continuous-learning-v2

Capture Claude Code session events and generate confidence-weighted instincts.

Updated Feb 5, 2026
One-click install
npx skills add https://github.com/gugug168/claudecode-tutorial --skill continuous-learning-v2-gugug168
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: continuous-learning-v2
Source: https://github.com/gugug168/claudecode-tutorial/tree/main/everything-claude-code-learning/02-Skills/continuous-learning-v2
Command: npx skills add https://github.com/gugug168/claudecode-tutorial --skill continuous-learning-v2-gugug168

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts noisy, unreliable end-of-session skill extraction into precise, atomic learning units that can be automatically applied with confidence scores so that assistants learn useful behaviors reliably from interactions.

Core Features & Use Cases

  • Hook-based observation: Captures PreToolUse and PostToolUse events to record prompts, tool calls, and results for deterministic observation.
  • Atomic instincts: Creates minimal trigger-action instincts with confidence weights to apply small, reliable behaviors instead of large brittle skills.
  • Evolution workflows: Cluster related instincts into full skills, commands, or agents and support export/import for sharing and review.
  • Use case: Automatically learn a user's code style preferences, recurring debugging steps, or common workflow sequences and apply them when appropriate.

Quick Start

Enable PreToolUse and PostToolUse hooks pointing to the observe.sh hook so the system begins capturing session events and generating instincts for later review.

Frequently Asked Questions about continuous-learning-v2

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

FAQPage Schema
How do I capture Claude Code session activity to learn coding preferences?

Capture Claude Code session activity by enabling PreToolUse and PostToolUse hooks pointing to an observe.sh hook, which records prompts, tool calls, and results for deterministic observation of coding preferences.

What are atomic confidence-weighted instincts in continuous learning?

Atomic confidence-weighted instincts are minimal trigger-action behaviors with assigned confidence scores, designed to replace large brittle skills with small, reliable automated actions applied during interactions.

How do I automatically detect and apply recurring debugging patterns from AI sessions?

Automatically detect recurring debugging patterns by using a background observer to analyze logged PreToolUse and PostToolUse events, converting repeated workflows into atomic instincts with provenance for later application.

Does continuous learning require specific hook configurations for Claude Code?

Yes, continuous learning requires configuring PreToolUse and PostToolUse hooks directed at an observe.sh script to capture session events and generate instincts for review.

What is the best way to manage and share evolved micro-skills extracted from conversations?

Manage and share evolved micro-skills by clustering related instincts into full skills, commands, or agents, and using export and import workflows for sharing and review.

Why use atomic instincts instead of extracting large skills at the end of a session?

Atomic instincts solve the problem of noisy, unreliable end-of-session skill extraction by creating precise, minimal learning units that can be automatically applied with confidence scores for reliable behavior learning.