| 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 | 1148 | | 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) | |
| 21.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1148 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "silence" | | 2 | "echoed" | | 3 | "depths" | | 4 | "pulsed" | | 5 | "scanned" | | 6 | "gloom" | | 7 | "glint" | | 8 | "standard" | | 9 | "stomach" | | 10 | "weight" | | 11 | "etched" | | 12 | "familiar" | | 13 | "vibrated" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 144 | | matches | (empty) | |
| 93.25% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 144 | | filterMatches | | | hedgeMatches | | 0 | "began to" | | 1 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 144 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1148 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1148 | | uniqueNames | 10 | | maxNameDensity | 1.31 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 4 | | Quinn | 15 | | Morris | 4 | | Police | 2 | | Detective | 2 | | Market | 1 | | Camden | 1 | | You | 4 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Police" | | 4 | "You" |
| | places | | | globalScore | 0.847 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | 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 | 1148 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 144 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 24.96 | | std | 18.95 | | cv | 0.759 | | sampleLengths | | 0 | 95 | | 1 | 10 | | 2 | 55 | | 3 | 56 | | 4 | 27 | | 5 | 13 | | 6 | 5 | | 7 | 33 | | 8 | 16 | | 9 | 20 | | 10 | 12 | | 11 | 55 | | 12 | 17 | | 13 | 14 | | 14 | 21 | | 15 | 53 | | 16 | 5 | | 17 | 45 | | 18 | 4 | | 19 | 36 | | 20 | 3 | | 21 | 33 | | 22 | 11 | | 23 | 19 | | 24 | 10 | | 25 | 6 | | 26 | 15 | | 27 | 37 | | 28 | 6 | | 29 | 8 | | 30 | 23 | | 31 | 26 | | 32 | 48 | | 33 | 10 | | 34 | 29 | | 35 | 44 | | 36 | 49 | | 37 | 21 | | 38 | 6 | | 39 | 42 | | 40 | 34 | | 41 | 17 | | 42 | 25 | | 43 | 17 | | 44 | 10 | | 45 | 7 |
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| 90.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 144 | | matches | | 0 | "are made" | | 1 | "been used" | | 2 | "was obscured" | | 3 | "was gone" | | 4 | "is closed" | | 5 | "got mugged" | | 6 | "were eaten" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 194 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 144 | | ratio | 0 | | matches | (empty) | |
| 76.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1148 | | adjectiveStacks | 4 | | stackExamples | | 0 | "locked tight against rotting" | | 1 | "faint, sickly green luminescence." | | 2 | "heavier, pressing against her" | | 3 | "below, illuminating strange silhouettes" |
| | adverbCount | 18 | | adverbRatio | 0.0156794425087108 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006097560975609756 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 144 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 144 | | mean | 7.97 | | std | 5.36 | | cv | 0.672 | | sampleLengths | | 0 | 18 | | 1 | 30 | | 2 | 14 | | 3 | 13 | | 4 | 20 | | 5 | 10 | | 6 | 8 | | 7 | 17 | | 8 | 5 | | 9 | 9 | | 10 | 4 | | 11 | 5 | | 12 | 7 | | 13 | 20 | | 14 | 8 | | 15 | 7 | | 16 | 4 | | 17 | 3 | | 18 | 4 | | 19 | 10 | | 20 | 3 | | 21 | 15 | | 22 | 9 | | 23 | 6 | | 24 | 7 | | 25 | 5 | | 26 | 8 | | 27 | 15 | | 28 | 10 | | 29 | 3 | | 30 | 3 | | 31 | 4 | | 32 | 6 | | 33 | 20 | | 34 | 4 | | 35 | 8 | | 36 | 3 | | 37 | 10 | | 38 | 3 | | 39 | 24 | | 40 | 15 | | 41 | 8 | | 42 | 5 | | 43 | 4 | | 44 | 3 | | 45 | 11 | | 46 | 7 | | 47 | 2 | | 48 | 12 | | 49 | 4 |
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| 34.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.2847222222222222 | | totalSentences | 144 | | uniqueOpeners | 41 | |
| 78.13% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 128 | | matches | | 0 | "Just a badge she had" | | 1 | "Only what you steal." | | 2 | "Then she looked down at" |
| | ratio | 0.023 | |
| 29.38% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 61 | | totalSentences | 128 | | matches | | 0 | "Her boots splashed through puddles" | | 1 | "She checked the time on" | | 2 | "Her breath fogged in the" | | 3 | "She did not shout." | | 4 | "She turned the corner, breath" | | 5 | "It groaned, locked tight against" | | 6 | "She checked the handle." | | 7 | "It rattled, loose." | | 8 | "She twisted it hard." | | 9 | "I know you followed him." | | 10 | "Her hand went to the" | | 11 | "Her voice didn't waver." | | 12 | "You want the truth?" | | 13 | "You step down that way," | | 14 | "She scanned the stairs, her" | | 15 | "Her jaw tightened." | | 16 | "She thought of Morris, how" | | 17 | "He had chased the dark" | | 18 | "I'm not looking for truth" | | 19 | "I'm looking for a warrant." |
| | ratio | 0.477 | |
| 14.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 114 | | totalSentences | 128 | | matches | | 0 | "Detective Harlow Quinn pressed the" | | 1 | "Her boots splashed through puddles" | | 2 | "She checked the time on" | | 3 | "The figure moved with the" | | 4 | "Quinn picked up the pace." | | 5 | "Her breath fogged in the" | | 6 | "She did not shout." | | 7 | "Shouting gave away the chase." | | 8 | "Silence was the advantage of" | | 9 | "She turned the corner, breath" | | 10 | "Quinn threw her shoulder into" | | 11 | "It groaned, locked tight against" | | 12 | "She checked the handle." | | 13 | "It rattled, loose." | | 14 | "She twisted it hard." | | 15 | "The mechanism screamed inside the" | | 16 | "Quinn slipped inside." | | 17 | "The smell of ozone and" | | 18 | "A narrow concrete staircase spiraled" | | 19 | "A voice echoed from the" |
| | ratio | 0.891 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 128 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn pressed the collar of her trench coat up against her neck, though the wet fabric offered little protection against the bite that had seep…" | | 1 | "The figure moved with the fluid confidence of someone who knew the shadows better than the streetlights." |
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| 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 | |