obsidian-wiki is a framework that helps AI agents build and maintain an interconnected knowledge base from text-based material in an Obsidian vault. It is for people who want their agents to remember discoveries, connect related information, and answer questions with wiki-link citations. Catalogue add-ons provide the agent skills, instructions, agents, and configuration used to create and maintain these wikis.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ar9av/obsidian-wiki/session-brainnpx skills add Ar9av/obsidian-wiki --skill session-braingit clone --depth 1 https://github.com/Ar9av/obsidian-wikiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ar9av/obsidian-wiki/session-brain)<a href="https://agentmods.dev/skills/ar9av/obsidian-wiki/session-brain"><img src="https://agentmods.dev/badge/skills/ar9av/obsidian-wiki/session-brain.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00153 | $0.01085 |
| Opus 5 | $0.00077 | $0.00543 |
| Sonnet 5 | $0.00031 | $0.00217 |
| Haiku 4.5 | $0.00015 | $0.00109 |
Grade A, and why
session-brain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Brain
Builds a searchable topic graph over your agent session history. The output is a sidecar
at ~/.claude/session-brain/ — the vault is never touched.
All the heavy lifting is deterministic Python in the obsidian-wiki CLI. Your only job is to
name the clusters, which takes exactly one turn and requires reading no transcripts.
When to use which skill
| Goal | Skill |
|---|---|
| Build or refresh the graph; survey topics | session-brain (this one) |
| Find and load a specific past session | session-search |
| Distil sessions into permanent vault pages | wiki-history-ingest / claude-history-ingest |
Step 1: Build
obsidian-wiki sessions-build --json
Roughly 3 seconds cold on ~1000 sessions, well under a second incrementally — it re-reads only transcripts whose size or mtime changed. Useful flags:
| Flag | When |
|---|---|
--full |
Ignore all caches and re-read everything |
--mutual |
Tighter, smaller clusters (mutual-kNN edges only) |
--half-life N |
Change the recency half-life (default 90 days) |
--min-sim 0.15 |
Fewer, stronger edges — use if the graph is too dense to read |
--skip name |
Exclude a project. Match is substring-based; pass the bare name, because cache dirs start with - and argparse reads that as a flag |
Report the headline numbers: total sessions, how many have transcripts vs. are history-only, edges, and cluster count.
Step 2: Name the unnamed clusters
obsidian-wiki sessions-clusters --unnamed --json
Each cluster comes with top_terms and exemplars (its three highest-degree sessions, whose
titles are already in graph.json). That is all you need. Do not open transcripts to name a
cluster — the whole design goal is that naming costs one turn regardless of corpus size.
Write a 3–5 word name and a one-sentence summary per cluster, then:
obsidian-wiki sessions-name --from - <<'EOF'
[{"id": 3, "name": "warden telemetry pipeline", "summary": "Building and debugging the redacted telemetry chain."}]
EOF
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 102 lines · 153 tokens per session scan A e72dc2189e2c
session-brain is a skill published in the GitHub repository Ar9av/obsidian-wiki (3,348 stars, last pushed 2d ago), licensed MIT. It adds 153 tokens to every session and 1,085 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
knowledge-base-management
Obsidian 知识库全生命周期管理：三层架构、素材入库(ABC分级)、健康检查、GBrain/GraphRAG/LLM Wiki 三件套集成、目录整理.
llm-wiki
Maintain a personal team knowledge base using the LLM Wiki pattern — incremental ingest, query, and lint operations on a layered wiki architecture.
llm-wiki
Build and maintain a persistent, interlinked Obsidian-compatible markdown wiki using Karpathy's LLM Wiki pattern. Extension-backed with auto-generated metadata, guardrails, and 14 custom tools (+3 opt-in agent-trajectory tools).
link-memory
Use after important user-approved decisions, when durable context should be proposed or reviewed, and for explicit Link memory lifecycle work: remember, recall, review, update, archive, restore, forget, or explain local memories through the CLI without requiring MCP.
link-retrieve
Use before answering work that may depend on user memory, project history, source-backed notes, or prior decisions; retrieve compact Link context through the CLI without loading the whole wiki or requiring MCP.
link-ingest
Use when raw files are present, source pages look stale, or a user asks to ingest notes into Link; refresh source-backed wiki pages, propose memories, and validate updates through the CLI without MCP.