| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 35 | | tagDensity | 0.514 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 992 | | 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) | |
| 84.88% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 992 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "weight" | | 1 | "flicked" | | 2 | "wavered" |
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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 | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 997 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 679 | | uniqueNames | 6 | | maxNameDensity | 1.33 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 9 | | Town | 1 | | Pratt | 5 | | Morris | 1 | | Eva | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Pratt" | | 3 | "Morris" | | 4 | "Eva" |
| | places | | | globalScore | 0.837 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | 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 | 997 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 81 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 31.16 | | std | 23.24 | | cv | 0.746 | | sampleLengths | | 0 | 17 | | 1 | 62 | | 2 | 13 | | 3 | 33 | | 4 | 45 | | 5 | 22 | | 6 | 8 | | 7 | 50 | | 8 | 9 | | 9 | 3 | | 10 | 15 | | 11 | 68 | | 12 | 10 | | 13 | 1 | | 14 | 78 | | 15 | 26 | | 16 | 55 | | 17 | 44 | | 18 | 81 | | 19 | 19 | | 20 | 53 | | 21 | 5 | | 22 | 12 | | 23 | 26 | | 24 | 45 | | 25 | 15 | | 26 | 67 | | 27 | 8 | | 28 | 23 | | 29 | 4 | | 30 | 41 | | 31 | 39 |
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| 88.82% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 64 | | matches | | 0 | "been sealed" | | 1 | "been pulled" | | 2 | "been warned " |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 115 | | matches | (empty) | |
| 1.76% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 81 | | ratio | 0.049 | | matches | | 0 | "The dust lay thick and undisturbed across the steps above him — except for a single trail where the loosed shoe had skidded." | | 1 | "Something sharp at the back of her throat, like the air before a thunderstorm — ozone, but wrong, threaded with a sweetness that didn't belong this far from any flower." | | 2 | "The skin beneath was unmarked, save for a faint discolouration along the side of the throat — not bruising." | | 3 | "\"Eva Kowalski. I consult. For the Museum. The restricted archives.\" She descended the rest of the way, stepping over the loose third step without looking, as if she'd been warned — or knew." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 679 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.023564064801178203 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005891016200294551 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 12.31 | | std | 9.51 | | cv | 0.773 | | sampleLengths | | 0 | 17 | | 1 | 21 | | 2 | 28 | | 3 | 13 | | 4 | 11 | | 5 | 2 | | 6 | 9 | | 7 | 13 | | 8 | 2 | | 9 | 9 | | 10 | 21 | | 11 | 4 | | 12 | 20 | | 13 | 5 | | 14 | 17 | | 15 | 8 | | 16 | 4 | | 17 | 40 | | 18 | 6 | | 19 | 2 | | 20 | 5 | | 21 | 2 | | 22 | 3 | | 23 | 15 | | 24 | 17 | | 25 | 23 | | 26 | 3 | | 27 | 3 | | 28 | 16 | | 29 | 6 | | 30 | 7 | | 31 | 3 | | 32 | 1 | | 33 | 23 | | 34 | 31 | | 35 | 24 | | 36 | 12 | | 37 | 14 | | 38 | 17 | | 39 | 32 | | 40 | 6 | | 41 | 9 | | 42 | 35 | | 43 | 11 | | 44 | 7 | | 45 | 17 | | 46 | 16 | | 47 | 30 | | 48 | 6 | | 49 | 3 |
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| 88.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5432098765432098 | | totalSentences | 81 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 95.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 58 | | matches | | 0 | "Her worn leather watch caught" | | 1 | "She'd been pulled from a" | | 2 | "His left shoe had come" | | 3 | "He gestured at the unnatural" | | 4 | "She didn't touch the body." | | 5 | "She let her gaze travel" | | 6 | "She tapped the step beside" | | 7 | "She mimed it with two" | | 8 | "She pointed to the dead" | | 9 | "She held her hand over" | | 10 | "She rose, knees protesting, and" | | 11 | "She'd smelled that scent once" | | 12 | "Her jaw tightened." | | 13 | "She crouched again, this time" | | 14 | "She didn't know what it" | | 15 | "She descended the rest of" | | 16 | "Her gaze went straight to" | | 17 | "She glanced up" |
| | ratio | 0.31 | |
| 72.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 58 | | matches | | 0 | "The body lay at the" | | 1 | "Detective Harlow Quinn paused at" | | 2 | "Camden Town station's abandoned eastern" | | 3 | "a voice called up" | | 4 | "Quinn descended without answering, counting" | | 5 | "Her worn leather watch caught" | | 6 | "She'd been pulled from a" | | 7 | "The man at the base" | | 8 | "His left shoe had come" | | 9 | "The constable straightened" | | 10 | "Pratt shifted his weight." | | 11 | "He gestured at the unnatural" | | 12 | "She didn't touch the body." | | 13 | "She let her gaze travel" | | 14 | "The dust lay thick and" | | 15 | "A man who fell down" | | 16 | "This one had left a" | | 17 | "She tapped the step beside" | | 18 | "She mimed it with two" | | 19 | "She pointed to the dead" |
| | ratio | 0.776 | |
| 86.21% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 58 | | matches | | 0 | "To the silver branching." |
| | ratio | 0.017 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 2 | | matches | | 0 | "Camden Town station's abandoned eastern shaft had been sealed since the seventies, and the air carried the particular staleness of a place that breathed only it…" | | 1 | "Something sharp at the back of her throat, like the air before a thunderstorm — ozone, but wrong, threaded with a sweetness that didn't belong this far from any…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "She rose knees protesting (protest)" |
| | dialogueSentences | 35 | | tagDensity | 0.114 | | leniency | 0.229 | | rawRatio | 0.25 | | effectiveRatio | 0.057 | |