| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 13 | | tagDensity | 0.538 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 96.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1275 | | 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) | |
| 80.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1275 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "efficient" | | 1 | "glistening" | | 2 | "streaming" | | 3 | "indexed" | | 4 | "glinting" |
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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 | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 87 | | 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 | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1290 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1103 | | uniqueNames | 17 | | maxNameDensity | 0.54 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 3 | | Detective | 1 | | Harlow | 1 | | Quinn | 6 | | Raven | 1 | | Nest | 1 | | Silas | 1 | | Herrera | 5 | | Dean | 1 | | Street | 1 | | Tube | 1 | | Morris | 1 | | Saint | 1 | | Christopher | 1 | | Spanish | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Silas" | | 5 | "Herrera" | | 6 | "Morris" | | 7 | "Saint" | | 8 | "Christopher" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a jar of teeth" | | 1 | "something like incense gone wrong" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.775 | | wordCount | 1290 | | matches | | 0 | "not the panicked sprint of a cornered man but the efficient lope of someone following a rehearsed route" |
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| 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 | 34 | | mean | 37.94 | | std | 24.96 | | cv | 0.658 | | sampleLengths | | 0 | 31 | | 1 | 85 | | 2 | 13 | | 3 | 3 | | 4 | 78 | | 5 | 25 | | 6 | 54 | | 7 | 7 | | 8 | 62 | | 9 | 50 | | 10 | 57 | | 11 | 9 | | 12 | 93 | | 13 | 29 | | 14 | 7 | | 15 | 69 | | 16 | 66 | | 17 | 35 | | 18 | 39 | | 19 | 45 | | 20 | 20 | | 21 | 40 | | 22 | 10 | | 23 | 65 | | 24 | 24 | | 25 | 47 | | 26 | 31 | | 27 | 33 | | 28 | 21 | | 29 | 22 | | 30 | 77 | | 31 | 29 | | 32 | 11 | | 33 | 3 |
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| 97.20% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 87 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 181 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 93 | | ratio | 0.151 | | matches | | 0 | "The Raven's Nest had been quiet that night — just the green sign buzzing above the door like a sickly halo, Silas wiping glasses behind the bar with the untroubled air of a man who'd never once called the police." | | 1 | "Herrera moved like he'd done this before — not the panicked sprint of a cornered man but the efficient lope of someone following a rehearsed route." | | 2 | "Eighteen years on the job had taught her the arithmetic of chases — this one wasn't going to end in exhaustion." | | 3 | "The stairs descended into darkness beneath a rusted gate marked CLOSED FOR MAINTENANCE — TRANSPORT FOR LONDON." | | 4 | "Somewhere in her chest, the old wound stirred — Morris, three years gone, and the case she'd never closed." | | 5 | "Rumors she'd dismissed as unprofessional gossip — that he treated patients who didn't exist on any NHS record." | | 6 | "The dark swallowed her in stages — first the glow of the city, then the sound, until there was only the drip of water somewhere deep and the cold breath of the tunnels rising to meet her." | | 7 | "Then, oddly, it played a snatch of music — a Spanish guitar, faint and distorted, gone before she could be sure." | | 8 | "She moved toward it with the discipline of years — checked corners, kept her weapon low and indexed, controlled her breathing." | | 9 | "And the people — or the things wearing people." | | 10 | "Eyes — too many eyes, some of them wrong — turned toward her sidearm and turned away again, and the crowd simply opened, swallowing her, indifferent as the sea." | | 11 | "\"One man. Yes. That's how it always starts.