3 Commits

Author SHA1 Message Date
user
0e09ce4646 remove unfunny frequency exchange from lol section
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2026-03-04 15:23:04 -08:00
user
5c02cf8bde use actual em-dashes in checklist examples
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2026-03-04 15:19:25 -08:00
3ce000178f Merge pull request 'LLM prose tells: merge adjacent sentences, add checklist items' (#11) from llm-prose-tells-merge-pass into main
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Reviewed-on: #11
2026-03-05 00:13:49 +01:00

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@@ -307,9 +307,9 @@ introduces another.
### Pass 2: Sentence-Level Restructuring ### Pass 2: Sentence-Level Restructuring
10. Find every em-dash pivot ("not X...but Y," "not just X...Y," "more than 10. Find every em-dash pivot ("not Xbut Y," "not just XY," "more than X—Y")
X...Y") and rewrite it as two separate clauses or a single sentence that and rewrite it as two separate clauses or a single sentence that makes the
makes the point without the negation-then-correction structure. point without the negation-then-correction structure.
11. Find every colon elaboration and check whether it's doing real work. If the 11. Find every colon elaboration and check whether it's doing real work. If the
clause before the colon could be deleted without losing meaning, rewrite the clause before the colon could be deleted without losing meaning, rewrite the
@@ -443,12 +443,6 @@ roughly like this:
> >
> **model:** _(rewrites entire document without em-dashes while describing > **model:** _(rewrites entire document without em-dashes while describing
> em-dash overuse)_ > em-dash overuse)_
>
> **human:** this whole document seems to be making the case for FREQUENCY of
> use being important. we don't care about frequency, remove all that
> persuasion.
>
> **model:** _(strips out every "humans do this too but less often" comparison)_
The human compared this process to the deleted scene in Terminator 2 where John The human compared this process to the deleted scene in Terminator 2 where John
Connor switches the T-800's CPU to learning mode. The model compared it to a Connor switches the T-800's CPU to learning mode. The model compared it to a