LLM Wiki is a system that uses AI agents to research sources, compile knowledge bases, organize project briefs, and answer questions from the resulting wiki. It is used to turn rough ideas and investigations into structured, reusable knowledge for agents, including Claude Code, Codex, and OpenCode. The catalogue entries are commands, hooks, skills, instructions, and a plugin that implement its workflow.
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.
git clone --depth 1 https://github.com/nvk/llm-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/plugins/nvk/llm-wiki/claude-plugin)<a href="https://agentmods.dev/plugins/nvk/llm-wiki/claude-plugin"><img src="https://agentmods.dev/badge/plugins/nvk/llm-wiki/claude-plugin/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/plugins/nvk/llm-wiki/claude-plugin"><img src="https://agentmods.dev/badge/plugins/nvk/llm-wiki/claude-plugin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
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 14d 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.
What it actually says
{
"name": "wiki",
"description": "LLM-compiled knowledge base with Project Knowledge Checkpoints Export, personal specialist skills, trusted adapters, Idea-to-Project workflows, compact queries, inventory, datasets, ingestion, audits, sessions, research, and outputs.",
"version": "0.25.1",
"author": {
"name": "nvk"
},
"license": "MIT",
"keywords": [
"wiki",
"knowledge-base",
"llm",
"markdown",
"research",
"thesis",
"obsidian",
"karpathy",
"audit",
"librarian",
"schema",
"topic-guide",
"collect",
"inventory",
"ideas",
"projects",
"checkpoints",
"knowledge-handoff",
"adapters",
"private-adapters",
"specialists",
"personal-skills",
"datasets",
"archive",
"sessions",
"feedback",
"hooks",
"context"
]
}
What it installs
The manifest is a name and a version. 1 skill, 28 commands travel with it, and installing the plugin installs all of them — 1,018 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill wiki-manager A 153 tokens
- Command research A 47 tokens
- Command wiki A 76 tokens
- Command collect A 32 tokens
- Command ingest-collection A 31 tokens
- Command ingest A 34 tokens
- Command librarian A 35 tokens
- Command plan A 40 tokens
- Command ll A 31 tokens
- Command assess A 24 tokens
- Command checkpoint A 24 tokens
- Command output A 33 tokens
- Command refresh A 24 tokens
- Command retract A 29 tokens
- Command adapter A 27 tokens
- Command session A 32 tokens
- Command specialist A 20 tokens
- Command feedback A 15 tokens
- Command inventory A 34 tokens
- Command lint A 28 tokens
- Command audit A 33 tokens
- Command dataset A 30 tokens
- Command archive A 36 tokens
- Command compile A 20 tokens
- Command idea A 18 tokens
- Command query A 31 tokens
- Command portfolio A 20 tokens
- Command thesis A 25 tokens
- Command project C 36 tokens
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.
- 14d ago Changed dc80e01217e5
- 1mo ago Changed c4c9ef24010d
- 1mo ago First seen · 40 lines scan A 873d0b85c28c
wiki is a plugin published in the GitHub repository nvk/llm-wiki (1,422 stars, last pushed 14d ago), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. 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 plugins, from other repositories
yait-aichain
The provider-agnostic AI toolkit for Python — pipelines, fan-outs and tool-using agents on any model provider.
behavioral-ecologist
Reasons from versioned ethograms, Altmann focal/scan sampling, and activity budgets; scores with BORIS (Cohen’s κ), analyzes sequences with Markov/HMM tools, runs sham-controlled playbacks under ARRIVE 2.0, and fits GLMMs on the correct experimental unit while treating pseudoreplication, spatial autocorrelation, and…
dx
Developer experience essentials: GitHub Actions debugging, conversation half/quarter-cloning, context handoffs, research (Reddit and Hacker News), private GitHub search, and Claude Code version checks.
fw-app-dev
Expert-level skill for building, debugging, reviewing, and migrating Freshworks Platform 3.0 custom apps.
developer-toolkit
Complete developer productivity toolkit: Git mastery, debugging skills, code intelligence, AI-assisted development, and best practices for modern software engineering.
humanizer
Rewrite AI-sounding text so it reads like the writer without changing what it says.