| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 31 | | adverbTagCount | 3 | | adverbTags | | 0 | "Quinn said aloud [aloud]" | | 1 | "Quinn said sharply [sharply]" | | 2 | "she said softly [softly]" |
| | dialogueSentences | 69 | | tagDensity | 0.449 | | leniency | 0.899 | | rawRatio | 0.097 | | effectiveRatio | 0.087 | |
| 96.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2894 | | 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) | |
| 86.18% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2894 | | totalAiIsms | 8 | | found | | 0 | | | 1 | | | 2 | | | 3 | | word | "voice hitched" | | count | 1 |
| | 4 | | | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "etched" | | 1 | "warmth" | | 2 | "traced" | | 3 | "voice hitched" | | 4 | "gleaming" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "weight" |
| |
| 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 | 198 | | matches | (empty) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 3 | | narrationSentences | 198 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 237 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 69 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2877 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 33 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 78 | | wordCount | 1911 | | uniqueNames | 9 | | maxNameDensity | 2.09 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 40 | | Kowalski | 1 | | Eva | 22 | | Veil | 1 | | Market | 2 | | Memory | 1 | | Morris | 3 | | Pryce | 7 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Market" | | 5 | "Memory" | | 6 | "Morris" | | 7 | "Pryce" |
| | places | | | globalScore | 0.453 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 133 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like sulphur and old iron" | | 1 | "tasted like rust again" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 0.695 | | wordCount | 2877 | | matches | | 0 | "not to the body but down the tunnel" | | 1 | "not yet formed a whole, but she could see the seam" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 237 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 33.85 | | std | 20.2 | | cv | 0.597 | | sampleLengths | | 0 | 76 | | 1 | 60 | | 2 | 38 | | 3 | 34 | | 4 | 38 | | 5 | 15 | | 6 | 26 | | 7 | 15 | | 8 | 19 | | 9 | 7 | | 10 | 44 | | 11 | 6 | | 12 | 22 | | 13 | 63 | | 14 | 49 | | 15 | 51 | | 16 | 52 | | 17 | 27 | | 18 | 13 | | 19 | 16 | | 20 | 20 | | 21 | 27 | | 22 | 62 | | 23 | 71 | | 24 | 26 | | 25 | 40 | | 26 | 15 | | 27 | 45 | | 28 | 39 | | 29 | 6 | | 30 | 17 | | 31 | 53 | | 32 | 35 | | 33 | 17 | | 34 | 48 | | 35 | 25 | | 36 | 11 | | 37 | 32 | | 38 | 34 | | 39 | 6 | | 40 | 19 | | 41 | 6 | | 42 | 35 | | 43 | 101 | | 44 | 50 | | 45 | 36 | | 46 | 40 | | 47 | 13 | | 48 | 44 | | 49 | 56 |
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| 85.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 11 | | totalSentences | 198 | | matches | | 0 | "been written" | | 1 | "been rubbed" | | 2 | "was drawn" | | 3 | "been scuffed" | | 4 | "been shoved" | | 5 | "been when" | | 6 | "been dampened" | | 7 | "been unfastened" | | 8 | "been pried" | | 9 | "been forced" | | 10 | "was forced" | | 11 | "was stamped" | | 12 | "been left" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 350 | | matches | | |
| 34.36% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 4 | | flaggedSentences | 9 | | totalSentences | 237 | | ratio | 0.038 | | matches | | 0 | "The circle had a dark smudge at one side where the chalk had been rubbed; someone had walked through it after it was drawn." | | 1 | "The ash came from a fine, fine burn—tobacco perhaps, or something pressed into a pipe." | | 2 | "He looked younger than Quinn’s partner had been when Quinn lost him—younger than the last case had let her keep." | | 3 | "She had looked at many deaths; she decoded them like maps." | | 4 | "The tunnel smelled of exhaust and wet earth, but beneath that there was something metallic and old—like the inside of an instrument box." | | 5 | "There, toward the far end of the platform where the tiles changed tone, two prints overlapped—one smaller, one larger." | | 6 | "\"It moves with the moon. The vendors change. Pryce is new; he only started selling here last year. The old network broke up after the raid, but someone kept pieces. If someone wanted to clear the Market’s name—if they wanted to take a particular object without the Market watching—this would be the easiest way. Stage a breach and watch forty pairs of eyes point the wrong way.