vardoger

A cross-platform plugin for AI coding assistants (Cursor, Claude Code, OpenAI Codex, OpenClaw, GitHub Copilot CLI, Windsurf, Cline) that reads your conversation history, extracts behavioral patterns, and generates personalized system prompt additions — making the assistant progressively better suited to how you work.

All processing happens locally. No data ever leaves your machine.

Prerequisites

Python 3.11+

Platform	Command
macOS	brew install python@3.13 (install Homebrew) or python.org/downloads/macos
Debian / Ubuntu	sudo apt install python3
Fedora	sudo dnf install python3
Windows	winget install Python.Python.3.13 or python.org/downloads/windows

pipx

Recommended for installing vardoger as an isolated CLI tool. Full instructions at pipx.pypa.io/stable/installation.

Platform	Command
macOS	brew install pipx && pipx ensurepath
Debian / Ubuntu	sudo apt install pipx && pipx ensurepath
Fedora	sudo dnf install pipx && pipx ensurepath
Windows	scoop install pipx or pip install --user pipx && pipx ensurepath

Quick Start

pipx install vardoger
vardoger setup cursor        # or claude-code, codex, openclaw, copilot, windsurf, cline

Then tell your assistant: "Personalize my assistant."

Looking for the in-app plugin listings? Track review status for each marketplace (PyPI, Cursor, Claude Code, Codex, Copilot CLI, Windsurf, Cline, ClawHub) in MARKETPLACE_STATUS.md.

Previous pre-releases. pipx install vardoger now resolves to the stable 0.2.x line. The beta install paths below stay here for anyone still pinning an earlier release; new installs should not need them.

# opt into future pre-releases (0.2.0bN, etc.):
pipx install --pip-args="--pre" vardoger
# or pin an older pre-release:
pipx install vardoger==0.1.0b3
# or run without installing:
uvx vardoger --help

CLI Commands

Command	Purpose
vardoger setup <platform>	Register vardoger with a platform (cursor, claude-code, codex, openclaw, copilot, windsurf, cline).
vardoger status [--platform X] [--json]	Report whether each personalization is fresh or stale.
vardoger prepare --platform X [--batch N] [--synthesize]	Produce the batched prompts used by the AI-driven skill pipeline.
vardoger write --platform X	Read synthesized personalization from stdin and write it to the platform's rules file (supports YAML-frontmatter confidence metadata).
vardoger feedback accept|reject --platform X [--reason TEXT]	Record whether you kept or rejected the last generation. reject auto-reverts to the prior generation.
vardoger compare --platform X | --all [--window DAYS] [--json]	Compare heuristic conversation-quality metrics before vs. after the latest personalization.

How It Works

1. Read — Parses conversation history already stored on disk by each platform
2. Analyze — The host AI model identifies patterns in your communication style, tech stack, workflow, and preferences
3. Generate — Produces a system prompt addition tailored to you
4. Deliver — Writes the addition to the platform's native config (.cursor/rules/, .claude/rules/, AGENTS.md, etc.)

Supported Platforms

Platform	History Source	Prompt Delivery	Integration
Cursor	Agent transcript JSONL	.cursor/rules/vardoger.md	MCP server
Claude Code	Session JSONL	.claude/rules/vardoger.md	Plugin with skill
OpenAI Codex	Session rollout JSONL	~/.codex/AGENTS.md	Plugin with skill
OpenClaw	Session JSONL	~/.openclaw/skills/vardoger-personalization/SKILL.md

... View full README on GitHub