| name | engram-lessons |
| description | Record or reinforce an Engram lesson — the self-learning loop. Use when the user corrects a mistake, when an action failed in a generalizable way, when the user confirms an approach as right, or when you just applied a previously recalled lesson.
|
Lessons make you measurably better with this user over time, in any agent. CLI path is in the session-start conventions block.
Capture (§7.3 triggers)
Record when: the user corrected you; your action failed and a general check would have prevented it; the user confirmed "always do it this way".
Quality bar — apply before writing: would this lesson change behavior in a future session? One-off trivia (flaky network, typo) is not a lesson.
Body must follow this shape:
**Mistake:** <what went wrong, concrete>
**Why it happened:** <the assumption or missing check>
**How to apply:** <the behavior-changing rule for next time>
echo "<body>" | ENGRAM_AGENT=claude-code python3 "<engram_py>" add \
--type lesson --name kebab-case-slug \
--description "Discriminating one-liner recall can match" --tags ...
For a confirmed-good approach, same shape with Mistake: replaced by Approach:.
Reinforce (§7.4)
When a recalled lesson actually changed what you did this session:
python3 "<engram_py>" lesson applied <name>
This bumps times_applied (ranks it higher) and renews its expiry. Unapplied lessons lapse naturally — that is the decay model, don't fight it.
