- Rename closing_style → closing_tendency in all 5 personas, making it
a soft preference rather than a hard constraint
- Add closing variation rule + 6 closing patterns table to writing-guide.md
- Step 4.5: LLM judges best closing from content; checks history.yaml
last 3 articles to avoid repeating the same closing_type
- Step 8.1: record closing_type in history.yaml for dedup
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Reorganize anti-AI rules into 3 tiers mapped to detector signals:
- Tier 1 (Statistical): sentence variance, vocab temperature, paragraph
rhythm, emotion polarity, adverb density, style drift
- Tier 2 (Linguistic): banned words, broken sentences, unexpected words,
coherence breaking
- Tier 3 (Content): real data anchoring, specificity, density waves,
dimension randomization
New rules added: emotion polarity distribution (1.4), adverb density
control (1.5), inter-paragraph style drift (1.6), unexpected word
usage (2.3). Each rule now references the detection signal it counters.
writing-config.example.yaml updated with corresponding new parameters.
SKILL.md Step 5 checklist aligned to new structure.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
