LLM Wiki Agent is a coding-agent workflow that reads source documents and builds a persistent, interconnected wiki from the extracted knowledge. It is for people who want an agent to maintain a structured knowledge base from materials such as documents, web pages, and data files. The catalogue entries provide commands and instructions for ingesting, querying, checking, and visualizing that wiki.
Borrowing it
Nothing to install: this file belongs to SamurAIGPT/llm-wiki-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SamurAIGPT/llm-wiki-agent/main/GEMINI.mdgit clone --depth 1 https://github.com/SamurAIGPT/llm-wiki-agentWrote 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/instructions/samuraigpt/llm-wiki-agent/gemini-md)<a href="https://agentmods.dev/instructions/samuraigpt/llm-wiki-agent/gemini-md"><img src="https://agentmods.dev/badge/instructions/samuraigpt/llm-wiki-agent/gemini-md/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/instructions/samuraigpt/llm-wiki-agent/gemini-md"><img src="https://agentmods.dev/badge/instructions/samuraigpt/llm-wiki-agent/gemini-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.01590 | $0.01590 |
| Opus 5 | $0.00795 | $0.00795 |
| Sonnet 5 | $0.00318 | $0.00318 |
| Haiku 4.5 | $0.00159 | $0.00159 |
Grade A, and why
llm-wiki-agent GEMINI.md 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 9d 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Wiki Agent — Schema & Workflow Instructions
This wiki is maintained entirely by Gemini CLI. No API key or Python scripts needed — just open this repo with gemini and talk to it.
How to Use
Describe what you want in plain English:
- "Ingest this file: raw/papers/my-paper.md"
- "What does the wiki say about transformer models?"
- "Check the wiki for orphan pages and contradictions"
- "Build the knowledge graph"
Or use shorthand triggers:
ingest <file>→ runs the Ingest Workflowquery: <question>→ runs the Query Workflowhealth→ runs the Health Workflow (fast, every session)lint→ runs the Lint Workflow (expensive, periodic)build graph→ runs the Graph Workflow
Directory Layout
raw/ # Immutable source documents — never modify these
wiki/ # Agent owns this layer entirely
index.md # Catalog of all pages — update on every ingest
log.md # Append-only chronological record
overview.md # Living synthesis across all sources
sources/ # One summary page per source document
entities/ # People, companies, projects, products
concepts/ # Ideas, frameworks, methods, theories
syntheses/ # Saved query answers
graph/ # Auto-generated graph data
tools/ # Standalone Python scripts
health.py # Structural checks (deterministic, no LLM calls)
lint.py # Content quality checks (uses LLM for semantic analysis)
build_graph.py # Knowledge graph generation
Page Format
Every wiki page uses this frontmatter:
---
title: "Page Title"
type: source | entity | concept | synthesis
tags: []
sources: []
last_updated: YYYY-MM-DD
---
Use [[PageName]] wikilinks to link to other wiki pages.
Ingest Workflow
Triggered by: "ingest "
Supported formats: .md ingested directly. Non-markdown files (.pdf, .docx, .pptx, .xlsx, .html, .txt, .csv, .json, .xml, .rst, .rtf, .epub, .ipynb, .yaml, .yml, .tsv, .wav, .mp3) auto-converted via markitdown. Use --no-convert to skip.
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.
- 9d ago First seen · 233 lines · 1,590 tokens per session scan A f863d4f5104d
llm-wiki-agent GEMINI.md is an instructions file published in the GitHub repository SamurAIGPT/llm-wiki-agent (3,497 stars, last pushed 2d ago), licensed MIT. It adds 1,590 tokens to every session, about $0.0080 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 instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.