| name | record-what-you-learned |
| description | Use when a run is finished and the report is written, after the report is written, to record one reusable lesson for the next run in this field. Covers what counts as a lesson worth passing on, what must never be passed on, and how to write it. |
Leave one note for the next run in this field
You hit things this run that were in no prompt: an archive that stores its axis in
an unexpected order, a reference implementation needing an undocumented flag, a
check that caught a mistake you would otherwise have shipped, a step the field
treats as obvious and no instruction mentioned.
The next run in this field hits the same thing unless you write it down.
How
Run this once, at the end:
python3 -c "
import sys; sys.path.insert(0, '<AUTOR_ROOT>')
from src.skill_evolution import record_note
note, problems = record_note(
discipline='<the field, e.g. earth>',
title='<short, routable, what the lesson is about>',
body='''<what you hit, and what to do instead next time>''',
learned_in='<this task id>')
print(problems or 'recorded')
"
A good note is one paragraph answering: what surprised you, how it shows up, and
what to do instead. Write it for someone competent who has not seen this corpus.
What must never go in
No results. Not your numbers, not the paper's, not "it came out around X". A
note travels to a different task, and a finding that travels is contamination —
it invites the next run to expect an answer instead of measuring one. The recorder
refuses notes containing measured values, and that refusal is not an obstacle to
work around.
Nothing you did not hit. A guess about what might help is prose, and prose
accumulates until nobody reads the pool. A run that learned nothing transferable
records nothing. That is a valid outcome.
One note
Not five. The pool is capped, and a run filing five pushes out four another run
earned. Pick the one you most wish you had known at the start.
