| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.478 | | leniency | 0.957 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1287 | | 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) | |
| 100.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1287 | | totalAiIsms | 0 | | found | (empty) | | highlights | (empty) | |
| 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 | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1301 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1073 | | uniqueNames | 18 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Buck | 1 | | Street | 1 | | Quinn | 10 | | Tomás | 1 | | Herrera | 7 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Camden | 1 | | London | 1 | | Tube | 1 | | Rain | 1 | | Saint | 1 | | Christopher | 1 | | Silvertown | 1 | | Morris | 2 | | Fear | 1 | | Three | 4 |
| | persons | | 0 | "Buck" | | 1 | "Street" | | 2 | "Quinn" | | 3 | "Tomás" | | 4 | "Herrera" | | 5 | "Raven" | | 6 | "Rain" | | 7 | "Saint" | | 8 | "Christopher" | | 9 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Silvertown" | | 3 | "Three" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.769 | | wordCount | 1301 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 33.36 | | std | 25.94 | | cv | 0.778 | | sampleLengths | | 0 | 51 | | 1 | 43 | | 2 | 14 | | 3 | 38 | | 4 | 2 | | 5 | 100 | | 6 | 53 | | 7 | 28 | | 8 | 33 | | 9 | 4 | | 10 | 89 | | 11 | 4 | | 12 | 52 | | 13 | 11 | | 14 | 10 | | 15 | 59 | | 16 | 7 | | 17 | 71 | | 18 | 14 | | 19 | 35 | | 20 | 29 | | 21 | 49 | | 22 | 25 | | 23 | 59 | | 24 | 22 | | 25 | 9 | | 26 | 11 | | 27 | 93 | | 28 | 21 | | 29 | 68 | | 30 | 11 | | 31 | 23 | | 32 | 18 | | 33 | 28 | | 34 | 1 | | 35 | 38 | | 36 | 48 | | 37 | 27 | | 38 | 3 |
| |
| 96.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 81 | | matches | | 0 | "been carved" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 175 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 93 | | ratio | 0.097 | | matches | | 0 | "From the green neon of the Raven's Nest to doorways in Soho to this — Camden, the night of a full moon, Herrera moving through the city like a man keeping an appointment he couldn't afford to miss." | | 1 | "She caught it in the window — his reflection stalling mid-step, brown eyes finding hers in the glass, holding them a beat too long." | | 2 | "It burst open in the air — syringes, amber vials, a coil of tubing scattering across the wet concrete — and something small bounced free, skipped off a puddle, and rolled to a stop against the wall." | | 3 | "A sigil had been carved into its face — spirals within spirals, worn shallow by thumbs." | | 4 | "Eighteen years of chasing people through London and her legs still remembered the drill — don't watch the runner, watch the route, cut the angles." | | 5 | "Ten steps down, twenty, the temperature dropped and the air changed — wet stone giving way to something older, dust and incense and copper." | | 6 | "Beyond the woman, Herrera stood at a wrought-iron gate set into the tunnel wall — a gate Quinn was certain hadn't existed in any survey of this station — and he was patting his jacket, his trousers, turning out empty pockets." | | 7 | "Her eyes had — down to Quinn's hand, to the leather cord wound around her knuckles." | | 8 | "\"Detective.\" Herrera's voice dropped low, and there was something in it she hadn't expected — not fear for himself." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1065 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.016901408450704224 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 13.99 | | std | 11.63 | | cv | 0.831 | | sampleLengths | | 0 | 15 | | 1 | 5 | | 2 | 31 | | 3 | 5 | | 4 | 38 | | 5 | 4 | | 6 | 10 | | 7 | 11 | | 8 | 24 | | 9 | 3 | | 10 | 2 | | 11 | 6 | | 12 | 26 | | 13 | 1 | | 14 | 6 | | 15 | 17 | | 16 | 7 | | 17 | 37 | | 18 | 20 | | 19 | 9 | | 20 | 24 | | 21 | 12 | | 22 | 16 | | 23 | 9 | | 24 | 20 | | 25 | 4 | | 26 | 4 | | 27 | 8 | | 28 | 33 | | 29 | 3 | | 30 | 25 | | 31 | 20 | | 32 | 4 | | 33 | 23 | | 34 | 14 | | 35 | 3 | | 36 | 5 | | 37 | 7 | | 38 | 3 | | 39 | 8 | | 40 | 10 | | 41 | 13 | | 42 | 22 | | 43 | 24 | | 44 | 7 | | 45 | 30 | | 46 | 41 | | 47 | 5 | | 48 | 9 | | 49 | 14 |
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| 61.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.41935483870967744 | | totalSentences | 93 | | uniqueOpeners | 39 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 77 | | matches | | 0 | "Then he ran." | | 1 | "Then he ran harder." | | 2 | "Then he was gone." | | 3 | "Then he took the case" |
| | ratio | 0.052 | |
| 58.96% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 77 | | matches | | 0 | "She stood beneath the rusted" | | 1 | "He crossed the road." | | 2 | "She gave him the width" | | 3 | "He made her outside the" | | 4 | "She caught it in the" | | 5 | "Her shout vanished into the" | | 6 | "He cut left down a" | | 7 | "He hit the fence at" | | 8 | "It burst open in the" | | 9 | "Her boots splashed down among" | | 10 | "She swept the case up," | | 11 | "He glanced back once, and" | | 12 | "She ran harder too." | | 13 | "He knew these streets better" | | 14 | "He took her through a" | | 15 | "Her lungs burned." | | 16 | "She gained on him at" | | 17 | "She pulled up at the" | | 18 | "Her beam caught graffiti, a" | | 19 | "Her voice came out like" |
| | ratio | 0.403 | |
| 83.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 77 | | matches | | 0 | "The rain had chased everyone" | | 1 | "She stood beneath the rusted" | | 2 | "He crossed the road." | | 3 | "She gave him the width" | | 4 | "He made her outside the" | | 5 | "She caught it in the" | | 6 | "Her shout vanished into the" | | 7 | "He cut left down a" | | 8 | "A mattress against a chain-link" | | 9 | "He hit the fence at" | | 10 | "The aluminium case caught the" | | 11 | "It burst open in the" | | 12 | "Quinn took the fence in" | | 13 | "Her boots splashed down among" | | 14 | "She swept the case up," | | 15 | "A disc of bone, yellowed" | | 16 | "A sigil had been carved" | | 17 | "Herrera was already at the" | | 18 | "He glanced back once, and" | | 19 | "She ran harder too." |
| | ratio | 0.753 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 16.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 6 | | matches | | 0 | "The rain had chased everyone else off Buck Street by midnight, which suited Quinn fine." | | 1 | "She caught it in the window — his reflection stalling mid-step, brown eyes finding hers in the glass, holding them a beat too long." | | 2 | "He cut left down a service alley, boots throwing water off the puddles, and Quinn gave chase, her breath tearing out of her in white bursts." | | 3 | "Beyond the woman, Herrera stood at a wrought-iron gate set into the tunnel wall — a gate Quinn was certain hadn't existed in any survey of this station — and he…" | | 4 | "Three years since a warehouse in Silvertown, since Morris went through a door ahead of her because she'd stopped to call it in, since the door opened onto a roo…" | | 5 | "The iron gate swung inward on its own, without a hand touching it, onto a stairwell that spiralled down past the reach of the lantern, past the reach of any lig…" |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "She hooked, and the disc settled against her sternum, warm as a held breath" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 23 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0 | | effectiveRatio | 0 | |