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Extracting reusable patterns from git history involves analyzing commits and diffs to identify recurring lessons. The skill codifies these findings into actionable instincts with confidence scoring, updating a shared knowledge base to accelerate future team iterations.

Building a team knowledge base from debugging sessions requires identifying patterns in tool usage and code changes. It converts these observations into codified instincts, reducing repeated effort and enabling faster problem resolution across the group.

You can automate knowledge management by reading existing instincts files alongside git diffs. The system gathers this evidence to produce updated pattern entries with traceable observations, automatically maintaining a living project catalog.

Pattern recognition works without external dependencies or components. It relies entirely on reading existing project evidence such as git history and tool observations to generate standalone instinct reports and update local catalog files.

You should run a pattern recognition workflow after completing a feature, bug fix, or end-of-session review. This timing ensures recent work evidence is fresh, allowing the system to accurately identify and codify new actionable instincts.