continuous-learning-v2

Observation hooks track Claude Code session history to identify recurring tool usage and workflows, clustering them into reusable skills, commands, or agents. This builds a personalized knowledge base by analyzing interaction patterns and user corrections.

AI instincts are atomic patterns extracted from tool usage and prompts. Confidence scoring assigns levels to these learned behaviors, enabling gradual adoption so only repeated, verified workflows evolve into automated skills.

Yes, Python3 and Claude are required. You enable observation by adding a JSON snippet to your Claude settings, allowing the system to analyze tool usage and automatically generate commands like a debug workflow.

Yes, custom AI agents can be created automatically from error resolutions. The system observes error resolutions and user corrections, clustering these learned instincts into reusable agents based on unique workflows.

The best way is letting the system observe specific command sequences. It automatically encapsulates those steps into a new command, generating a personalized skill from your workflow.

Automatically generated AI skills might miss workflow patterns if observation hooks are not properly enabled in your settings JSON, preventing the system from analyzing tool usage and assigning confidence scores to recurring behaviors.