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

bash

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. Vardoger is currently live on PyPI, the Cursor Marketplace, the Claude Code community catalog, self-hosted Codex and Copilot marketplaces, ClawHub, McpMux, and the Official MCP Registry.

Previous pre-releases. pipx install vardoger now resolves to the stable 0.3.2 release. The beta install paths below stay here for anyone still pinning an earlier release; new installs should not need them.
bash
# 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

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

First run vs. incremental runs. By default vardoger does not apply a time window — the first run reads your full local history (that is when the signal is richest and a windowed default would silently drop older sessions you never get a second chance to feed in). After that, a per-conversation checkpoint store at ~/.vardoger/state.json ensures every subsequent run only reprocesses new or changed conversations, so refreshes stay fast. If you have very large local history and want to cap the first-run cost, pass --since DAYS (e.g. vardoger prepare --platform cursor --since 90); use --full to force a full re-crawl that bypasses the checkpoint.

Supported Platforms

Platform	History Source	Prompt Delivery	Integration
Cursor	Agent transcript JSONL	`.cursor/rules/vardoger.md`	Marketplace plugin + MCP
Claude Code	Session JSONL	`.claude/rules/vardoger.md`	Community/custom plugin
OpenAI Codex	Session rollout JSONL	`~/.codex/AGENTS.md`	Repository marketplace plugin
OpenClaw	Session JSONL	`~/.openclaw/skills/vardoger-personalization/SKILL.md`	Skill + ClawHub
GitHub Copilot CLI	`~/.copilot/session-state/*.jsonl`	`~/.copilot/copilot-instructions.md` (global) or `<project>/.github/copilot-instructions.md` (project) — managed inside a `<!-- vardoger:start -->` fenced section	Custom plugin + published skill
Windsurf	`~/.codeium/windsurf/*/.jsonl`	`~/.codeium/windsurf/memories/global_rules.md` (global, fenced section) or `<project>/.windsurf/rules/vardoger.md` (project, dedicated file)	Native skill + CLI + MCP
Cline	VS Code `globalStorage/.../tasks/*/api_conversation_history.json`	`<project>/.clinerules/vardoger.md` if `.clinerules` is a directory, otherwise a fenced section in `<project>/.clinerules` (project-only)	CLI + MCP

Development

Requires uv (Python package manager):

bash

git clone https://github.com/dstrupl/vardoger.git
cd vardoger
uv sync
.venv/bin/vardoger --help

Project Layout

Code

src/vardoger/          # shared core — history reading, analysis, prompt generation
.agents/plugins/       # repository-level Codex marketplace catalog
plugins/_shared/       # shared analysis/personalization skill authored once
plugins/cursor/        # Cursor MCP server config, install script
plugins/claude-code/   # Claude Code plugin manifest, skills
plugins/codex/         # Codex plugin manifest, skills
plugins/openclaw/      # OpenClaw skill
plugins/copilot/       # GitHub Copilot CLI plugin manifest, skills
plugins/windsurf/      # Windsurf install snippet and rules delivery
plugins/cline/         # Cline MCP-marketplace manifest + llms-install guide
tests/                 # all tests, mirroring src/ structure

Platform-agnostic logic lives under src/vardoger/.
Platform-specific integration (manifests, skills, install scripts) lives under plugins/<platform>/.
Tests live in tests/, mirroring the source tree.

See AGENTS.md for full coding standards and quality checks.

Quality gates

CI enforces a combined quality bar on every push and pull request:

ruff check / ruff format --check — lint (incl. complexity, pylint, return, pathlib, tryceratops rules) and formatting.
mypy src/ — strict type checking.
pytest --cov=vardoger --cov-fail-under=80 — tests across Python 3.11–3.13 with a combined 80% coverage floor.
A parallel security job runs bandit -r src/ and pip-audit --skip-editable to catch common code smells and dependency CVEs.

Run the full bundle locally before pushing:

bash

uv run ruff check . && uv run ruff format --check . && uv run mypy src/ && uv run pytest --cov=vardoger --cov-fail-under=80

Contributing

Contributions are welcome. Short version:

Fork dstrupl/vardoger on GitHub and clone your fork.
uv sync and create a topic branch.
Make your changes with tests and run the quality-gate one-liner above.
Push to your fork and open a PR against main.

CI (test on Python 3.11/3.12/3.13 plus a security job) will run automatically on the PR. First-time contributors may need a maintainer to click Approve and run before the first workflow execution.

See CONTRIBUTING.md for the full walkthrough and AGENTS.md for coding standards and commit-message conventions.

Releasing to PyPI

CI runs automatically on every push and PR (lint, type check, tests across Python 3.11–3.13). To publish a new version:

Bump the package, generated setup manifests, platform manifests, and registry metadata together; close the matching section in CHANGELOG.md.
Run the complete quality, security, plugin-validation, and build checks.
Commit and push to main, then wait for all required checks.
Create an annotated vX.Y.Z tag and publish the matching GitHub release.

The publish.yml workflow builds the package and uploads it to PyPI via trusted publishers (no API tokens needed). Once complete, pipx install vardoger will pull the new version.

Status

Public beta. Version 0.3.2 is published on PyPI and actively maintained. See MARKETPLACE_STATUS.md for live listings and the remaining official-directory submissions. See MANUAL_SUBMISSION_RUNBOOK.md for the owner-only submission, review, and publication steps. See PRD.md for the full product requirements document.

Privacy and security

PRIVACY.md — what vardoger reads, writes, and (importantly) does not send anywhere.
SECURITY.md — how to report a vulnerability privately.

License

Licensed under the Apache License, Version 2.0. See also the public Privacy Policy and Terms of Use.