intelligence-learning

Detect user preference patterns and apply them to future command contexts.

18|7|Updated Mar 11, 2026

Search Tags:#personalization #ai #learning #pattern detection #preference learning #adaptive ai

Ready to run

npx skills add https://github.com/thecloudtips/founder-os --skill intelligence-learning

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: intelligence-learning
Source: https://github.com/thecloudtips/founder-os/tree/main/plugin/skills/infrastructure/intelligence-learning
Command: npx skills add https://github.com/thecloudtips/founder-os --skill intelligence-learning

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the process of learning and applying user preferences to improve AI interactions, reducing repetitive adjustments and enhancing personalization.

Core Features & Use Cases

Pattern Detection: Identifies recurring user behaviors and successful outcomes.
Preference Injection: Automatically incorporates learned insights into future command executions.
Confidence-Based Application: Gradually applies learned patterns based on a calculated confidence score.
Use Case: If a user consistently refines a generated report by asking for specific data points, this Skill will learn to include those data points by default in future reports.

Quick Start

Use the intelligence-learning skill to observe the current command's outcome and learn from it.

Frequently Asked Questions about intelligence-learning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate AI personalization to learn user preferences?▼

AI personalization is automated by implementing an adaptive learning cycle that detects recurring user behaviors and injects those learned preference patterns into subsequent command contexts.

How does confidence scoring work for adaptive AI pattern detection?▼

Confidence scoring for adaptive AI evaluates recurring user behaviors and successful outcomes, gradually applying learned preference patterns as instructions only when the calculated confidence score reaches a sufficient threshold.

How do I prevent repetitive adjustments in AI-generated reports?▼

Repetitive adjustments in AI-generated reports are prevented by preference learning, which identifies recurring refinements like specific data requests and automatically includes those data points by default in future executions.

What is the pattern lifecycle when managing user preference learning?▼

The pattern lifecycle in user preference learning transitions detected behaviors from candidate states to approved states, utilizing confidence scoring to validate and manage the integration of learned preferences into the AI context.

Can I integrate learned user preferences into existing command contexts?▼

Learned user preferences can be integrated into existing command contexts by automatically injecting approved preference patterns as instructions, enabling personalized AI behavior for subsequent command executions.