| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.407 | | leniency | 0.815 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1829 | | totalAiIsmAdverbs | 2 | | 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) | |
| 78.13% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1829 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "glint" | | 1 | "standard" | | 2 | "structure" | | 3 | "flickered" | | 4 | "echoed" | | 5 | "scanned" | | 6 | "weight" | | 7 | "velvet" |
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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 | 1 | | narrationSentences | 177 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 177 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 192 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1829 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 1 | | matches | | 0 | "It moved locations every full moon, they said." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1619 | | uniqueNames | 20 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Chapter | 1 | | Seven | 1 | | Frith | 2 | | Street | 3 | | Quinn | 15 | | Soho | 2 | | Old | 1 | | Compton | 1 | | Morris | 4 | | Bermondsey | 1 | | London | 2 | | Chinatown | 2 | | Tommy | 8 | | Georgian | 1 | | Friday | 1 | | Tube | 2 | | Victorian | 2 | | Camden | 1 | | Didn | 1 | | Three | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Tommy" |
| | places | | 0 | "Frith" | | 1 | "Street" | | 2 | "Soho" | | 3 | "Old" | | 4 | "Compton" | | 5 | "Bermondsey" | | 6 | "London" | | 7 | "Chinatown" | | 8 | "Three" |
| | globalScore | 1 | | windowScore | 1 | |
| 79.91% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 107 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a human tooth the size of a f" | | 1 | "as though warding something off" | | 2 | "sounded like two people talking at once, s" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.547 | | wordCount | 1829 | | matches | | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 192 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 29.03 | | std | 18.65 | | cv | 0.642 | | sampleLengths | | 0 | 3 | | 1 | 13 | | 2 | 34 | | 3 | 6 | | 4 | 42 | | 5 | 30 | | 6 | 68 | | 7 | 53 | | 8 | 61 | | 9 | 37 | | 10 | 48 | | 11 | 48 | | 12 | 31 | | 13 | 19 | | 14 | 50 | | 15 | 32 | | 16 | 42 | | 17 | 13 | | 18 | 26 | | 19 | 16 | | 20 | 7 | | 21 | 46 | | 22 | 12 | | 23 | 6 | | 24 | 32 | | 25 | 18 | | 26 | 43 | | 27 | 9 | | 28 | 82 | | 29 | 66 | | 30 | 6 | | 31 | 63 | | 32 | 8 | | 33 | 25 | | 34 | 50 | | 35 | 50 | | 36 | 14 | | 37 | 5 | | 38 | 30 | | 39 | 45 | | 40 | 23 | | 41 | 24 | | 42 | 26 | | 43 | 15 | | 44 | 52 | | 45 | 18 | | 46 | 28 | | 47 | 15 | | 48 | 18 | | 49 | 6 |
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| 97.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 177 | | matches | | 0 | "been dragged" | | 1 | "been painted" | | 2 | "were worked" | | 3 | "was terrified" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 273 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 192 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1627 | | adjectiveStacks | 1 | | stackExamples | | 0 | "illuminating graffiti-covered walls" |
| | adverbCount | 43 | | adverbRatio | 0.02642901044867855 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.004917025199754148 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 192 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 192 | | mean | 9.53 | | std | 6.64 | | cv | 0.697 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 18 | | 3 | 6 | | 4 | 6 | | 5 | 6 | | 6 | 5 | | 7 | 14 | | 8 | 2 | | 9 | 3 | | 10 | 18 | | 11 | 8 | | 12 | 14 | | 13 | 3 | | 14 | 5 | | 15 | 2 | | 16 | 14 | | 17 | 26 | | 18 | 6 | | 19 | 20 | | 20 | 9 | | 21 | 6 | | 22 | 9 | | 23 | 29 | | 24 | 11 | | 25 | 23 | | 26 | 21 | | 27 | 1 | | 28 | 5 | | 29 | 15 | | 30 | 16 | | 31 | 6 | | 32 | 7 | | 33 | 20 | | 34 | 4 | | 35 | 2 | | 36 | 5 | | 37 | 2 | | 38 | 3 | | 39 | 5 | | 40 | 3 | | 41 | 2 | | 42 | 16 | | 43 | 15 | | 44 | 12 | | 45 | 12 | | 46 | 4 | | 47 | 4 | | 48 | 11 | | 49 | 5 |
