Engram: A Learning Plugin for OpenClaw That Actually Makes Knowledge Stick

Engram is a learning plugin for OpenClaw that applies spaced repetition and retrieval practice to help developers actually retain knowledge. Built by someone who found that AI agents made him 10x faster at building but didn't improve his own learning speed, Engram focuses on the human side of the equation.

How It Works

• Topic breakdown: Run /learn kalman filters (or any topic) and an agent builds a dependency map — what must be understood before what — rather than following chapter order.
• Pre-test tutoring: You answer before the agent explains. Guessing wrong before being taught improves retention. Being made to retrieve beats rereading by a wide margin, per old findings that few tools implement.
• Blind grading: A second agent grades your answers without seeing the lesson — only the rubric and your exact words. This prevents the grader from grading the lesson instead of your recall. Every grade is written to disk as a receipt; nothing counts as learned without one.
• Spaced repetition: The scheduler uses FSRS-4.5 (the same algorithm behind modern Anki) to book each concept's next review just before you'd forget it. A /review session takes two to four minutes.
• Local only: All data is plain JSON on your machine. No account, no cloud, no network code in the engine.

OpenClaw Integration

Engram runs in OpenClaw chat, so /review can happen on your phone — where the schedule often sends reviews when you're away from a desk. Install with three commands:

openclaw plugins install engram --marketplace nagisanzenin/engram
openclaw config set hooks.internal.enabled true
openclaw gateway restart

Note: OpenClaw ignores plugin hooks until internal hooks are enabled. Without it, the due-review reminder sits listed as ready but never fires. The author notes that OpenClaw support shipped today and while skills, grading, and scheduling are verified on a live install, the reminder landing in every chat channel has only been tested locally.