recognize-pattern

You can recognize real-time patterns by running a Go-based CLI to observe behavioral, technical, thinking, relational, and error domains during work sessions, triggering learning when patterns crystallize for actionable insights.

Real-time pattern recognition for workflow learning loops surfaces recurring approaches across technical and behavioral domains before they become habits. It uses a configurable category and strength model to provide actionable insights, enabling timely adaptation during live sessions.

You configure pattern categories and strength thresholds by loading settings from a pattern-config.toml file. The CLI tooling reads this TOML configuration to apply a customizable category and strength model to your live observation sessions.

You can generate observation templates and journal insights from the command line. The CLI drives exploration by listing categories, viewing details, generating templates, and assessing pattern strength to support a seamless learning loop.

The pattern recognition CLI is Go-based and integrates a learning loop that allows you to reflect on sessions, journal insights, and optionally persist established patterns to memory for future reference.

Avoid real-time pattern recognition for error tracking if your work context lacks recurring live sessions or if you need post-hoc batch analysis rather than immediate, configurable strength-based observation and learning triggers.