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-history-ingestgit 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-history-ingest)<a href="https://agentmods.dev/skills/ar9av/obsidian-wiki/wiki-history-ingest"><img src="https://agentmods.dev/badge/skills/ar9av/obsidian-wiki/wiki-history-ingest/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-history-ingest"><img src="https://agentmods.dev/badge/skills/ar9av/obsidian-wiki/wiki-history-ingest.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 | $0.00076 | $0.00640 |
| Opus 5 | $0.00038 | $0.00320 |
| Sonnet 5 | $0.00015 | $0.00128 |
| Haiku 4.5 | $0.00008 | $0.00064 |
Grade A, and why
wiki-history-ingest 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 12d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unified History Ingest Router
This is a thin router for history sources only. It does not replace wiki-ingest for documents.
Subcommands
If the user invokes /wiki-history-ingest <target> (or equivalent text command), dispatch directly:
| Subcommand | Route To |
|---|---|
claude |
claude-history-ingest |
copilot |
copilot-history-ingest |
codex |
codex-history-ingest |
hermes |
hermes-history-ingest |
openclaw |
openclaw-history-ingest |
pi |
pi-history-ingest |
auto |
infer from context using rules below |
Routing Rules
- If the user explicitly says
claude,copilot,codex,hermes,openclaw, orpi, route directly. - If the user provides a path/source:
~/.claudeor Claude memory/session JSONL artifacts ->claude-history-ingest~/.copilot,session-store.db, VS Code copilot-chat transcripts ->copilot-history-ingest~/.codexor rollout/session index artifacts ->codex-history-ingest~/.hermesor Hermes memories/session artifacts ->hermes-history-ingest~/.openclawor OpenClaw MEMORY.md/session JSONL artifacts ->openclaw-history-ingest~/.pi/agent/sessionsor Pi session JSONL artifacts ->pi-history-ingest
- If ambiguous, ask one short clarification:
- "Should I ingest
claude,copilot,codex,hermes,openclaw, orpihistory?"
- "Should I ingest
Execution Contract
- After routing, execute the destination skill's workflow exactly.
- Do not duplicate destination logic in this file.
- Leave manifest/index/log update semantics to the destination skill.
UX Convention
- Use
wiki-ingestfor documents/content sources - Use
wiki-history-ingestfor agent history sources
Examples:
/wiki-history-ingest claude/wiki-history-ingest copilot/wiki-history-ingest codex/wiki-history-ingest hermes/wiki-history-ingest openclaw/wiki-history-ingest pi$wiki-history-ingest claude(agents that use$skillinvocation)$wiki-history-ingest copilot
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.
- 12d ago First seen · 62 lines · 76 tokens per session scan A 30a8607ed79c
wiki-history-ingest is a skill published in the GitHub repository Ar9av/obsidian-wiki (3,393 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 640 once invoked, about $0.0004 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.