| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.431 | | leniency | 0.863 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1152 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 34.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1152 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "electric" | | 1 | "shattered" | | 2 | "blown wide" | | 3 | "familiar" | | 4 | "chill" | | 5 | "echoed" | | 6 | "measured" | | 7 | "facade" | | 8 | "calculating" | | 9 | "etched" | | 10 | "magnetic" | | 11 | "reverberated" | | 12 | "flickered" | | 13 | "gloom" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "clenched right fist" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 78 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1152 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 790 | | uniqueNames | 9 | | maxNameDensity | 2.53 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Eva" | | discoveredNames | | Camden | 1 | | Victorian | 1 | | Constable | 1 | | Vance | 8 | | Quinn | 20 | | Morris | 2 | | Blackfriars | 1 | | Eva | 11 | | Kowalski | 1 |
| | persons | | 0 | "Camden" | | 1 | "Constable" | | 2 | "Vance" | | 3 | "Quinn" | | 4 | "Morris" | | 5 | "Eva" | | 6 | "Kowalski" |
| | places | | | globalScore | 0.234 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1152 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 19.53 | | std | 14.4 | | cv | 0.738 | | sampleLengths | | 0 | 15 | | 1 | 31 | | 2 | 37 | | 3 | 12 | | 4 | 30 | | 5 | 16 | | 6 | 35 | | 7 | 30 | | 8 | 40 | | 9 | 5 | | 10 | 2 | | 11 | 20 | | 12 | 8 | | 13 | 39 | | 14 | 28 | | 15 | 19 | | 16 | 4 | | 17 | 5 | | 18 | 57 | | 19 | 9 | | 20 | 18 | | 21 | 55 | | 22 | 13 | | 23 | 8 | | 24 | 32 | | 25 | 37 | | 26 | 5 | | 27 | 31 | | 28 | 21 | | 29 | 26 | | 30 | 21 | | 31 | 26 | | 32 | 7 | | 33 | 13 | | 34 | 8 | | 35 | 2 | | 36 | 12 | | 37 | 38 | | 38 | 14 | | 39 | 8 | | 40 | 2 | | 41 | 27 | | 42 | 18 | | 43 | 18 | | 44 | 1 | | 45 | 2 | | 46 | 20 | | 47 | 28 | | 48 | 3 | | 49 | 48 |
| |
| 96.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 78 | | matches | | 0 | "was dressed" | | 1 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 142 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 794 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.018891687657430732 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.011335012594458438 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 10.77 | | std | 6.47 | | cv | 0.601 | | sampleLengths | | 0 | 15 | | 1 | 16 | | 2 | 15 | | 3 | 19 | | 4 | 18 | | 5 | 6 | | 6 | 6 | | 7 | 3 | | 8 | 27 | | 9 | 14 | | 10 | 2 | | 11 | 9 | | 12 | 15 | | 13 | 11 | | 14 | 14 | | 15 | 16 | | 16 | 2 | | 17 | 15 | | 18 | 16 | | 19 | 7 | | 20 | 5 | | 21 | 2 | | 22 | 5 | | 23 | 15 | | 24 | 4 | | 25 | 4 | | 26 | 25 | | 27 | 14 | | 28 | 3 | | 29 | 10 | | 30 | 5 | | 31 | 10 | | 32 | 5 | | 33 | 14 | | 34 | 4 | | 35 | 5 | | 36 | 11 | | 37 | 13 | | 38 | 8 | | 39 | 8 | | 40 | 17 | | 41 | 9 | | 42 | 11 | | 43 | 7 | | 44 | 6 | | 45 | 16 | | 46 | 33 | | 47 | 13 | | 48 | 4 | | 49 | 4 |
| |
| 70.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.45794392523364486 | | totalSentences | 107 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 65 | | matches | | 0 | "His skin showed an ash-grey" | | 1 | "She stripped off a leather" | | 2 | "She leaned closer." | | 3 | "She touched the glazed ceramic." | | 4 | "His eyes were wide, the" | | 5 | "His mouth hung open in" | | 6 | "She reached for the victim's" | | 7 | "It was a smooth, rectangular" | | 8 | "It was the same dead" | | 9 | "Her hand went instinctively to" | | 10 | "She reached the threshold of" | | 11 | "She tucked a stray curl" | | 12 | "She reached inside and withdrew" | | 13 | "It shuddered, spun three complete" |
| | ratio | 0.215 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 63 | | totalSentences | 65 | | matches | | 0 | "Quinn ducked beneath the rusted" | | 1 | "The abandoned access tunnel beneath" | | 2 | "Halogen lamps cast harsh, white" | | 3 | "Detective Constable Vance said, flicking" | | 4 | "Quinn checked her worn leather" | | 5 | "Quinn stepped around a puddle" | | 6 | "The body sat upright against" | | 7 | "The man was dressed in" | | 8 | "His skin showed an ash-grey" | | 9 | "Vance said, pointing his pen" | | 10 | "The air around the corpse" | | 11 | "She stripped off a leather" | | 12 | "A faint, prickling vibration tickled" | | 13 | "Vance lowered his pen." | | 14 | "Quinn aimed her torch at" | | 15 | "She leaned closer." | | 16 | "The wall tiles behind the" | | 17 | "She touched the glazed ceramic." | | 18 | "The surface felt slick, transformed" | | 19 | "Quinn gripped the dead man's" |
| | ratio | 0.969 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 1 | | matches | | 0 | "A jagged, vertical tear hung in the air, oozing thick, oily smoke that smelled of dead stars and ozone." |
| |
| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 2 | | matches | | 0 | "the woman said, her voice rapid and high-pitched" | | 1 | "Quinn said, her voice dropping to a gravelly rasp" |
| |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 3 | | fancyTags | | 0 | "Quinn ordered (order)" | | 1 | "Eva murmured (murmur)" | | 2 | "Quinn yelled (yell)" |
| | dialogueSentences | 51 | | tagDensity | 0.373 | | leniency | 0.745 | | rawRatio | 0.158 | | effectiveRatio | 0.118 | |