| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.30% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1063 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 81.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1063 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "electric" |
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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 | 78 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 3 | | totalWords | 1063 | | ratio | 0.003 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 84.01% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 985 | | uniqueNames | 10 | | maxNameDensity | 1.32 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 13 | | Camden | 1 | | Bayham | 1 | | Street | 1 | | Tube | 1 | | Morris | 2 | | Deptford | 1 | | Herrera | 2 | | Soho | 1 | | Three | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Herrera" |
| | places | | 0 | "Camden" | | 1 | "Bayham" | | 2 | "Street" | | 3 | "Deptford" | | 4 | "Soho" | | 5 | "Three" |
| | globalScore | 0.84 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared beside the first, taller, its cowl slipping back just enough to reveal eyes that held no whites at all, only a deep, endless black" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1063 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 23.62 | | std | 20.67 | | cv | 0.875 | | sampleLengths | | 0 | 14 | | 1 | 56 | | 2 | 2 | | 3 | 28 | | 4 | 57 | | 5 | 28 | | 6 | 48 | | 7 | 8 | | 8 | 21 | | 9 | 2 | | 10 | 28 | | 11 | 10 | | 12 | 65 | | 13 | 4 | | 14 | 83 | | 15 | 10 | | 16 | 45 | | 17 | 8 | | 18 | 12 | | 19 | 36 | | 20 | 23 | | 21 | 12 | | 22 | 29 | | 23 | 8 | | 24 | 5 | | 25 | 5 | | 26 | 35 | | 27 | 9 | | 28 | 9 | | 29 | 66 | | 30 | 29 | | 31 | 61 | | 32 | 8 | | 33 | 19 | | 34 | 4 | | 35 | 11 | | 36 | 31 | | 37 | 28 | | 38 | 5 | | 39 | 1 | | 40 | 2 | | 41 | 29 | | 42 | 17 | | 43 | 48 | | 44 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 179 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 88 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 989 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.03640040444893832 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006066734074823054 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 12.08 | | std | 9.38 | | cv | 0.776 | | sampleLengths | | 0 | 14 | | 1 | 22 | | 2 | 6 | | 3 | 22 | | 4 | 6 | | 5 | 2 | | 6 | 3 | | 7 | 5 | | 8 | 20 | | 9 | 20 | | 10 | 11 | | 11 | 8 | | 12 | 3 | | 13 | 15 | | 14 | 4 | | 15 | 2 | | 16 | 22 | | 17 | 24 | | 18 | 8 | | 19 | 16 | | 20 | 8 | | 21 | 12 | | 22 | 5 | | 23 | 2 | | 24 | 2 | | 25 | 2 | | 26 | 4 | | 27 | 20 | | 28 | 3 | | 29 | 1 | | 30 | 10 | | 31 | 20 | | 32 | 45 | | 33 | 4 | | 34 | 24 | | 35 | 28 | | 36 | 6 | | 37 | 25 | | 38 | 10 | | 39 | 20 | | 40 | 16 | | 41 | 9 | | 42 | 8 | | 43 | 12 | | 44 | 3 | | 45 | 12 | | 46 | 3 | | 47 | 18 | | 48 | 15 | | 49 | 3 |
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| 82.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5227272727272727 | | totalSentences | 88 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 68 | | matches | | 0 | "Of course he didn't stop." | | 1 | "Somewhere below, water dripped in" | | 2 | "Somewhere past the turnstile, deeper" | | 3 | "Somewhere in that crush of" |
| | ratio | 0.059 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 68 | | matches | | 0 | "She closed the gap through" | | 1 | "He didn't stop." | | 2 | "He cut left down Bayham" | | 3 | "Her lungs burned." | | 4 | "He glanced back once." | | 5 | "He hit the plywood shoulder-first" | | 6 | "She keyed her radio." | | 7 | "She tried again." | | 8 | "She thought about Morris." | | 9 | "She'd watched him walk into" | | 10 | "She drew her torch and" | | 11 | "Her torch beam skated over" | | 12 | "Her voice bounced back at" | | 13 | "She kept moving." | | 14 | "He'd gone through." | | 15 | "She approached the turnstile, and" | | 16 | "She held it up like" | | 17 | "She caught the flash of" | | 18 | "She stepped toward the turnstile." |
| | ratio | 0.279 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 68 | | matches | | 0 | "The man's boots hit a" | | 1 | "She closed the gap through" | | 2 | "Tonight, finally, a body to" | | 3 | "He didn't stop." | | 4 | "Nobody stopped when Quinn shouted" | | 5 | "He cut left down Bayham" | | 6 | "Quinn followed, boots slapping through" | | 7 | "A cat shrieked and vanished" | | 8 | "Her lungs burned." | | 9 | "He glanced back once." | | 10 | "The alley spat them out" | | 11 | "The suspect didn't slow down" | | 12 | "He hit the plywood shoulder-first" | | 13 | "Quinn skidded to a stop" | | 14 | "Copper, and something sweeter underneath." | | 15 | "She keyed her radio." | | 16 | "Static answered, a thin hiss" | | 17 | "She tried again." | | 18 | "Quinn had a choice, and" | | 19 | "She thought about Morris." |
| | ratio | 0.676 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 11 | | matches | | 0 | "Three months of dead ends, whispered names, and a growing file marked *Herrera, T.* that made less sense the deeper she dug." | | 1 | "Enough for her to catch pale eyes, too pale, and a face that shouldn't have belonged to a man moving that fast." | | 2 | "Her torch beam skated over faded advertisements, peeling posters for products that hadn't existed in years." | | 3 | "Something warmer, flickering, lanterns maybe, strung along a passage that shouldn't have led anywhere but a bricked-off tunnel." | | 4 | "She caught the flash of coin changing hands, saw a stall selling jars of something that glowed faint blue, saw a woman with too many joints in her fingers count…" | | 5 | "Somewhere in that crush of impossible things, wearing a torn coat and pale eyes that had looked at her like she was the aberration." | | 6 | "About Herrera's name cross-referenced against three assault victims who'd healed too fast, wounds that closed overnight according to hospital records nobody wan…" | | 7 | "Quinn's hand drifted to her wrist, to the leather watch strap worn soft from years of habit, the one thing her father had left her that didn't come wrapped in d…" | | 8 | "A second figure had appeared beside the first, taller, its cowl slipping back just enough to reveal eyes that held no whites at all, only a deep, endless black." | | 9 | "Behind her, the stairwell she'd descended had gone dark, the entrance she'd broken through swallowed by shadow that hadn't been there a moment ago." | | 10 | "Ahead, lantern light beckoned, promising answers to three months of questions, three years of grief, one impossible case that had led her exactly here." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.231 | | leniency | 0.462 | | rawRatio | 0 | | effectiveRatio | 0 | |