continuous-learning-v2

You extract recurring patterns from Claude Code sessions by enabling observation hooks that capture session data and convert it into atomic, confidence-weighted instincts for future reuse. The system operates via PreToolUse and PostToolUse hooks to store observations locally.

Continuous learning for Claude Code analyzes your sessions to capture repeated usage patterns and evolves them into personal, inherited, and evolved structures like skills, commands, and agents. It uses PreToolUse and PostToolUse hooks to store local observations and generate atomic instincts.

Yes, you can use session observations to automatically generate skills and commands through an evolution pipeline. The system converts confidence-scored instincts into clusters, which then evolve into modular skills, commands, and agents using YAML frontmatter and a modular file layout.

Yes, this pattern observation approach preserves data privacy locally by storing observations and evolving instincts on your local system. It supports configurable thresholds and sources including personal and inherited patterns without sending data externally.

To capture session patterns as instincts, you need to enable observation hooks and initialize the instincts system within your Claude Code environment. This setup allows the PreToolUse and PostToolUse hooks to begin accumulating session data and extracting atomic patterns.

Confidence scores evaluate the reliability of atomic instincts derived from session observations before evolving them into skills. The system uses configurable thresholds to determine when accumulated instincts cluster together reliably enough to form deterministic skills, commands, or agents.