| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "Her voice echoed flatly [flatly]" | | 1 | "Quinn stepped back [back]" |
| | dialogueSentences | 36 | | tagDensity | 0.389 | | leniency | 0.778 | | rawRatio | 0.143 | | effectiveRatio | 0.111 | |
| 92.62% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1355 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 80.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 70.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1355 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "gloom" | | 1 | "etched" | | 2 | "echoed" | | 3 | "weight" | | 4 | "silk" | | 5 | "traced" | | 6 | "silence" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1355 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 935 | | uniqueNames | 8 | | maxNameDensity | 1.71 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 16 | | Camden | 1 | | Town | 1 | | Hall | 1 | | Detective | 1 | | Sergeant | 1 | | Millbrook | 8 | | Pembroke | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Millbrook" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Hall" | | 3 | "Pembroke" |
| | globalScore | 0.644 | | windowScore | 0.333 | |
| 79.58% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like he was missing his sixth-form" | | 1 | "looked like a shuffle of footprints, all" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.738 | | wordCount | 1355 | | matches | | 0 | "not as a stage, but as a snapshot" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 33.88 | | std | 19.84 | | cv | 0.586 | | sampleLengths | | 0 | 59 | | 1 | 47 | | 2 | 10 | | 3 | 37 | | 4 | 39 | | 5 | 25 | | 6 | 46 | | 7 | 18 | | 8 | 25 | | 9 | 43 | | 10 | 21 | | 11 | 4 | | 12 | 11 | | 13 | 36 | | 14 | 62 | | 15 | 54 | | 16 | 7 | | 17 | 51 | | 18 | 35 | | 19 | 52 | | 20 | 35 | | 21 | 75 | | 22 | 8 | | 23 | 32 | | 24 | 59 | | 25 | 54 | | 26 | 31 | | 27 | 6 | | 28 | 15 | | 29 | 38 | | 30 | 36 | | 31 | 11 | | 32 | 63 | | 33 | 23 | | 34 | 5 | | 35 | 47 | | 36 | 14 | | 37 | 4 | | 38 | 58 | | 39 | 59 |
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| 87.18% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 97 | | matches | | 0 | "was propped" | | 1 | "was clenched" | | 2 | "was mottled" | | 3 | "being handled" | | 4 | "been killed" | | 5 | "been drawn" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 145 | | matches | | 0 | "was missing" | | 1 | "wasn't pointing" | | 2 | "was spinning" | | 3 | "was holding" | | 4 | "was going" | | 5 | "was pulling" | | 6 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 116 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 939 | | adjectiveStacks | 1 | | stackExamples | | 0 | "thick, cream-coloured cashmere" |
| | adverbCount | 26 | | adverbRatio | 0.027689030883919063 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007454739084132056 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 11.68 | | std | 7.95 | | cv | 0.681 | | sampleLengths | | 0 | 16 | | 1 | 17 | | 2 | 26 | | 3 | 12 | | 4 | 20 | | 5 | 15 | | 6 | 10 | | 7 | 15 | | 8 | 16 | | 9 | 6 | | 10 | 21 | | 11 | 13 | | 12 | 5 | | 13 | 18 | | 14 | 7 | | 15 | 4 | | 16 | 20 | | 17 | 8 | | 18 | 14 | | 19 | 8 | | 20 | 10 | | 21 | 14 | | 22 | 11 | | 23 | 34 | | 24 | 9 | | 25 | 3 | | 26 | 18 | | 27 | 4 | | 28 | 10 | | 29 | 1 | | 30 | 3 | | 31 | 33 | | 32 | 8 | | 33 | 7 | | 34 | 11 | | 35 | 12 | | 36 | 6 | | 37 | 6 | | 38 | 2 | | 39 | 2 | | 40 | 4 | | 41 | 4 | | 42 | 14 | | 43 | 9 | | 44 | 9 | | 45 | 22 | | 46 | 7 | | 47 | 7 | | 48 | 44 | | 49 | 17 |
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| 54.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3706896551724138 | | totalSentences | 116 | | uniqueOpeners | 43 | |
| 70.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 94 | | matches | | 0 | "Then the silence of the" | | 1 | "Then, from far down the" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 94 | | matches | | 0 | "It was ozone, sharp and" | | 1 | "She ducked under the yellow-and-black" | | 2 | "Her voice echoed flatly off" | | 3 | "He was a solid, dependable" | | 4 | "He paused for effect" | | 5 | "She ignored him and crouched" | | 6 | "Her clothes were too clean" | | 7 | "he countered, his tone bordering" | | 8 | "Its casing was mottled with" | | 9 | "It was spinning, a slow," | | 10 | "She stood, turning in a" | | 11 | "She pictured the scene not" | | 12 | "Her eyes traced the scattered" | | 13 | "Their prints were obvious." | | 14 | "It led from the tunnel" | | 15 | "He looked flummoxed." | | 16 | "It was a tool." | | 17 | "He saw what she was" | | 18 | "He saw where she was" | | 19 | "She clicked off her torch," |
| | ratio | 0.298 | |
| 34.47% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 94 | | matches | | 0 | "The smell hit Quinn first," | | 1 | "It was ozone, sharp and" | | 2 | "She ducked under the yellow-and-black" | | 3 | "A city of dust motes" | | 4 | "The air was thick with" | | 5 | "Her voice echoed flatly off" | | 6 | "Detective Sergeant Millbrook detached himself" | | 7 | "He was a solid, dependable" | | 8 | "Quinn's gaze swept the scene" | | 9 | "A single body, female, lay" | | 10 | "Millbrook gestured with his chin" | | 11 | "Quinn moved past him." | | 12 | "The uniformed constable standing sentry," | | 13 | "Quinn ignored him and leaned" | | 14 | "A man was propped inside," | | 15 | "Millbrook said, consulting his notebook" | | 16 | "Quinn looked from the body" | | 17 | "He paused for effect" | | 18 | "Quinn’s jaw tightened." | | 19 | "Quinn stepped back from the" |
| | ratio | 0.851 | |
| 53.19% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 94 | | matches | | | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 2 | | matches | | 0 | "The uniformed constable standing sentry, a lad who looked like he was missing his sixth-form lecture, shifted his weight nervously." | | 1 | "It was spinning, a slow, violent tremble that hadn't settled since she died." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 5 | | matches | | 0 | "Quinn asked, her voice tight" | | 1 | "he countered, his tone bordering on defensive" | | 2 | "Millbrook asked, his voice losing its bluster" | | 3 | "Quinn said, her voice dropping" | | 4 | "She drew, its beam slicing into the black" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 36 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0 | | effectiveRatio | 0 | |