| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1685 | | 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) | |
| 79.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1685 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "familiar" | | 1 | "echoed" | | 2 | "pulsed" | | 3 | "vibrated" | | 4 | "glinting" | | 5 | "warmth" | | 6 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 127 | | matches | (empty) | |
| 86.61% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 127 | | filterMatches | | | hedgeMatches | | 0 | "began to" | | 1 | "tried to" | | 2 | "started to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 133 | | 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 | 2 | | markdownWords | 2 | | totalWords | 1702 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1592 | | uniqueNames | 15 | | maxNameDensity | 1.13 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Mercer" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 18 | | Raven | 1 | | Nest | 1 | | Mercer | 15 | | Morris | 4 | | Thames | 1 | | Street | 2 | | Tube | 1 | | Camden | 1 | | Herrera | 2 | | Saint | 1 | | Christopher | 1 | | Spanish | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Mercer" | | 3 | "Morris" | | 4 | "Herrera" | | 5 | "Saint" | | 6 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Thames" | | 3 | "Street" | | 4 | "Tube" | | 5 | "Spanish" |
| | globalScore | 0.935 | | windowScore | 0.833 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a drowned painting" | | 1 | "felt like a clue she couldn't read" | | 2 | "as if humming" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.588 | | wordCount | 1702 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 133 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 38.68 | | std | 29.42 | | cv | 0.761 | | sampleLengths | | 0 | 57 | | 1 | 71 | | 2 | 50 | | 3 | 25 | | 4 | 4 | | 5 | 97 | | 6 | 84 | | 7 | 58 | | 8 | 33 | | 9 | 66 | | 10 | 68 | | 11 | 5 | | 12 | 2 | | 13 | 79 | | 14 | 4 | | 15 | 60 | | 16 | 22 | | 17 | 7 | | 18 | 41 | | 19 | 86 | | 20 | 32 | | 21 | 23 | | 22 | 79 | | 23 | 13 | | 24 | 6 | | 25 | 97 | | 26 | 56 | | 27 | 5 | | 28 | 6 | | 29 | 59 | | 30 | 7 | | 31 | 5 | | 32 | 53 | | 33 | 3 | | 34 | 47 | | 35 | 67 | | 36 | 27 | | 37 | 4 | | 38 | 13 | | 39 | 26 | | 40 | 46 | | 41 | 46 | | 42 | 3 | | 43 | 60 |
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| 96.97% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 127 | | matches | | 0 | "been closed" | | 1 | "been repurposed " | | 2 | "been *inhabited" |
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| 51.85% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 270 | | matches | | 0 | "was driving" | | 1 | "was going" | | 2 | "was driving" | | 3 | "was carrying" | | 4 | "was wearing" | | 5 | "was happening" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 17 | | semicolonCount | 0 | | flaggedSentences | 16 | | totalSentences | 133 | | ratio | 0.12 | | matches | | 0 | "The target was a man she knew only as Mercer — a fixer, a courier, a man who ran errands for people who didn't exist on paper." | | 1 | "Mercer came out — wiry, hooded, head down against the rain." | | 2 | "He was fast — the kind of fast that came from practice, not panic." | | 3 | "Quinn took the same jump and felt the worn leather of her watch slap against her wrist, felt the familiar twist of the strap between her fingers as she ran — an old habit, a tic she'd picked up in the months after Morris died, when every case felt like a clue she couldn't read." | | 4 | "She knew it before she saw it — the block of hoardings, the scaffold, the boarded-up entrance to a Tube station beneath Camden that had been closed since the eighties." | | 5 | "Below, the air was cold and still, thick with the smell of damp concrete and something older — rust, and dust, and the sweet rot of things left underground too long." | | 6 | "Quinn caught it in the way he stood — too still, head cocked at an angle no human neck could hold comfortably." | | 7 | "He looked at Mercer, who had already fumbled something from his pocket — a small white thing, a knuckle of bone — and held it up." | | 8 | "Mercer snarled, twisted, and a knife came up — short blade, street knife, the kind that had left a scar on more than one forearm in this city." | | 9 | "The abandoned station had been repurposed — no, that wasn't right." | | 10 | "He reached into his jacket and brought out the package — a flat envelope wrapped in waxed paper." | | 11 | "He was stronger than she remembered — but then, she'd only ever questioned him across a table, never like this." | | 12 | "She'd heard the stories — the paramedic who lost his license for treating patients the system wouldn't