| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.242 | | leniency | 0.485 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1020 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 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 | 1020 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "perfect" | | 1 | "etched" | | 2 | "magnetic" |
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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 | 34 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 34 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 59 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 72 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1022 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 91.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 601 | | uniqueNames | 7 | | maxNameDensity | 1.16 | | worstName | "Patel" | | maxWindowNameDensity | 2 | | worstWindowName | "Patel" | | discoveredNames | | Chalk | 1 | | Farm | 1 | | Road | 1 | | July | 1 | | Patel | 7 | | Quinn | 6 | | Morris | 2 |
| | persons | | 0 | "Patel" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.918 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 24 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like years, but the paint tin sitt" | | 1 | "looked like verdigris, the same green-bla" | | 2 | "quite manage it" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1022 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 59 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 29.2 | | std | 22.69 | | cv | 0.777 | | sampleLengths | | 0 | 75 | | 1 | 41 | | 2 | 39 | | 3 | 56 | | 4 | 38 | | 5 | 6 | | 6 | 12 | | 7 | 8 | | 8 | 12 | | 9 | 50 | | 10 | 36 | | 11 | 15 | | 12 | 48 | | 13 | 10 | | 14 | 14 | | 15 | 26 | | 16 | 72 | | 17 | 1 | | 18 | 17 | | 19 | 40 | | 20 | 17 | | 21 | 5 | | 22 | 25 | | 23 | 12 | | 24 | 4 | | 25 | 29 | | 26 | 25 | | 27 | 51 | | 28 | 17 | | 29 | 5 | | 30 | 16 | | 31 | 28 | | 32 | 93 | | 33 | 13 | | 34 | 66 |
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| 74.30% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 34 | | matches | | 0 | "been disturbed" | | 1 | "been crouched" | | 2 | "been painted" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 112 | | matches | | |
| 94.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 59 | | ratio | 0.017 | | matches | | 0 | "The address had come through at half four in the morning, scrawled on a call log that made no sense to anyone at the station — a flat above a defunct locksmith's on Chalk Farm Road, reported by a neighbour who'd smelled something through the floorboards." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 603 | | adjectiveStacks | 1 | | stackExamples | | 0 | "same green-black bloom" |
| | adverbCount | 16 | | adverbRatio | 0.026533996683250415 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004975124378109453 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 59 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 59 | | mean | 17.32 | | std | 13.94 | | cv | 0.805 | | sampleLengths | | 0 | 46 | | 1 | 29 | | 2 | 7 | | 3 | 34 | | 4 | 16 | | 5 | 23 | | 6 | 4 | | 7 | 34 | | 8 | 18 | | 9 | 4 | | 10 | 34 | | 11 | 6 | | 12 | 7 | | 13 | 5 | | 14 | 8 | | 15 | 12 | | 16 | 26 | | 17 | 5 | | 18 | 19 | | 19 | 15 | | 20 | 21 | | 21 | 15 | | 22 | 4 | | 23 | 6 | | 24 | 38 | | 25 | 10 | | 26 | 14 | | 27 | 26 | | 28 | 57 | | 29 | 10 | | 30 | 5 | | 31 | 1 | | 32 | 17 | | 33 | 26 | | 34 | 14 | | 35 | 8 | | 36 | 9 | | 37 | 5 | | 38 | 4 | | 39 | 21 | | 40 | 7 | | 41 | 5 | | 42 | 4 | | 43 | 29 | | 44 | 7 | | 45 | 18 | | 46 | 19 | | 47 | 32 | | 48 | 9 | | 49 | 8 |
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| 93.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.6101694915254238 | | totalSentences | 59 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 30 | | matches | (empty) | | ratio | 0 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 30 | | matches | | 0 | "It caught the torchlight with" | | 1 | "She didn't answer that." | | 2 | "Her eyes had caught the" | | 3 | "She moved to the far" | | 4 | "She hadn't thought about that" | | 5 | "She'd trained herself not to." | | 6 | "He did, humouring her." | | 7 | "He set the compass down" | | 8 | "She stood, brushing salt from" | | 9 | "She looked back at the" |
| | ratio | 0.333 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 30 | | totalSentences | 30 | | matches | | 0 | "The address had come through" | | 1 | "Quinn climbed the narrow stairwell" | | 2 | "The door to the flat" | | 3 | "Frost rimed the inside of" | | 4 | "DS Patel straightened from where" | | 5 | "Quinn crossed the threshold." | | 6 | "The man lay on his" | | 7 | "A ring of salt circled" | | 8 | "Patel checked his notes, flipped" | | 9 | "Quinn crouched at the edge" | | 10 | "The salt wasn't table salt." | | 11 | "It caught the torchlight with" | | 12 | "She didn't answer that." | | 13 | "Her eyes had caught the" | | 14 | "Every window in the flat" | | 15 | "She moved to the far" | | 16 | "She hadn't thought about that" | | 17 | "She'd trained herself not to." | | 18 | "Patel crouched, reached, came back" | | 19 | "The needle spun, lazy, unbothered" |
| | ratio | 1 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 30 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 17 | | technicalSentenceCount | 8 | | matches | | 0 | "The address had come through at half four in the morning, scrawled on a call log that made no sense to anyone at the station — a flat above a defunct locksmith'…" | | 1 | "Quinn climbed the narrow stairwell with her torch cutting through dust that hung motionless in the air, like it hadn't been disturbed in years despite the build…" | | 2 | "Frost rimed the inside of the frame, thick as the kind that formed on a freezer left unplugged for a week, except it was July and the heatwave outside had turne…" | | 3 | "It caught the torchlight with a faint blue shimmer, coarse-grained, laid down in a hand that hadn't been shaking." | | 4 | "She moved to the far wall where a mirror hung, its surface clouded with a residue that looked like verdigris, the same green-black bloom she'd seen once on an o…" | | 5 | "Patel crouched, reached, came back with a small brass compass, its casing dulled with the same green corrosion, its face etched with markings that weren't numbe…" | | 6 | "The needle swung hard, snapped toward the blacked-out glass and held there, trembling, as if the glass itself were pulling it." | | 7 | "A scorch mark, no bigger than a coin, blackened the plaster, radiating outward in a pattern that reminded her of frost crystallising on a window, except drawn i…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.152 | | leniency | 0.303 | | rawRatio | 0 | | effectiveRatio | 0 | |