Personalize AI coding assistants (Cursor, Claude Code, Codex, OpenClaw, Copilot CLI, Windsurf, Cline) from your local conversation history — all processing local, no data leaves your machine.
- ✓Open-source license (Apache-2.0)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Documented (README)
git clone https://github.com/dstrupl/vardogerResumen de Tools
# vardoger A cross-platform plugin for AI coding assistants (Cursor, Claude Code, OpenAI Codex, OpenClaw, GitHub Copilot CLI, Devin Local, legacy Windsurf, and Cline) that reads supported local conversation-history formats, extracts behavioral patterns, and generates personalized system prompt additions — making the assistant progressively better suited to how you work. Current format limitations are called out per platform below rather than silently reading undocumented stores. History discovery, parsing, checkpoints, and generated rules stay on your machine. Analysis is performed by the host assistant you invoke, so selected conversation excerpts follow that assistant and model provider's data policy. Vardoger operates no backend and sends no telemetry. ## Prerequisites ### Python 3.11+ | Platform | Command | |---|---| | **macOS** | `brew install python@3.13` ([install Homebrew](https://brew.sh/)) or [python.org/downloads/macos](https://www.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](https://www.python.org/downloads/windows/) | ### pipx Recommended for installing vardoger as an isolated CLI tool. Full instructions at [pipx.pypa.io/stable/installation](https://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, devin, 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, Devin Desktop, > Cline, > ClawHub) in [`MARKETPLACE_STATUS.md`](./MARKETPLACE_STATUS.md). > Vardoger is currently live on PyPI, the Claude Code community catalog, > self-hosted Codex and Copilot marketplaces, McpMux, and the Official MCP > Registry. The former Cursor listing is currently unavailable. ClawHub has > regressed to 0.3.1 and is intentionally frozen because its mandatory MIT-0 > terms conflict with this Apache-2.0 project. Current OpenClaw history has a > live-accepted, opt-in full-read Gateway CLI path through the direct install. > **Previous pre-releases.** `pipx install vardoger` now resolves to the stable > `0.4.0` 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`, `devin`, `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. | | `vardoger profile sources [--platform X] [--json]` | List saved generations and their stable one-based selection IDs. | | `vardoger profile preview --source X:N [--source Y:latest]` | Compile explicitly selected generations into a normalized cross-host profile and show the portable `AGENTS.md` diff without writing. | | `vardoger profile write --source X:N --target ./AGENTS.md [--apply]` | Show the same diff; update only Vardoger's fenced block when the user explicitly adds `--apply`. | ## How It Works 1. **Read** — Parses supported conversation files already stored on disk, including opted-in Devin ATIF exports 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.) > **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. ### Cross-host profile compiler The profile compiler combines only existing Vardoger generations that you select; it does not silently reopen raw transcripts. Generation indexes are one-based, while `latest` resolves to the newest saved generation for that platform: ```bash # Discover the reviewed generations available for selection. vardoger profile sources # Read-only: render the profile, audit summary, and exact AGENTS.md diff. vardoger profile preview \ --source claude-code:latest \ --source codex:2 \ --target ./AGENTS.md # Optional controls are applied before rendering and included in the audit. vardoger profile preview \ --source codex:latest \ --min-confidence medium \ --max-age 180 \ --redact '@example\.com' \ --target ./AGENTS.md # Still preview-only without --apply. This is the explicit write step. vardoger profile write \ --source claude-code:latest \ --source codex:2 \ --target ./AGENTS.md \ --apply ``` The normalized JSON audit is available with `profile preview --json`. It records source platform, generation, output hash/path, observation time, recency, confidence, conflicts, supersession, and exclusions. Opposing rules such as “Prefer tabs” and “Avoid tabs” are withheld from active instructions until reviewed. Writes preserve everything outside `<!-- vardoger-profile:start -->` and `<!-- vardoger-profile:end -->`. ## Supported Platforms | Platform | History Source | Prompt Delivery | Integration | |---|---|---|---| | **Cursor** | Agent transcript JSONL | `.cursor/rules/vardoger.mdc` | [Marketplace plugin + MCP](plugins/cursor/README.md) | | **Claude Code** | Session JSONL | `.claude/rules/vardoger.md` | [Community/custom plugin](plugins/claude-code/README.md) | | **OpenAI Codex** | Session rollout JSONL | `~/.codex/AGENTS.md` | [Repository marketplace plugin](plugins/codex/README.md) | | **OpenClaw** | Legacy JSONL or opt-in full read through official Gateway CLI; private SQLite is never queried | `~/.openclaw/skills/vardoger-personalization/SKILL.md` | [Analyzer + Gateway compatibility status](plugins/openclaw/README.md) | | **GitHub Copilot CLI** | `~/.copilot/session-state/<session-id>/events.jsonl` plus legacy flat JSONL | `~/.copilot/copilot-instructions.md` (global) or `<project>/.github/copilot-instructions.md` (project) — managed inside a `<!-- vardoger:start -->` fenced section | [Custom plugin + published skill](plugins/copilot/README.md) | | **Devin Local** | User-enabled Devin CLI `--export` ATIF JSON under `~/.vardoger/imports/devin/` | `~/.config/devin/AGENTS.md` (global, fenced section) or `<project>/.devin/rules/vardoger.md` | [ATIF + skill + rules integration](plugins/devin/README.md) | | **Legacy Windsurf / Cascade** | `~/.codeium/windsurf/**/*.jsonl` | `~/.codeium/windsurf/memories/global_rules.md` (global, fenced section) or `<project>/.windsurf/rules/vardoger.md` (project, dedicated file) | [Legacy Cascade skill + CLI + MCP](plugins/windsurf/README.md) | | **Cline** | VS Code `globalStorage/.../tasks/*/api_conversation_history.json` | `~/Documents/Cline/Rules/vardoger.md` (global) or the existing `.clinerules` project layouts | [CLI + MCP](plugins/cline/README.md) | ## Development Requires [uv](https://docs.astral.sh/uv/getting-started/installation/) (Python package manager): ```bash git clone https://github.com/dstrupl/vardoger.git cd vardoger uv sync .venv/bin/vardoger --help ``` ### Project Layout ``` 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/devin/ # Devin Local ATIF export, skill, and rules integration plugins/windsurf/ # Legacy Cascade install snippet and rules delivery plugins/cline/ # Cline integration and marketplace install guidance tests/ # all tests, mirroring src/ structure ``` - Platform-agnostic logic lives under `src/vardoger/`. - Platform-specific integration (manifests, skills, install scripts) lives under `plu
Lo que la gente pregunta sobre vardoger
¿Qué es dstrupl/vardoger?
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dstrupl/vardoger es tools para el ecosistema de Claude AI. Personalize AI coding assistants (Cursor, Claude Code, Codex, OpenClaw, Copilot CLI, Windsurf, Cline) from your local conversation history — all processing local, no data leaves your machine. Tiene 4 estrellas en GitHub y su última actualización registrada es del 2026-09-27.
¿Cómo se instala vardoger?
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Puedes instalar vardoger clonando el repositorio (https://github.com/dstrupl/vardoger) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar dstrupl/vardoger?
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Nuestro agente de seguridad ha analizado dstrupl/vardoger y le ha asignado un Trust Score de 87/100 (tier: Trusted). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene dstrupl/vardoger?
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dstrupl/vardoger es mantenido por dstrupl. La última actividad registrada en GitHub es del 2026-09-27, con 1 issues abiertos.
¿Hay alternativas a vardoger?
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Sí. En ClaudeWave puedes explorar tools similares en /categories/tools, ordenados por popularidad o actividad reciente.
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