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 skills add Ar9av/obsidian-wiki --skill wiki-importgit 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/wiki-import)<a href="https://agentmods.dev/skills/ar9av/obsidian-wiki/wiki-import"><img src="https://agentmods.dev/badge/skills/ar9av/obsidian-wiki/wiki-import/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ar9av/obsidian-wiki/wiki-import"><img src="https://agentmods.dev/badge/skills/ar9av/obsidian-wiki/wiki-import.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 5.1 | $0.00108 | $0.03881 |
| Opus 5 | $0.00054 | $0.01940 |
| Sonnet 5 | $0.00022 | $0.00776 |
| Haiku 4.5 | $0.00011 | $0.00388 |
Grade A, and why
wiki-import 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- beeweave-import — 91% identical, 35 lines differ
How it starts
The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Import — Reconstruct Pages from an Export
You are importing a vault's knowledge into the current vault from one of two sources produced by wiki-export:
graph.json— the graph skeleton. Reconstructs page stubs (frontmatter, typed relationships, a## Relatedlink list — no body). Lossy.- OKF bundle (a
wiki-export/okf/directory) — the actual markdown files. Reconstructs full pages with their real bodies. Lossless. Use this for true vault-to-vault transfer.
Either way, the import writes pages with correct frontmatter and wikilinks, then updates all vault metadata. Step 2, Step 3 (graph only), and Step 5 are shared; Step 4 forks by source type.
Before You Start
Writing profile: Before drafting or rewriting natural-language Markdown, read and apply the Writing Profile Resolution section in llm-wiki/SKILL.md. Framework schema, provenance, safety, and operation-specific requirements take precedence.
Preserve imported source prose; apply WRITING.md preferences only to newly generated metadata or stubs.
- Resolve config — follow the Config Resolution Protocol in
llm-wiki/SKILL.md(inline@nameoverride → walk up CWD for.env→ global config → prompt setup). This givesOBSIDIAN_VAULT_PATH. - Read
$OBSIDIAN_VAULT_PATH/AGENTS.mdif it exists — apply any owner-specific conventions.
Step 1: Locate and Detect Source Type
Find the import source:
- If the user provided a path argument, use it directly.
- Otherwise auto-detect, in order:
./wiki-export/okf/(a directory) →./wiki-export/graph.json(a file). - If neither exists, ask the user for the path.
Detect the source type:
- The path is a file ending in
.json→ graph.json import (validate below, then Step 3 + Step 4-Graph). - The path is a directory containing
.mdfiles with OKF frontmatter (atype:key), and/or a rootindex.mdwithokf_version→ OKF bundle import (skip Step 3; go to Step 4-OKF). - Anything else → report what's wrong and stop.
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.
- 10d ago First seen · 277 lines · 108 tokens per session scan A def1fa89c943
wiki-import is a skill published in the GitHub repository Ar9av/obsidian-wiki (3,378 stars, last pushed 3d ago), licensed MIT. It adds 108 tokens to every session and 3,881 once invoked, about $0.0005 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
A lifecycle system for managing an Obsidian knowledge base, which is a folder of linked notes. It organizes raw material, AI-maintained wiki pages, and generated views into separate layers.
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.