touch, who stitched up monsters in back rooms and asked no questions." | | 13 | "The black cloth moved, and a figure emerged — tall, thin, draped in shadows." | | 14 | "Behind her, she heard him swear — a word in Spanish, sharp as a slap." | | 15 | "She just ran — deeper into the dark, deeper into the place where the law had no name, chasing a dead man's killer through the belly of a city that had never once told her the truth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1577 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.02663284717818643 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.0057070386810399495 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 133 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 133 | | mean | 12.8 | | std | 9.29 | | cv | 0.726 | | sampleLengths | | 0 | 19 | | 1 | 26 | | 2 | 12 | | 3 | 8 | | 4 | 27 | | 5 | 25 | | 6 | 6 | | 7 | 5 | | 8 | 1 | | 9 | 3 | | 10 | 11 | | 11 | 13 | | 12 | 4 | | 13 | 18 | | 14 | 12 | | 15 | 2 | | 16 | 1 | | 17 | 4 | | 18 | 6 | | 19 | 4 | | 20 | 14 | | 21 | 22 | | 22 | 19 | | 23 | 10 | | 24 | 19 | | 25 | 13 | | 26 | 2 | | 27 | 2 | | 28 | 13 | | 29 | 12 | | 30 | 55 | | 31 | 8 | | 32 | 30 | | 33 | 10 | | 34 | 10 | | 35 | 16 | | 36 | 17 | | 37 | 9 | | 38 | 31 | | 39 | 8 | | 40 | 18 | | 41 | 3 | | 42 | 22 | | 43 | 17 | | 44 | 26 | | 45 | 5 | | 46 | 2 | | 47 | 17 | | 48 | 20 | | 49 | 28 |
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| 34.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2556390977443609 | | totalSentences | 133 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 117 | | matches | | 0 | "Too quick to move." | | 1 | "Then the gatekeeper moved." | | 2 | "Then she stepped through the" | | 3 | "Then his voice, carrying over" |
| | ratio | 0.034 | |
| 62.74% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 117 | | matches | | 0 | "She'd been watching the door" | | 1 | "She'd been chasing him for" | | 2 | "He didn't look back, but" | | 3 | "She crossed the street without" | | 4 | "He turned, saw her, and" | | 5 | "He was fast — the" | | 6 | "He cut left down a" | | 7 | "She was forty-one years old" | | 8 | "She knew these streets the" | | 9 | "She knew that Mercer was" | | 10 | "She'd have followed him into" | | 11 | "He was driving her toward" | | 12 | "She knew it before she" | | 13 | "He looked at Mercer, who" | | 14 | "She hit Mercer low, wrapping" | | 15 | "They went down in a" | | 16 | "He didn't run." | | 17 | "He simply reached down, took" | | 18 | "His eyes were the color" | | 19 | "She followed his gaze." |
| | ratio | 0.393 | |
| 7.01% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 106 | | totalSentences | 117 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn stood in" | | 2 | "The green sign buzzed overhead" | | 3 | "She'd been watching the door" | | 4 | "The target was a man" | | 5 | "She'd been chasing him for" | | 6 | "The same breath as the" | | 7 | "The people who'd killed Morris." | | 8 | "The door opened." | | 9 | "Mercer came out — wiry," | | 10 | "He didn't look back, but" | | 11 | "Quinn recognized the set of" | | 12 | "She crossed the street without" | | 13 | "Mercer's head came up." | | 14 | "He turned, saw her, and" | | 15 | "Quinn went after him." | | 16 | "He was fast — the" | | 17 | "He cut left down a" | | 18 | "She was forty-one years old" | | 19 | "She knew these streets the" |
| | ratio | 0.906 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 117 | | matches | (empty) | | ratio | 0 | |
| 68.23% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 7 | | matches | | 0 | "He cut left down a narrow service alley, splashing through a channel of runoff, and Quinn followed, her boots slapping wet stone." | | 1 | "She knew it before she saw it — the block of hoardings, the scaffold, the boarded-up entrance to a Tube station beneath Camden that had been closed since the ei…" | | 2 | "The place her informants had whispered about for years, the place that moved every full moon, the place where you could buy anything if you had the right curren…" | | 3 | "She thought about the file she kept under her floorboards at home, the photographs, the witness statements that contradicted physics." | | 4 | "Stalls lined the old track bed, canvas awnings dripping with condensation, vendors in hoods and long coats selling things that made her skin prickle." | | 5 | "Ahead, darkness, and the splash of footsteps, and the faint smell of rain on a man who'd run through it." | | 6 | "She just ran — deeper into the dark, deeper into the place where the law had no name, chasing a dead man's killer through the belly of a city that had never onc…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0 | | effectiveRatio | 0 | |