learning-evolution

What problem does it solve?

This skill helps teams convert experiential signals into reusable knowledge assets by guiding a structured reflection and codification process, turning messy notes into stable outputs.

Core Features & Use Cases

• Two-stage workflow: Observation -> Selection -> Representation, with optional Evolution when requested.
• Writes outcomes to project context or long-term assets (.learned/rules.md, .learned/support.md, or target assets).
• Supports templates and reference guidance for consistent learning articulation.

Quick Start

Activate Learning Evolution to extract a valuable signal from this session and write a concise entry to the appropriate place (.learned or a formal asset) based on user direction.