continuous-learning

Create confidence-weighted instincts from AI coding session observations.

Updated Mar 11, 2026
One-click install
npx skills add https://github.com/yzlin/supa-opencode --skill continuous-learning-yzlin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: continuous-learning
Source: https://github.com/yzlin/supa-opencode/tree/main/skills/continuous-learning
Command: npx skills add https://github.com/yzlin/supa-opencode --skill continuous-learning-yzlin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms your AI coding sessions into a continuous learning loop, automatically identifying patterns in your workflow and generating reusable "instincts" that improve AI performance and consistency over time.

Core Features & Use Cases

  • Automatic Pattern Detection: Observes your interactions (tool use, corrections, error resolutions) to find recurring behaviors.
  • Instinct Creation: Generates atomic, confidence-scored "instincts" (e.g., "prefer functional style," "validate user input") based on observed patterns.
  • Project Scoping: Keeps instincts project-specific to avoid cross-contamination (e.g., React patterns stay in React projects).
  • Evolution: Clusters instincts into higher-level skills, commands, or agents.
  • Use Case: As you code, the system learns your preferred coding styles, common debugging steps, and efficient tool usage, then automatically suggests or applies these learned behaviors in future sessions, making the AI more tailored to your needs.

Quick Start

Activate the continuous learning system to observe your current coding session and begin building project-specific instincts.

Frequently Asked Questions about continuous-learning

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

FAQPage Schema
How does AI learn from my coding sessions to improve workflow automation?

AI learns from coding sessions by using plugin hooks to observe tool usage and user corrections, detecting recurring patterns to generate confidence-weighted instincts that automate future workflows.

How do I build project-specific AI instincts for recurring coding patterns?

Build project-specific AI instincts by activating the continuous learning system to observe interactions, automatically creating atomic, confidence-scored instincts stored in YAML files within that project's scope.

What is the best way to prevent cross-contamination of learned patterns across different projects?

Prevent pattern cross-contamination by using project-specific scoping, which confines observed instincts like React patterns to their original project rather than applying them globally.

Can I evolve learned coding instincts into higher-level commands or agents?

Evolve learned coding instincts into higher-level skills, commands, or agents by clustering related atomic instincts together and managing them through provided Python scripts and a CLI.

Do I need Python and YAML to manage AI instincts generated from my sessions?

Python scripts and a CLI are required to manage and evolve the generated instincts, which are persisted as structured data in YAML files for confidence-weighted workflow automation.