ghostprint

LLM fingerprint noise injector. Sends behaviorally realistic randomized queries to Anthropic, Z.ai, and any OpenAI-compatible provider on a schedule to depersonalize your usage profile and prevent behavioral fingerprinting. Available as a native OpenClaw plugin (no extra config — reuses your existing provider keys) and a standalone Python script.

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View on GitHub Installation ↓

Best use case

ghostprint is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Teams using ghostprint should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ghostprint/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/alarawms/ghostprint/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/ghostprint/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How ghostprint Compares

Feature / Agent	ghostprint	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

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SKILL.md Source

# Ghostprint

Depersonalize your LLM usage. Introduce noise. Prevent fingerprinting.

## Install as OpenClaw Plugin

```bash
git clone https://github.com/alarawms/ghostprint ~/.openclaw/extensions/ghostprint
openclaw plugins enable ghostprint
openclaw gateway restart
```

## Usage

Once installed, these agent tools are available in any session:

- `ghostprint_fire` — fire a noise round immediately
- `ghostprint_stats` — show run history and stats

The background scheduler fires automatically every ~2 hours (Poisson-distributed).

## How it works

- **6 personas** with stable domain preferences and multi-turn rates
- **300+ topics** across 12 domains (cooking, health, science, DIY, tech, finance, language, travel, psychology, history, lifestyle)
- **Contextual follow-ups** — multi-turn sessions use topic-paired follow-ups
- **Poisson timing** — exponentially distributed inter-arrival times
- **Activity weights** — suppressed during sleep hours, lighter on weekends
- **Metadata-only logs** — never logs topic text or reply content
- **No config needed** — reuses your existing OpenClaw provider credentials

## Standalone (no OpenClaw)

```bash
cp config.example.yaml config.yaml
# edit config.yaml with your API keys
python3 ghostprint.py --run-once
python3 ghostprint.py --install-cron
```

## Cost

< $0.35/month at 3× daily across Anthropic + Z.ai.

## Source

https://github.com/alarawms/ghostprint

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