An Obsidian vault that gives AI coding agents persistent memory. Built for Claude Code, with working hooks for Codex CLI and Gemini CLI. Start a session, talk about your day, and the agent handles the rest — notes, links, indexes, performance tracking. Every conversation builds on the last.
AI coding agents are powerful, but they forget. Every session starts from zero — no context on your goals, your team, your patterns, your wins. You re-explain the same things. You lose decisions made three conversations ago. The knowledge never compounds.
Give your agent a brain.
You: "start session"
Agent: *reads North Star, checks active projects, scans recent memories*
Agent: "You're working on Project Alpha, blocked on the BE contract.
Last session you decided to split the coordinator. Your 1:1
with your manager is tomorrow — review brief is ready."
Works with Claude Code (full support), Codex CLI, and Gemini CLI — same hooks, same commands, same vault.
Install via shardmind install or git clone — same vault either way.
Morning kickoff:
/om-standup
# → loads North Star, active projects, open tasks, recent git changes
# → "You have 2 active projects. The auth refactor is blocked on API contract.
# Your 1:1 with Sarah is at 2pm — last time she flagged observability."
Brain dump after a meeting:
/om-dump Just had a 1:1 with Sarah. She's happy with the auth work but wants
us to add error monitoring before release. Also, Tom mentioned the cache
migration is deferred to Q2 — we decided to focus on the API contract first.
Decision: defer Redis migration. Win: Sarah praised the auth architecture.
→ Updated org/people/Sarah Chen.md with meeting context
→ Created work/1-1/Sarah 2026-03-26.md with key takeaways
→ Created Decision Record: "Defer Redis migration to Q2"
→ Added to perf/Brag Doc.md: "Auth architecture praised by manager"
→ Updated work/active/Auth Refactor.md with error monitoring task
Incident response:
/om-incident-capture https://slack.com/archives/C0INCIDENT/p123456
# → slack-archaeologist reads every message, thread, and profile
# → people-profiler creates notes for new people involved
# → Full timeline, root cause analysis, brag doc entry
End of day:
You: "wrap up"
# → verifies all notes have links
# → updates indexes
# → brag-spotter finds uncaptured wins
# → suggests improvements
npm install -g shardmind
mkdir my-vault && cd my-vault
shardmind install github:breferrari/obsidian-mind
shardmind install writes into the current directory, so create and enter a fresh folder first. The wizard collects your name, organization, vault purpose, agents to include, and whether to enable QMD; ShardMind then initializes git, optionally bootstraps QMD, and personalizes brain/North Star.md with your answers. Then:
claude, codex, or gemini. Codex runs the vault's hooks only once the folder is trusted and each hook approved: see Using with Other Agents.ShardMind is the package manager for Obsidian vault templates. The install adds a .shardmind/ sidecar that powers the wizard, optional modules (skip what you don't use), and three-way-merge upgrades. With every value at its default the install is byte-equivalent to git clone — clone-UX is preserved exactly. Delete .shardmind/ and shard-values.yaml from the installed vault and it keeps working: ShardMind is additive, not load-bearing.
git clone https://github.com/breferrari/obsidian-mind.git
Or use it as a GitHub template. Skip the wizard, get the bare template. Then run through the same 4 steps above, plus fill in brain/North Star.md with your goals (the ShardMind wizard does this for you).
QMD is where most of the agent's retrieval intelligence comes from. Optional in the strict sense — the vault falls back to grep + the Obsidian CLI — but the experience is meaningfully better with it:
AGENTS.md, which points to .claude/rules/brain-topics.md) to consult brain/ guidance through QMD when the conversation touches a listed topic.context-loader, review-prep, brag-spotter, and friends consult QMD first, then fall back to grep..mcp.json — when QMD is installed, mcp__qmd__query, mcp__qmd__get, and mcp__qmd__multi_get appear in the agent's tool menu alongside Read and Edit. Subagents, slash commands, and the main conversation all call the same typed contract. Add another MCP-aware tool later (a database, a ticketing system, a calendar) and it plugs in the same way.npm install -g @tobilu/qmd
node --experimental-strip-types .scripts/qmd-bootstrap.ts
The bootstrap is idempotent — safe to re-run. It resolves this vault's index name — the qmd_index field from vault-manifest.json when set, otherwise the vault folder name slugified — reads qmd_context, registers the collection, attaches the context, and builds the index + embeddings. The SessionStart hook and .mcp.json wrapper both read the same manifest field, so CLI queries, the MCP server, and the re-index all scope to the same named SQLite store. This isolates the vault from any other QMD-using vault on the same machine.
If you want to use a different index name (for example, one vault per engineer on a shared workstation), edit qmd_index in vault-manifest.json before running the bootstrap. Once the store is populated, always pass --index <name> to the CLI:
qmd --index obsidian-mind query "what did we decide about caching"
qmd --index obsidian-mind update # after bulk edits
qmd --index obsidian-mind embed # after many new notes
QMD runs three small models locally, so there is no API key to set up, no per-query cost, and it works offline:
| model | size | job |
|---|---|---|
embeddinggemma-300M |
~328MB | turns notes and queries into vectors |
qmd-query-expansion-1.7B |
~1.28GB | rewrites your query into better search terms |
Qwen3-Reranker-0.6B |
~640MB | reorders the shortlist by actual relevance |
They download on first use and are cached. QMD offloads to the GPU when it finds one — CUDA on a discrete card, Metal on Apple Silicon — and falls back to CPU otherwise. Check what yours is doing with qmd doctor.
Use qmd 2.5.1 or later. In 2.1, qmd status probes the GPU, and on a machine without one that can take several seconds (4 to 37 s on CI runners, measured 2026-10-13, #349). SessionStart's self-heal reads qmd status under a 5-second limit, so a status that times out leaves it unable to see a broken install.
The three CLI verbs map onto that stack, cheapest first: qmd search is BM25 keywords with no model at all, qmd vsearch is vector-only, and qmd query is the full hybrid. If you want to avoid the larger downloads, search alone is genuinely useful.
The om server sends a lexical and a vector sub-query, so retrieval finds the note that answers your question even when it shares no keywords with it. Practical consequences worth knowing:
recall with a query takes a couple of seconds while recall without one is near-instant. search over notes is fast — it is the vector step that costs.[!NOTE] If QMD isn't installed, everything still works — the agent falls back to grep and the Obsidian CLI, and the MCP server entry is skipped with a harmless warning.
Note on the Node flag. Hook scripts execute TypeScript di
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