Session Memory

A skill for persisting findings across skill runs so that future skills can compare, correlate, and build on what was previously discovered.

Output type: Memory file creation and recall. This skill writes structured session files and retrieves previous session data. It does not produce analysis — it provides the memory layer that other skills draw from.

Why this exists

Every skill in Design System Ops produces findings. But those findings are ephemeral — they exist in the conversation, get summarised, and then vanish. The next time someone runs token-audit, it starts from zero. It cannot tell you whether things got better or worse since last quarter. It cannot cross-reference what drift-detection found last month with what component-audit finds today.

Session Memory fixes this. It creates a structured memory layer that:

1. Saves findings from any skill run with timestamps, severity, and skill provenance
2. Recalls findings when a skill asks "what did we find before?"
3. Compares findings between runs to surface trends (improving, stable, worsening)
4. Correlates findings across skills to surface patterns that persist over time