Add readability scoring (Flesch, Flesch-Kincaid, Fog, SMOG, ARI)#318
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Up to standards ✅🟢 Issues
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| Metric | Results |
|---|---|
| Complexity | 50 |
| Duplication | 0 |
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Summary
The text utilities canonicalise (
text_normalize), match (text_similarity,fuzzy) and rank (search_index) text, but nothing scores how hard it is to read. This adds the classic English readability formulae over a deterministic tokeniser and syllable heuristic, so a test can assert an on-screen message or label stays within a target reading grade.Layers
je_auto_control/utils/readability/readability.py—flesch_reading_ease,flesch_kincaid_grade,gunning_fog,smog_index,automated_readability_index,readability_report,readability_stats,count_syllables. Pure stdlib (re/math), no PySide6, pure functions.__all__.AC_readability_report→ full report.ac_readability_report.CommandSpecunder Data.Tests / docs
test/unit_test/headless/test_readability_batch.py— 9 headless tests (syllable heuristic incl. silent-e / consonant-le, stats counts, easy-vs-hard ordering, known Flesch value, empty-text zeros + wiring + facade).v110_features_doc.rst+ toctrees; 3 README What's-new sections.