Surface prior learnings relevant to the current task. Use before starting any non-trivial work — new experiment, new feature, new submission strategy, debugging a pattern — to check if we've been here before. Also use when the user says "what have we learned about X", "any past notes on Y", "recall", or "check learnings".
The exact command may vary by repository. Check the README on GitHub.
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Recalling Prior Learnings
Surfaces the most relevant learnings from .learnings/ for the task at hand. This is the compound-interest mechanism — every session should call it before committing to an approach.
When to invoke proactively
Before:
Picking a modeling approach ("LightGBM vs CatBoost for tabular").
Designing a CV split strategy.
Writing submission glue code for a new competition.
Starting an agent's main decision loop.
Deciding a hyperparameter range.
Writing code t
[Description truncada. Veja o README completo no GitHub.]
