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style(no-slop): remove every em-dash + banned words across all modules + capstone

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Apply the no-ai-slop standard (now binding in AGENTS.md): the em-dash character is
banned outright (restructured, not blind-replaced), plus the banned word/phrase
list (delve, leverage, robust, seamless, truly, unlock, etc.). 0 em-dashes remain
in modules + capstone; the only "robust" left is the planted M10 ai-change.patch
trap. Module H1 titles use a colon separator.

All deliberate teaching devices preserved; labs compile/parse (py/sh/yaml/json);
no junk. AGENTS.md updated with the hard no-slop rules.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
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Claude (agent)
2026-06-22 23:21:09 -04:00
parent 513d7e7ac8
commit 389ac2e460
99 changed files with 1324 additions and 1315 deletions
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modules/27-evals/lab/candidates/swapped_model/tasks.py
+2 -2
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@@ -1,12 +1,12 @@
"""Candidate output: a SWAPPED model/prompt.
Same task, different model (or a tweaked prompt). This output "looks right" and
passes a casual manual check — adding three tasks and calling count returns 3.
passes a casual manual check; adding three tasks and calling count returns 3.
But pending_count() returns the total number of tasks, not the number of
*pending* ones, so it's wrong the moment anything is marked done.
Nobody would notice this by skimming. The eval set notices it instantly. That's
the regression eval catching an unsafe swap — exactly the scenario this module
the regression eval catching an unsafe swap, exactly the scenario this module
exists for. Replace this with your own swapped-model output when you run it for
real; you may get lucky and have it pass, or you may catch a regression like
this one.