llm-wiki

LLM Wiki — a second brain for AI agents

Turn PDFs, articles, transcripts, and notes into a shared wiki that your AI agents can search, cite, and keep up to date. Add a source once. Ask questions later. Keep the useful answers.

Works with Claude Code, Codex, Cursor, Gemini CLI, OpenCode, OpenClaw, Pi, OMP, and Hermes. Read the documentation.

What is LLM Wiki?

AI agents are good at the task in front of them, but a new session starts with limited context. LLM Wiki gives them a shared memory that can live in one personal wiki across all projects or inside a specific project.

When you add a source, the agent turns it into linked Markdown pages. Later, it can find the right section and answer with citations. Useful answers can be saved back into the wiki, so the knowledge grows instead of being rebuilt from scratch.

Everything canonical stays in readable Markdown. Default semantic search is local—no hosted vector database or embedding service.

What's new in v3.2.0

• Learn from completed work. /wiki:learn captures verified successes/failures and consolidates cited patterns, applicability and counterexamples.
• Turn evidence into tested procedures. /wiki:evolve runs training, evidence consolidation, whole-skill proposals, validation, and independent final testing, retaining rejected attempts. Adapters for nine supported agent hosts provide bounded runs, durable tool traces and cross-agent transfer; see the execution requirements.
• Explicit apply and rollback. Only a reviewed, passing change can be applied; whole-skill snapshot checks prevent overwriting intervening edits.
• Runnable evaluation examples. Separate training, validation and final-test tasks cover source-grounded answers and file artifacts, with calibrated judging, paired task-level analysis, and ingestion/graph/hybrid-search checks. Fictional fixtures stay outside the installed skill.
• Compatible upgrade. Existing Markdown and commands remain valid. /wiki:upgrade adds optional templates and archive guidance idempotently.

See Learning and skill evolution for the full workflow, evaluation limits and inference costs. This release adds tooling; it does not claim measured model gains.

The evolution workflow adapts WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution (Google Research and Virginia Tech, 2026): persistent experience-to-pattern learning, repeated skill proposals, retained failures, validation-only selection and independent final testing. See what we adapted and changed and the measured results. Our study rejected both proposals; no quality improvement was demonstrated.

Why use it?

• Stop repeating project context. Your agent can read the knowledge you already collected.
• Use the same wiki across agents. The files are plain Markdown, not tied to one model or tool.
• Trace every answer. Citations point back to the wiki page and original source.
• Keep the wiki healthy. The agent updates links, summaries, and contradictions as new sources arrive.
• Stay in control. Your pages remain readable, editable, and versionable.

LLM Wiki works best for knowledge that grows over time: research, meeting notes, customer calls, papers, articles, and project decisions. Use a regular database when your main problem is structured records and transactions.

Installation

uv is the only prerequisite: it creates the pinned script environments on every supported platform. Install it using the official uv instructions before running /wiki:init or the natural-language equivalent.

Plugin/skill installation copies all agent-facing commands and bundled tools. Wiki initialization then performs mandatory runtime setup: FastEmbed 0.8.0, sqlite-vec 0.1.9, PyYAML 6.0.3, the local BAAI/bge-small-en-v1.5 model, the parse cache, and vectors for every existing section. Upgrade runs the same setup again, incrementally synchronizing changed and deleted sections.

Claude Code — full plugin

The native path: the skill, the nine /wiki:* slash commands, and the marketplace manifest all ship in one install.

/plugin marketplace add praneybehl/llm-wiki-plugin
/plugin install llm-wiki@llm-wiki

Once installed, the plugin works in any project. Installation does not decide where your wiki lives.

Other coding agents — skill only

The llm-wiki skill uses the standard agentskills.io format, so it installs cleanly into any agent supported by the skills CLI. Pick the --agent flag that matches your setup:

# Install globally so the skill is available across all projects
npx skills add praneybehl/llm-wiki-plugin -a <agent> -g

# Or install into the current project only
npx skills add praneybehl/llm-wiki-plugin -a <agent>

OpenCode also reads .claude/skills/ and ~/.claude/skills/, so if you already installed the skill for Claude Code you can use it in OpenCode without a second install.

Hermes Agent (Nous Research), OMP ("Oh My Pi"), and other agentskills.io-compatible runtimes that aren't yet in the npx skills registry can still use this skill — clone the repo and symlink or copy skills/llm-wiki/ into the agent's skills directory. Hermes reads from ~/.hermes/skills/; OMP reads managed/user skills from ~/.omp/agent/skills/ and surfaces them via skill://.

git clone https://github.com/praneybehl/llm-wiki-plugin.git
mkdir -p ~/.hermes/skills ~/.omp/agent/skills
ln -s "$(pwd)/llm-wiki-plugin/skills/llm-wiki" ~/.hermes/skills/llm-wiki
ln -s "$(pwd)/llm-wiki-plugin/skills/llm-wiki" ~/.omp/agent/skills/llm-wiki

A few things to know when using the skill outside Claude Code:

• Slash commands are Claude Code-only. The nine /wiki:* commands live in commands/wiki/ as Claude Code plugin manifests. In other agents, invoke the skill by natural language ("add this paper to the wiki", "what does the wiki say about X", "lint the wiki") — the SKILL.md handles the rest.
• All bundled tools are agent-accessible. Every listed agent can invoke setup_wiki.py, hybrid/lexical search, lint, stats, graph lint/extract/query, and initialization through the installed skill. Dependency-bearing scripts carry pinned PEP 723 metadata and run with uv run --script; initialization and upgrade verify the full runtime before reporting readiness.
• The wiki itself is agent-agnostic. It's just a directory of markdown files. You can ingest with one agent and query with another; nothing in wiki/ ties it to a specific runtime.

Choose where the wiki lives

Skill scope and wiki scope are separate choices. A global skill install makes the skill available in every project; it does not create or select a global wiki.

• One personal wiki across projects: keep it at a stable user-level path such as ~/wiki/, keep raw