\"" | | 7 | "Quinn followed the path their suspects had used—toward the service doors, to the pry marks, to the asphalt outside the exit where rain had washed away half the trail." | | 8 | "The platform's flood of commuters would come back within hours; the scene would fill with a thousand casual eyes." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1633 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.01653398652786283 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.003061849357011635 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 237 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 237 | | mean | 12.14 | | std | 9.36 | | cv | 0.771 | | sampleLengths | | 0 | 9 | | 1 | 20 | | 2 | 23 | | 3 | 4 | | 4 | 20 | | 5 | 13 | | 6 | 17 | | 7 | 11 | | 8 | 6 | | 9 | 13 | | 10 | 14 | | 11 | 24 | | 12 | 17 | | 13 | 17 | | 14 | 8 | | 15 | 14 | | 16 | 16 | | 17 | 15 | | 18 | 6 | | 19 | 20 | | 20 | 13 | | 21 | 2 | | 22 | 3 | | 23 | 16 | | 24 | 7 | | 25 | 9 | | 26 | 10 | | 27 | 7 | | 28 | 5 | | 29 | 9 | | 30 | 4 | | 31 | 6 | | 32 | 5 | | 33 | 17 | | 34 | 12 | | 35 | 14 | | 36 | 23 | | 37 | 8 | | 38 | 3 | | 39 | 3 | | 40 | 7 | | 41 | 15 | | 42 | 11 | | 43 | 16 | | 44 | 14 | | 45 | 17 | | 46 | 20 | | 47 | 3 | | 48 | 7 | | 49 | 18 |
| |
| 45.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.26582278481012656 | | totalSentences | 237 | | uniqueOpeners | 63 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 173 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 173 | | matches | | 0 | "Her boots didn’t hesitate." | | 1 | "Her watch, worn leather, ticked" | | 2 | "Its casing had a verdigris" | | 3 | "She pushed her glasses up" | | 4 | "Her voice went low, the" | | 5 | "She straightened and picked up" | | 6 | "She hesitated, eyes flicking back" | | 7 | "It was not from the" | | 8 | "It was a copy." | | 9 | "She stopped at a smear" | | 10 | "She cupped it and let" | | 11 | "She tilted the compass so" | | 12 | "She knelt and examined the" | | 13 | "She nudged the compass with" | | 14 | "Her voice cut without warmth." | | 15 | "He stepped back and folded" | | 16 | "He looked younger than Quinn’s" | | 17 | "She had watched Morris vanish" | | 18 | "She had looked at many" | | 19 | "It was for show." |
| | ratio | 0.283 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 163 | | totalSentences | 173 | | matches | | 0 | "Rain had driven the station" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "Her boots didn’t hesitate." | | 3 | "Her watch, worn leather, ticked" | | 4 | "A body lay in the" | | 5 | "The chalk line had been" | | 6 | "A brass compass sat on" | | 7 | "Its casing had a verdigris" | | 8 | "The needle held steady, pointing" | | 9 | "Quinn crouched and spread her" | | 10 | "The circle had a dark" | | 11 | "Eva Kowalski leaned close, the" | | 12 | "She pushed her glasses up" | | 13 | "Her voice went low, the" | | 14 | "She straightened and picked up" | | 15 | "Quinn let the word" | | 16 | "Eva’s mouth tightened." | | 17 | "She hesitated, eyes flicking back" | | 18 | "A uniformed officer handed over" | | 19 | "Quinn turned it over under" |
| | ratio | 0.942 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 173 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 84 | | technicalSentenceCount | 3 | | matches | | 0 | "Fluorescent tubes hummed over the deserted platform, throwing a sickly light that made the symbols on the tiles look wet." | | 1 | "Her watch, worn leather, ticked against the bones of her wrist as though it kept time for other people’s panic." | | 2 | "The protective sigils etched into the brass were neat, as if stamped by a machine rather than hand-scribed." |
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| 92.74% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 31 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn said aloud, and the word dropped into the station like a stone" | | 1 | "she said, voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 28 | | fancyCount | 3 | | fancyTags | | 0 | "Pryce muttered (mutter)" | | 1 | "she murmured (murmur)" | | 2 | "she ordered (order)" |
| | dialogueSentences | 69 | | tagDensity | 0.406 | | leniency | 0.812 | | rawRatio | 0.107 | | effectiveRatio | 0.087 | |