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| 64.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.4322916666666667 | | totalSentences | 192 | | uniqueOpeners | 83 | |
| 61.73% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 162 | | matches | | 0 | "Somewhere beyond this door, a" | | 1 | "Just the words circled twice," | | 2 | "Just spoke with the certainty" |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 162 | | matches | | 0 | "She hit the iron rail" | | 1 | "She swallowed it and kept" | | 2 | "He rounded the corner into" | | 3 | "She didn't register the words." | | 4 | "She'd spent every spare hour" | | 5 | "She'd watched the exchange from" | | 6 | "He bolted, and here they" | | 7 | "He was fifty yards ahead," | | 8 | "She hurdled a fallen crate" | | 9 | "Her chest heaved." | | 10 | "She looked back the way" | | 11 | "She'd called it in when" | | 12 | "She didn't have that." | | 13 | "She looked down the staircase." | | 14 | "She drew her warrant card," | | 15 | "She rattled off the street" | | 16 | "She pocketed the phone and" | | 17 | "He didn't stop." | | 18 | "He didn't even slow." | | 19 | "He pushed through a heavy" |
| | ratio | 0.241 | |
| 89.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 120 | | totalSentences | 162 | | matches | | 0 | "# Chapter Seven The suspect" | | 1 | "Quinn didn't slow down." | | 2 | "She hit the iron rail" | | 3 | "Pain shot up her left" | | 4 | "She swallowed it and kept" | | 5 | "The figure ahead glanced back." | | 6 | "Hood up, face shadowed, but" | | 7 | "A medallion, maybe." | | 8 | "He rounded the corner into" | | 9 | "A taxi blared its horn" | | 10 | "The driver swore." | | 11 | "She didn't register the words." | | 12 | "The official cause was cardiac" | | 13 | "A healthy forty-three-year-old man with" | | 14 | "She'd spent every spare hour" | | 15 | "Tonight's thread had pulled her" | | 16 | "An envelope of cash exchanged" | | 17 | "The buyer matched a description" | | 18 | "She'd watched the exchange from" | | 19 | "He bolted, and here they" |
| | ratio | 0.741 | |
| 30.86% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 162 | | matches | | | ratio | 0.006 | |
| 31.25% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 10 | | matches | | 0 | "Three years of incident reports that read like fiction, of colleagues who stopped meeting her eyes, of evidence that evaporated between collection and the foren…" | | 1 | "All roads led back to the same knot: a handful of individuals operating in London's margins, the kind who existed in police databases only as footnotes, if at a…" | | 2 | "He was fifty yards ahead, cutting between pedestrians, moving with the fluid economy of someone who knew how to run." | | 3 | "The beam cut through the dark, illuminating graffiti-covered walls that descended at a steep angle." | | 4 | "He pushed through a heavy door at the corridor's end, and it swung shut behind him with a metallic boom that echoed through the tunnel." | | 5 | "Candles and lanterns hung from wires strung between the columns, casting everything in a warm amber glow that made the shadows move like living things." | | 6 | "A woman in a Victorian mourning dress examined a row of glass bottles containing liquids that shifted colour as the light caught them." | | 7 | "She pushed forward, keeping her distance, letting bodies between them provide cover." | | 8 | "Tall, thin, wearing identical grey coats that hung to their ankles." | | 9 | "Looked at the faces around her, human and otherwise, going about their business in a market that shouldn't exist beneath the streets of London." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.148 | | leniency | 0.296 | | rawRatio | 0 | | effectiveRatio | 0 | |