| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.49 | | leniency | 0.98 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1756 | | 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) | |
| 85.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1756 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "trembled" | | 2 | "etched" | | 3 | "footsteps" | | 4 | "stark" |
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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 | 94 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1769 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1131 | | uniqueNames | 16 | | maxNameDensity | 1.24 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 14 | | Met | 2 | | Callum | 1 | | Pike | 11 | | Morris | 3 | | Candle | 1 | | Chalk | 1 | | River | 1 | | Thames | 1 | | Footsteps | 1 | | British | 1 | | Museum | 1 | | Eva | 6 | | English | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Pike" | | 3 | "Morris" | | 4 | "Candle" | | 5 | "Museum" | | 6 | "Eva" |
| | places | | 0 | "Met" | | 1 | "River" | | 2 | "Thames" | | 3 | "British" |
| | globalScore | 0.881 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1769 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 120 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 32.76 | | std | 26.92 | | cv | 0.822 | | sampleLengths | | 0 | 39 | | 1 | 57 | | 2 | 44 | | 3 | 39 | | 4 | 23 | | 5 | 16 | | 6 | 2 | | 7 | 60 | | 8 | 5 | | 9 | 60 | | 10 | 2 | | 11 | 9 | | 12 | 73 | | 13 | 5 | | 14 | 52 | | 15 | 31 | | 16 | 16 | | 17 | 57 | | 18 | 26 | | 19 | 44 | | 20 | 12 | | 21 | 68 | | 22 | 12 | | 23 | 12 | | 24 | 50 | | 25 | 13 | | 26 | 51 | | 27 | 4 | | 28 | 54 | | 29 | 5 | | 30 | 10 | | 31 | 5 | | 32 | 56 | | 33 | 52 | | 34 | 28 | | 35 | 3 | | 36 | 43 | | 37 | 13 | | 38 | 89 | | 39 | 2 | | 40 | 40 | | 41 | 3 | | 42 | 5 | | 43 | 6 | | 44 | 73 | | 45 | 66 | | 46 | 97 | | 47 | 11 | | 48 | 4 | | 49 | 100 |
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| 86.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 94 | | matches | | 0 | "been opened" | | 1 | "was fisted" | | 2 | "been etched" | | 3 | "got opened" | | 4 | "been photographed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 189 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 120 | | ratio | 0.058 | | matches | | 0 | "Her torch beam swept the ground ahead of her — a habit Morris had drilled into her, back when drilling her had been his job." | | 1 | "The tiles beneath his neck held nothing but dust and a pale ring where the pooling should have been — as if someone had lifted the body, scrubbed the floor, and laid him back down inside the outline of his own crime scene." | | 2 | "Her beam found the flooded maintenance passage beyond the arch — six inches of standing water, black silt curled at its edges, thick handprints of mud on the railing where the SOCOs had come through." | | 3 | "Chalk marks dusted the tiles beneath it — arcs and strokes, half of them scrubbed away with something wet." | | 4 | "The phone's needle swung to settle on north — behind her, up the platform, toward the river." | | 5 | "The bricks here were old, mortared over, sealed for decades — and yet the air coming off them cut colder than the rest of the station, cold enough that her breath thickened." | | 6 | "\"You must be the consultant.\" Quinn had signed off on the request two hours ago — a researcher from the British Museum's restricted archives, attached to the Met's occult liaison file, a file that got opened perhaps once a decade and had gathered dust since the last time Quinn had needed it." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1131 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 16 | | adverbRatio | 0.014146772767462422 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0017683465959328027 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 14.74 | | std | 13.12 | | cv | 0.89 | | sampleLengths | | 0 | 19 | | 1 | 6 | | 2 | 14 | | 3 | 12 | | 4 | 22 | | 5 | 23 | | 6 | 11 | | 7 | 15 | | 8 | 18 | | 9 | 4 | | 10 | 25 | | 11 | 10 | | 12 | 14 | | 13 | 9 | | 14 | 2 | | 15 | 14 | | 16 | 2 | | 17 | 6 | | 18 | 10 | | 19 | 1 | | 20 | 43 | | 21 | 5 | | 22 | 22 | | 23 | 38 | | 24 | 2 | | 25 | 4 | | 26 | 5 | | 27 | 12 | | 28 | 35 | | 29 | 26 | | 30 | 5 | | 31 | 52 | | 32 | 17 | | 33 | 14 | | 34 | 1 | | 35 | 1 | | 36 | 14 | | 37 | 28 | | 38 | 29 | | 39 | 3 | | 40 | 23 | | 41 | 11 | | 42 | 19 | | 43 | 14 | | 44 | 6 | | 45 | 2 | | 46 | 4 | | 47 | 6 | | 48 | 36 | | 49 | 26 |
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| 73.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.48333333333333334 | | totalSentences | 120 | | uniqueOpeners | 58 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 88.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 82 | | matches | | 0 | "She counted them out of" | | 1 | "He stood at the edge" | | 2 | "Her torch beam swept the" | | 3 | "She pushed the thought down" | | 4 | "His throat had been opened" | | 5 | "She held her torch close" | | 6 | "Her beam found the flooded" | | 7 | "She stood and turned in" | | 8 | "She crouched again and pressed" | | 9 | "She scraped at the edge" | | 10 | "She held up the disc" | | 11 | "She locked her wrist." | | 12 | "She had seen that mark" | | 13 | "She circled the body." | | 14 | "She nodded to the nearest" | | 15 | "It strained toward the bricks" | | 16 | "She pressed her palm flat" | | 17 | "He did, and pulled his" | | 18 | "She dug through it as" | | 19 | "She stopped at the table," |
| | ratio | 0.329 | |
| 2.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 82 | | matches | | 0 | "The ladder down into the" | | 1 | "She counted them out of" | | 2 | "The platform below stretched into" | | 3 | "A generator chugged somewhere in" | | 4 | "DS Callum Pike's voice bounced" | | 5 | "He stood at the edge" | | 6 | "Quinn crossed the platform." | | 7 | "Her torch beam swept the" | | 8 | "She pushed the thought down" | | 9 | "The dead man lay face-down" | | 10 | "His throat had been opened" | | 11 | "She held her torch close" | | 12 | "The tiles beneath his neck" | | 13 | "Pike crouched opposite her, careful" | | 14 | "Pike glanced at them." | | 15 | "Brogues, cracked at the heel." | | 16 | "Quinn angled her torch along" | | 17 | "Her beam found the flooded" | | 18 | "She stood and turned in" | | 19 | "Candle stubs ringed the folding" |
| | ratio | 0.915 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "Thirty-two, ambitious, the kind of detective who treated every case like a box to be ticked and filed." | | 1 | "The tiles beneath his neck held nothing but dust and a pale ring where the pooling should have been — as if someone had lifted the body, scrubbed the floor, and…" | | 2 | "She nodded to the nearest SOCO, who worked the fingers open with tweezers and lifted out a small brass compass on a tarnished chain." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "The pathologist had (have)" |
| | dialogueSentences | 51 | | tagDensity | 0.118 | | leniency | 0.235 | | rawRatio | 0.167 | | effectiveRatio | 0.039 | |