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Personalize AI coding assistants by analyzing local conversation history. Runs on your machine.
Personalize AI coding assistants by analyzing local conversation history. Runs on your machine.
Vardoger is a well-architected personalization tool with proper authentication guards, careful input validation, and appropriate permission scoping for its purpose as a developer-focused AI assistant enhancement. Minor code quality concerns around error handling and path validation do not materially impact security. Supply chain analysis found 4 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
4 files analyzed · 9 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: VARDOGER_MCP_PLATFORM
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-dstrupl-vardoger": {
"env": {
"VARDOGER_MCP_PLATFORM": "your-vardoger-mcp-platform-here"
},
"args": [
"vardoger"
],
"command": "uvx"
}
}
}From the project's GitHub README.
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.
| 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 |
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 |
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 vardogernow resolves to the stable0.2.xline. 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
| 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. |
.cursor/rules/, .claude/rules/, AGENTS.md, etc.)| 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 | Skill |
| GitHub Copilot CLI | ~/.copilot/session-state/*.jsonl | ~/.copilot/copilot-instructions.md (global) or <project>/.github/copilot-instructions.md (project) — managed inside a `` fenced section | CLI-only |
| Windsurf | ~/.codeium/windsurf/**/*.jsonl | ~/.codeium/windsurf/memories/global_rules.md (global, fenced section) or <project>/.windsurf/rules/vardoger.md (project, dedicated file) | CLI-only |
| 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-only |
Requires uv (Python package manager):
git clone https://github.com/dstrupl/vardoger.git
cd vardoger
uv sync
.venv/bin/vardoger --help
src/vardoger/ # shared core — history reading, analysis, prompt generation
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
src/vardoger/.plugins/<platform>/.tests/, mirroring the source tree.See AGENTS.md for full coding standards and quality checks.
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.bandit -r src/ and pip-audit --skip-editable to catch common code smells and dependency CVEs.Run the full bundle locally before pushing:
uv run ruff check . && uv run ruff format --check . && uv run mypy src/ && uv run pytest --cov=vardoger --cov-fail-under=80
Contributions are welcome. Short version:
dstrupl/vardoger on GitHub and clone your fork.uv sync and create a topic branch.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.
CI runs automatically on every push and PR (lint, type check, tests across Python 3.11–3.13). To publish a new version:
version in pyproject.tomlmainv0.1.0), add a title and descriptionThe 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.
Public beta. The 0.3.x line is published on PyPI and actively maintained;
marketplace listings are rolling out per MARKETPLACE_STATUS.md.
See PRD.md for the full product requirements document.
Licensed under the Apache License, Version 2.0.
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