Reusable Skills from Real Coding-Agent Sessions
Successful workflows, edge cases, and pitfalls should survive after the task ends.
A scheduled host adapter captures new session messages and tool calls. The coding agent reviews related skills, then decides whether to do nothing, patch an existing skill, or create new Markdown. memU stores the result and indexes its name and description for later retrieval.

What Long-Term Memory Can Do for AI Coding
- Captures new messages and tool calls from the host agent’s own session history
- Prepares self-contained jobs with the paths and context the agent needs
- Keeps judgment inside the coding agent: no change, patch a skill, or create a new one
- Stores readable skill Markdown with a searchable name and description
- Retrieves relevant skills by embedding similarity before a similar future task
- Shares the same skill backend across Codex, Claude Code, Cursor, and other configured hosts
Where Coding Skills Compound
Skills work best when they preserve verified procedures and lessons that would otherwise be rediscovered in another session.
Start Compounding Skills Across Coding Agents
Give your agent the canonical memU skill. It identifies the right host adapter, configures one shared memory backend, and verifies both memorization and retrieval.
Let Proven Workflows Survive the Session
Install memU in your coding agent, capture real outcomes, and retrieve the right skill when a similar task appears again.