skills obsidianInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Obsidian vault = a normal folder on disk.
Vault structure (typical)
*.md (plain text Markdown; edit with any editor).obsidian/ (workspace + plugin settings; usually don’t touch from scripts)*.canvas (JSON)Obsidian desktop tracks vaults here (source of truth):
~/Library/Application Support/obsidian/obsidian.jsonobsidian-cli resolves vaults from that file; vault name is typically the folder name (path suffix).
Fast “what vault is active / where are the notes?”
obsidian-cli print-default --path-only~/Library/Application Support/obsidian/obsidian.json and use the vault entry with "open": true.Notes
~/Documents, work/personal, etc.). Don’t guess; read config.print-default.Pick a default vault (once):
obsidian-cli set-default "<vault-folder-name>"obsidian-cli print-default / obsidian-cli print-default --path-onlySearch
obsidian-cli search "query" (note names)obsidian-cli search-content "query" (inside notes; shows snippets + lines)Create
obsidian-cli create "Folder/New note" --content "..." --openobsidian://…) working (Obsidian installed)..something/...) via URI; Obsidian may refuse.Move/rename (safe refactor)
obsidian-cli move "old/path/note" "new/path/note"[[wikilinks]] and common Markdown links across the vault (this is the main win vs mv).Delete
obsidian-cli delete "path/note"Prefer direct edits when appropriate: open the .md file and change it; Obsidian will pick it up.
testing
Navigates archived ChatGPT or Claude-style conversation exports and a MemFS reference archive on demand. Use when recalling what a past assistant knew, searching old conversations, rendering specific chats, seeding reference memory from export sidecars, or mining historical context without doing a full import.
testing
Migrates deprecated Letta Filesystem folders/files to MemFS using markdown document corpora, chunking, local lexical search, and QMD semantic search via the memfs-search skill. Use when replacing folders.files.upload, working with PDFs or document QA, or emulating open_file, grep_file, and search_file behavior.
data-ai
Configures Letta agent compaction settings and custom summarization prompts. Use when a user asks to change an agent's compaction prompt, improve summaries after context eviction, tune sliding-window or all-message compaction, or design companion/coding-agent continuity summaries.
development
Semantic search over agent memory files. Use when you need to find conceptually related memory blocks, discover forgotten reference files, check what you already know before creating new memory, or search beyond exact keyword matching. Currently supports QMD (local, no API keys).