| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1820 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 91.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1820 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "stomach" | | 1 | "silence" | | 2 | "flicked" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "stomach knotted" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 102 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 150 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 77 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1820 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 14.86% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 70 | | wordCount | 1036 | | uniqueNames | 11 | | maxNameDensity | 2.7 | | worstName | "Aurora" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Nia" | | discoveredNames | | Berwick | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Blackwood | 1 | | Silas | 9 | | Aurora | 28 | | Cardiff | 1 | | Nia | 23 | | Rain | 3 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Blackwood" | | 3 | "Silas" | | 4 | "Aurora" | | 5 | "Nia" | | 6 | "Rain" |
| | places | | 0 | "Berwick" | | 1 | "Street" | | 2 | "Cardiff" |
| | globalScore | 0.149 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1820 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 150 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 96 | | mean | 18.96 | | std | 21.91 | | cv | 1.156 | | sampleLengths | | 0 | 146 | | 1 | 4 | | 2 | 7 | | 3 | 21 | | 4 | 9 | | 5 | 3 | | 6 | 94 | | 7 | 1 | | 8 | 3 | | 9 | 3 | | 10 | 41 | | 11 | 8 | | 12 | 34 | | 13 | 13 | | 14 | 14 | | 15 | 13 | | 16 | 35 | | 17 | 9 | | 18 | 8 | | 19 | 3 | | 20 | 27 | | 21 | 12 | | 22 | 7 | | 23 | 12 | | 24 | 6 | | 25 | 6 | | 26 | 10 | | 27 | 28 | | 28 | 8 | | 29 | 13 | | 30 | 3 | | 31 | 10 | | 32 | 48 | | 33 | 3 | | 34 | 8 | | 35 | 26 | | 36 | 8 | | 37 | 4 | | 38 | 20 | | 39 | 8 | | 40 | 2 | | 41 | 2 | | 42 | 77 | | 43 | 32 | | 44 | 29 | | 45 | 8 | | 46 | 51 | | 47 | 7 | | 48 | 37 | | 49 | 9 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 102 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 186 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 150 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1042 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 11 | | adverbRatio | 0.01055662188099808 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 150 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 150 | | mean | 12.13 | | std | 10.13 | | cv | 0.835 | | sampleLengths | | 0 | 12 | | 1 | 16 | | 2 | 4 | | 3 | 10 | | 4 | 17 | | 5 | 4 | | 6 | 8 | | 7 | 10 | | 8 | 9 | | 9 | 6 | | 10 | 7 | | 11 | 5 | | 12 | 11 | | 13 | 14 | | 14 | 13 | | 15 | 4 | | 16 | 7 | | 17 | 21 | | 18 | 9 | | 19 | 3 | | 20 | 13 | | 21 | 7 | | 22 | 18 | | 23 | 8 | | 24 | 8 | | 25 | 16 | | 26 | 14 | | 27 | 7 | | 28 | 3 | | 29 | 1 | | 30 | 3 | | 31 | 3 | | 32 | 14 | | 33 | 7 | | 34 | 15 | | 35 | 5 | | 36 | 8 | | 37 | 10 | | 38 | 5 | | 39 | 19 | | 40 | 13 | | 41 | 7 | | 42 | 7 | | 43 | 13 | | 44 | 8 | | 45 | 7 | | 46 | 8 | | 47 | 6 | | 48 | 6 | | 49 | 9 |
| |
| 44.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.26 | | totalSentences | 150 | | uniqueOpeners | 39 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 100 | | matches | | 0 | "His grey-streaked auburn hair caught" | | 1 | "His beard held neat lines." | | 2 | "His hazel eyes lifted and" | | 3 | "His right hand, with its" | | 4 | "His left leg dragged a" | | 5 | "Her bright blue eyes swept" | | 6 | "She stamped rain from smart" | | 7 | "Her throat worked." | | 8 | "Her left sleeve rode up" | | 9 | "She yanked the cuff down." | | 10 | "She crossed the floor with" | | 11 | "Her charcoal suit held a" | | 12 | "She looked ten years past" | | 13 | "Her stomach knotted." | | 14 | "His signet ring flashed as" | | 15 | "She rose and reached for" | | 16 | "She walked to the door" | | 17 | "She looked back over her" | | 18 | "His ring clicked against the" |
| | ratio | 0.19 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 100 | | matches | | 0 | "Rain needled Berwick Street and" | | 1 | "A bus hissed past." | | 2 | "A sax moaned from a" | | 3 | "Aurora Carter pushed the door" | | 4 | "Heat wrapped round her." | | 5 | "Yeast and lemon and smoke" | | 6 | "Silas Blackwood stood behind the" | | 7 | "His grey-streaked auburn hair caught" | | 8 | "His beard held neat lines." | | 9 | "His hazel eyes lifted and" | | 10 | "His right hand, with its" | | 11 | "His left leg dragged a" | | 12 | "Aurora tugged her damp collar" | | 13 | "Silas reached for a clean" | | 14 | "Aurora slid onto a stool" | | 15 | "Her bright blue eyes swept" | | 16 | "A tall bookcase stood at" | | 17 | "A woman in red dozed" | | 18 | "The door swung in and" | | 19 | "She stamped rain from smart" |
| | ratio | 0.92 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |