nox-preference-learner

name	nox-preference-learner
description	Train your agent by talking. Detects approval/disapproval signals in conversations and builds a behavioral preference database. Injects learned preferences into agent context before each response. RLHF-lite without model fine-tuning — the agent adapts its behavior based on accumulated human feedback patterns.
license	MIT
compatibility	OpenClaw 2026.1.30+, Node.js >= 20

Preference Learner — Train by Talking

What It Does

Listens to your conversations and detects feedback signals:

• Positive: "perfekt", "genau so", "gut gemacht", "mach", 👍, 💪
• Negative: "wrong", "annoying", "stop that", "never again", "don't ask"
  Also detects German: "falsch", "nervt", "frag nicht"

Maps signals to 6 behavioral dimensions:

1. Autonomy — act independently vs. ask first
2. Verbosity — brief vs. detailed
3. Proactivity — suggest things vs. wait for instructions
4. Formality — casual vs. professional
5. Technical depth — show code vs. high-level summary
6. Confirmation seeking — just do it vs. check first

Each dimension has a score that increases/decreases with feedback and decays if not reinforced (30-day half-life). Strong, consistent feedback creates strong preferences. Occasional remarks create mild nudges.

How It Works

User says "Stop asking me every time, just do it!"
  → Signal: negative (-1.5)
  → Category: confirmation_seeking → LESS
  → Category: autonomy → MORE
  → Score updated, saved to preferences.json

Next session:
  → Plugin loads preferences.json
  → Injects: "STRONG preference for LESS confirmation seeking"
  → Agent adjusts behavior accordingly

Configuration

{
  "nox-preference-learner": {
    "enabled": true
  }
}

Preferences stored in: memory/preferences.json Log: memory/preference-learner.log