\" She released Quinn's arm and pressed something into her palm — small, smooth, cold as riverbed stone." | | 12 | "Turned, and for a moment his face was lit by the lantern-glow — the olive skin, the warm eyes, the medal glinting at his throat." | | 13 | "Somewhere far down it, in the deep dark of the dead line, something answered — a long, low sound, half whistle, half voice." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1097 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.0300820419325433 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006381039197812215 | |
| 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 | 13.87 | | std | 10.36 | | cv | 0.747 | | sampleLengths | | 0 | 31 | | 1 | 4 | | 2 | 40 | | 3 | 41 | | 4 | 13 | | 5 | 3 | | 6 | 20 | | 7 | 26 | | 8 | 32 | | 9 | 7 | | 10 | 8 | | 11 | 10 | | 12 | 22 | | 13 | 3 | | 14 | 21 | | 15 | 6 | | 16 | 2 | | 17 | 7 | | 18 | 19 | | 19 | 17 | | 20 | 4 | | 21 | 2 | | 22 | 6 | | 23 | 14 | | 24 | 19 | | 25 | 17 | | 26 | 9 | | 27 | 5 | | 28 | 29 | | 29 | 2 | | 30 | 4 | | 31 | 18 | | 32 | 4 | | 33 | 9 | | 34 | 11 | | 35 | 37 | | 36 | 10 | | 37 | 6 | | 38 | 2 | | 39 | 27 | | 40 | 4 | | 41 | 21 | | 42 | 4 | | 43 | 7 | | 44 | 21 | | 45 | 22 | | 46 | 1 | | 47 | 19 | | 48 | 6 | | 49 | 9 |
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| 68.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.44086021505376344 | | totalSentences | 93 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 78 | | matches | | 0 | "Then he ran." | | 1 | "Somewhere in her chest, the" | | 2 | "Then, oddly, it played a" | | 3 | "Somewhere far down it, in" |
| | ratio | 0.051 | |
| 76.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 78 | | matches | | 0 | "She'd almost had him." | | 1 | "he'd said, all warm brown" | | 2 | "She went after him, shoulder-checking" | | 3 | "He cut left off Dean" | | 4 | "she shouted, knowing it was" | | 5 | "He turned down a service" | | 6 | "Her lungs burned." | | 7 | "He knew where he was" | | 8 | "He vanished down a set" | | 9 | "She reached the top of" | | 10 | "She'd told herself a hundred" | | 11 | "She drew her sidearm and" | | 12 | "Her torch beam cut a" | | 13 | "Her radio hissed static." | | 14 | "She clicked it off." | | 15 | "She moved toward it with" | | 16 | "She'd heard the phrase once," | | 17 | "You need a token to" | | 18 | "She spotted Herrera's dark curls" | | 19 | "She pushed forward." |
| | ratio | 0.359 | |
| 36.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 78 | | matches | | 0 | "The rain came down in" | | 1 | "She'd almost had him." | | 2 | "The Raven's Nest had been" | | 3 | "Quinn had come in on" | | 4 | "he'd said, all warm brown" | | 5 | "She went after him, shoulder-checking" | | 6 | "Herrera moved like he'd done" | | 7 | "He cut left off Dean" | | 8 | "she shouted, knowing it was" | | 9 | "Nobody in Soho at midnight" | | 10 | "Everybody in Soho at midnight" | | 11 | "He turned down a service" | | 12 | "Her lungs burned." | | 13 | "He knew where he was" | | 14 | "He vanished down a set" | | 15 | "She reached the top of" | | 16 | "The stairs descended into darkness" | | 17 | "An abandoned Tube station." | | 18 | "The rain drummed on her" | | 19 | "The last time she'd followed" |
| | ratio | 0.846 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "The Raven's Nest had been quiet that night — just the green sign buzzing above the door like a sickly halo, Silas wiping glasses behind the bar with the untroub…" | | 1 | "Herrera was moving again, slipping past a stall hung with cages of sleeping birds that shouldn't have existed, heading toward the dark mouth of the northbound t…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "he'd (would)" | | 1 | "she shouted (shout)" |
| | dialogueSentences | 13 | | tagDensity | 0.385 | | leniency | 0.769 | | rawRatio | 0.4 | | effectiveRatio | 0.308 | |