| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.108 | | leniency | 0.216 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1099 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "nervously" |
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| 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) | |
| 22.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1099 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "chill" | | 1 | "gloom" | | 2 | "pang" | | 3 | "etched" | | 4 | "stomach" | | 5 | "whisper" | | 6 | "pulse" | | 7 | "footsteps" | | 8 | "echoed" | | 9 | "scanned" | | 10 | "flickered" | | 11 | "flicked" | | 12 | "trembled" | | 13 | "pulsed" | | 14 | "shimmered" |
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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 | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 11 | | totalWords | 1086 | | ratio | 0.01 | | matches | | 0 | "Aurora Vey." | | 1 | "where" | | 2 | "when" | | 3 | "The Black Ledger" | | 4 | "not supposed to exist" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 772 | | uniqueNames | 12 | | maxNameDensity | 2.33 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Ellis" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 18 | | Detective | 2 | | Sergeant | 1 | | Gary | 1 | | Ellis | 15 | | Yard | 1 | | Morris | 3 | | Kowalski | 1 | | Eva | 7 | | Vey | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Gary" | | 4 | "Ellis" | | 5 | "Morris" | | 6 | "Kowalski" | | 7 | "Eva" |
| | places | | | globalScore | 0.334 | | windowScore | 0.167 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 2 | | matches | | 0 | "quite fit" | | 1 | "not quite light" |
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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 | 1086 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 128 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 19.05 | | std | 16.44 | | cv | 0.863 | | sampleLengths | | 0 | 67 | | 1 | 55 | | 2 | 13 | | 3 | 6 | | 4 | 23 | | 5 | 14 | | 6 | 58 | | 7 | 5 | | 8 | 74 | | 9 | 38 | | 10 | 1 | | 11 | 10 | | 12 | 49 | | 13 | 3 | | 14 | 7 | | 15 | 16 | | 16 | 26 | | 17 | 7 | | 18 | 5 | | 19 | 23 | | 20 | 15 | | 21 | 26 | | 22 | 12 | | 23 | 19 | | 24 | 5 | | 25 | 9 | | 26 | 8 | | 27 | 13 | | 28 | 6 | | 29 | 27 | | 30 | 6 | | 31 | 15 | | 32 | 11 | | 33 | 8 | | 34 | 9 | | 35 | 21 | | 36 | 22 | | 37 | 3 | | 38 | 40 | | 39 | 19 | | 40 | 5 | | 41 | 27 | | 42 | 12 | | 43 | 22 | | 44 | 6 | | 45 | 48 | | 46 | 8 | | 47 | 20 | | 48 | 10 | | 49 | 22 |
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| 94.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 98 | | matches | | 0 | "were flushed" | | 1 | "been sectioned" | | 2 | "was verdigrised" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 136 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 128 | | ratio | 0.078 | | matches | | 0 | "The air smelled of damp stone and something older—ozone, maybe, or spoilt meat left to rot in the dark." | | 1 | "She knew the voice of Detective Sergeant Gary Ellis from the Yard well enough—though not well enough to trust him." | | 2 | "His cheeks were flushed, either from the cold or the excitement, and his tie—some gaudy print—hung askew." | | 3 | "She checked the watch—3:32." | | 4 | "The sigils glowed faintly in her peripheral vision—like embers in dark water." | | 5 | "A fresh bruise circled his wrist—dark, almost purple, like a handprint." | | 6 | "A whisper of memory surfaced—Morris’s voice, strained: “They’re using her as the anchor. Like the others. The Veil’s thinning. She doesn’t know.”" | | 7 | "A woman stepped into the dim light—curly red hair tucked behind round glasses, a satchel slung across her chest." | | 8 | "Eva pulled a book from her satchel—leather-bound, pages yellowed." | | 9 | "A silhouette—tall, draped in something that shimmered like tar in moonlight." |
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| 91.53% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 785 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.049681528662420385 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.014012738853503185 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 8.48 | | std | 6.17 | | cv | 0.727 | | sampleLengths | | 0 | 23 | | 1 | 25 | | 2 | 19 | | 3 | 19 | | 4 | 6 | | 5 | 15 | | 6 | 11 | | 7 | 2 | | 8 | 2 | | 9 | 13 | | 10 | 6 | | 11 | 3 | | 12 | 20 | | 13 | 14 | | 14 | 4 | | 15 | 14 | | 16 | 17 | | 17 | 6 | | 18 | 5 | | 19 | 12 | | 20 | 5 | | 21 | 8 | | 22 | 24 | | 23 | 14 | | 24 | 17 | | 25 | 2 | | 26 | 9 | | 27 | 11 | | 28 | 5 | | 29 | 2 | | 30 | 4 | | 31 | 12 | | 32 | 4 | | 33 | 1 | | 34 | 10 | | 35 | 8 | | 36 | 2 | | 37 | 2 | | 38 | 20 | | 39 | 14 | | 40 | 3 | | 41 | 3 | | 42 | 7 | | 43 | 2 | | 44 | 14 | | 45 | 9 | | 46 | 12 | | 47 | 5 | | 48 | 7 | | 49 | 2 |
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| 66.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.421875 | | totalSentences | 128 | | uniqueOpeners | 54 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Too precise to be an" | | 1 | "Then the strip lights flickered" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 82 | | matches | | 0 | "Her leather watch, its face" | | 1 | "She knew the voice of" | | 2 | "She finally faced him." | | 3 | "His cheeks were flushed, either" | | 4 | "It had been Morris’s favourite." | | 5 | "She crouched beside him, brushing" | | 6 | "She checked the watch—3:32." | | 7 | "Her stomach clenched." | | 8 | "She stood abruptly." | | 9 | "She exhaled through her nose." | | 10 | "She waved a hand over" | | 11 | "She reached toward the compass." | | 12 | "She paused, eye fixed on" | | 13 | "He hesitated, then tugged his" | | 14 | "She reached for the compass" | | 15 | "She yanked her arm free." | | 16 | "She turned the compass over." | | 17 | "Her pulse spiked." | | 18 | "Her green eyes scanned the" | | 19 | "Her gaze flickered to the" |
| | ratio | 0.268 | |
| 20.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 82 | | matches | | 0 | "Rain splattered against the scuffed" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The air smelled of damp" | | 3 | "Quinn pressed her palm against" | | 4 | "Her leather watch, its face" | | 5 | "A shadow detached itself from" | | 6 | "Quinn didn’t turn." | | 7 | "She knew the voice of" | | 8 | "She finally faced him." | | 9 | "Ellis was younger, mid-thirties, dressed" | | 10 | "His cheeks were flushed, either" | | 11 | "Quinn had seen that tie" | | 12 | "It had been Morris’s favourite." | | 13 | "A pang shot through her" | | 14 | "Ellis gestured toward the back" | | 15 | "The space between two support" | | 16 | "A man, late twenties, dark" | | 17 | "Quinn didn’t recognise him, but" | | 18 | "She crouched beside him, brushing" | | 19 | "The body was still warm." |
| | ratio | 0.878 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn stepped over a puddle that hadn’t been there a second ago, her shoes disturbing the dust settled across the cracked platform tiles." | | 1 | "A silhouette—tall, draped in something that shimmered like tar in moonlight." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 37 | | tagDensity | 0.027 | | leniency | 0.054 | | rawRatio | 1 | | effectiveRatio | 0.054 | |