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/llm-wikinpx skills add Ar9av/obsidian-wiki --skill llm-wikigit clone --depth 1 https://github.com/Ar9av/obsidian-wikiWhat 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 | $0.00113 | $0.09009 |
| Opus 5 | $0.00056 | $0.04505 |
| Sonnet 5 | $0.00023 | $0.01802 |
| Haiku 4.5 | $0.00011 | $0.00901 |
Grade A, and why
llm-wiki 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 today.
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 — 657 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Wiki — Knowledge Distillation Pattern
You are maintaining a persistent, compounding knowledge base. The wiki is not a chatbot — it is a compiled artifact where knowledge is distilled once and kept current, not re-derived on every query.
Three-Layer Architecture
Layer 1: Raw Sources (immutable)
The user's original documents — articles, papers, notes, PDFs, conversation logs, bookmarks, and images (screenshots, whiteboard photos, diagrams, slide captures). These are never modified by the system. They live wherever the user keeps them (configured via OBSIDIAN_SOURCES_DIR in .env). Images are first-class sources: the ingest skills read them via the Read tool's vision support and treat their interpreted content as inferred unless it's verbatim transcribed text. Image ingestion requires a vision-capable model — models without vision support should skip image sources and report which files were skipped.
Think of raw sources as the "source code" — authoritative but hard to query directly.
Don't confuse this with the in-vault _raw/ staging folder, which is a different thing: a scratch inbox for quick captures and drafts awaiting promotion (see wiki-capture and wiki-ingest). Files there aren't Layer 1 sources, but wiki-ingest still moves rather than deletes them on promotion, since some have no other copy.
Layer 2: The Wiki (LLM-maintained)
A collection of interconnected Obsidian-compatible markdown files organized by category. This is the compiled knowledge — synthesized, cross-referenced, and navigable. Each page has:
- YAML frontmatter (title, category, tags, sources, timestamps)
- Obsidian
[[wikilinks]]connecting related concepts - Clear provenance — every claim traces back to a source
The wiki lives at the path configured via OBSIDIAN_VAULT_PATH in .env.
Layer 3: The Schema (this skill + config)
The rules governing how the wiki is structured — categories, conventions, page templates, and operational workflows. The schema tells the LLM how to maintain the wiki.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today Changed · +4 lines e0e01f88e1a6
- yesterday First seen · 653 lines · 113 tokens per session scan A 2debf9365116
llm-wiki is a skill published in the GitHub repository Ar9av/obsidian-wiki (3,325 stars, last pushed today), licensed MIT. It adds 113 tokens to every session and 9,009 once invoked, about $0.0006 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
deeprefine
Agent-native DeepRefine refinement loop — same control flow as DeepRefine.refine(), graphify search instead of FAISS, session LLM, dry-run review before approved graph writes.
deeprefine
Agent-native DeepRefine refinement loop — same control flow as DeepRefine.refine(), graphify search instead of FAISS, session LLM, dry-run review before approved graph writes.
deeprefine
Claude Code adapter for the DeepRefine agent-native refinement loop. Use when the user invokes /deeprefine, or asks to refine, diagnose, review, or apply changes to a Graphify / LLM-Wiki knowledge graph. Must follow the canonical DeepRefine skill rules and stop for review before graph writes.
binder-modeling
Binder data modeling — define entity types, fields, relations, constraints, views, and navigation. Use when asked to "create a type", "add a field", "define a schema", "set up relations", "model entities", "create a view", "set up navigation", "render entities as files", or design a binder workspace schema.
binder-app
Build a small HTTP app (dashboard, kanban board, admin panel, custom UI) on top of an existing Binder workspace. Use when asked to "create an app", "build a dashboard", "show records in a chart", "make a kanban/board", "build an admin panel", or "add a UI on top of binder".
binder-cli
Binder CLI for knowledge graph operations — CRUD, search, schema inspection, transaction import, docs rendering. Use when asked to "query binder", "search records", "create a record", "check the schema", "import transactions", "undo changes", or work with a binder workspace.