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v1.1.0 — Empirically calibrated humanization

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@kauenet kauenet released this 04 Jul 16:45
· 12 commits to main since this release

v1.1.0 — 2026-07-04

Empirically calibrated humanization (4 blind-judged rounds, 100+ adversarial agents):

  • Seams≠markers architecture: markers: budgets + context gates in the card; kaue.md §5b identity anti-triggers (biography exempt, named receipts win)
  • themes.md substance bank (receipted stances/anecdotes; no hyperspecific third-party names)
  • profiles/kaue/LESSONS.md — calibrated writing lessons, writer-loaded and binding for ALL routed blends (ROUTING guard + per-secondary guards)
  • Pipeline v2: mood + re-outline-in-voice, coordinator palettes, fresh-eyes reviser, long-form ledger, course mode (context-gated closers/openers)
  • Validator v2: density (marker budgets/gates), intra-doc audit, warmth telemetry, batch twin-scan, QA-machine/epigram/clipped-sentence checks
  • Golden regression outputs in testbed/accepted/ (check_round.py)
  • Calibration working data moved out of the repo (gitignored); knowledge absorbed into pack/rules