From Agent Memory to Portable Skills

An agent accumulates hard-won procedural knowledge inside a single workspace and single context window: how to triage a P1 incident, which tool to call first, or what “done” looks like. This learned experience captures how your organization actually gets things done, but open a fresh session and the agent starts cold. NAMS (Neo4j Agent Memory Service) gives agents persistent, graph-based memory, so a new session can look up what happened. But recall is not capability: knowing how last month’s P1 triage went does not hand the next agent the procedure to triage the next incident. This post is about the transformation that closes that gap: skill distillation, turning a scoped slice of a workspace’s memory graph into a portable, provenance-grounded Agent Skill (a SKILL.md package) an agent can load and run. Skill distillation produces knowledge your agents can act on, an artifact they load at runtime, and a governance loop that keeps both honest. Agents work, memory grows, a scope is distilled into a skill, and the next agent loads…