| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva said quietly [quietly]" | | 1 | "Eva said softly [softly]" |
| | dialogueSentences | 38 | | tagDensity | 0.421 | | leniency | 0.842 | | rawRatio | 0.125 | | effectiveRatio | 0.105 | |
| 62.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2022 | | totalAiIsmAdverbs | 15 | | found | | | highlights | | 0 | "carefully" | | 1 | "slightly" | | 2 | "perfectly" | | 3 | "slowly" | | 4 | "truly" | | 5 | "softly" | | 6 | "gently" | | 7 | "lazily" | | 8 | "sharply" | | 9 | "suddenly" |
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| 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) | |
| 62.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2022 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "could feel" | | 1 | "etched" | | 2 | "weight" | | 3 | "trembled" | | 4 | "pulse" | | 5 | "familiar" | | 6 | "traced" | | 7 | "flickered" | | 8 | "charged" | | 9 | "echoing" | | 10 | "constructed" | | 11 | "raced" | | 12 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 178 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 178 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 198 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2012 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 1 | | matches | | 0 | "Her satchel clinked—glass vials, Quinn guessed." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 84 | | wordCount | 1618 | | uniqueNames | 15 | | maxNameDensity | 2.04 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Harlow | 2 | | Quinn | 33 | | Constable | 1 | | Patel | 8 | | Kowalski | 2 | | Eva | 25 | | Morris | 4 | | London | 1 | | Glock | 1 | | Market | 2 | | Latin | 1 | | Ahead | 1 | | Veil | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Constable" | | 4 | "Patel" | | 5 | "Kowalski" | | 6 | "Eva" | | 7 | "Morris" | | 8 | "Market" | | 9 | "Latin" |
| | places | | | globalScore | 0.48 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | glossingSentenceCount | 2 | | matches | | 0 | "as though listening for a train that would never come" | | 1 | "sounded like bastard Latin mixed with some" |
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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 | 2012 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 198 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 26.13 | | std | 16.97 | | cv | 0.649 | | sampleLengths | | 0 | 83 | | 1 | 54 | | 2 | 2 | | 3 | 60 | | 4 | 20 | | 5 | 14 | | 6 | 59 | | 7 | 19 | | 8 | 3 | | 9 | 18 | | 10 | 14 | | 11 | 34 | | 12 | 17 | | 13 | 14 | | 14 | 10 | | 15 | 59 | | 16 | 46 | | 17 | 25 | | 18 | 38 | | 19 | 21 | | 20 | 44 | | 21 | 6 | | 22 | 27 | | 23 | 24 | | 24 | 23 | | 25 | 59 | | 26 | 26 | | 27 | 7 | | 28 | 28 | | 29 | 32 | | 30 | 13 | | 31 | 4 | | 32 | 60 | | 33 | 28 | | 34 | 57 | | 35 | 20 | | 36 | 10 | | 37 | 37 | | 38 | 42 | | 39 | 45 | | 40 | 14 | | 41 | 29 | | 42 | 21 | | 43 | 35 | | 44 | 31 | | 45 | 7 | | 46 | 6 | | 47 | 38 | | 48 | 4 | | 49 | 56 |
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| 91.46% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 178 | | matches | | 0 | "been replaced" | | 1 | "been dressed" | | 2 | "been placed" | | 3 | "been found" | | 4 | "been sealed" | | 5 | "been seen" | | 6 | "was gone" |
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| 5.35% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 8 | | totalVerbs | 274 | | matches | | 0 | "was whispering" | | 1 | "was watching" | | 2 | "was quietly building" | | 3 | "were flaring" | | 4 | "was backing" | | 5 | "was speaking" | | 6 | "was beginning" | | 7 | "was shaking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 1 | | flaggedSentences | 10 | | totalSentences | 198 | | ratio | 0.051 | | matches | | 0 | "The abandoned Tube station beneath Camden smelled of damp concrete, ozone, and something sharper—burnt copper and old incense." | | 1 | "The man’s skin looked waxen under the harsh light, almost translucent, and his eyes—" | | 2 | "The way his clothes—expensive wool coat, tailored shirt—showed no creasing, as though he had been dressed after death." | | 3 | "Her satchel clinked—glass vials, Quinn guessed." | | 4 | "She had seen that compass before—briefly—during the Morris investigation." | | 5 | "Eva’s nervous habit returned; the curl tucked behind her ear again." | | 6 | "She looked at Eva Kowalski—childhood friend of someone Quinn had been watching for months, the clique the detective was quietly building a file on." | | 7 | "She could smell the ozone again, stronger now, and something sweet underneath it—like rotting lilies." | | 8 | "She saw it then—the detail everyone else had missed." | | 9 | "And someone—something—had just accepted on her behalf." |
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| 82.47% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1637 | | adjectiveStacks | 1 | | stackExamples | | 0 | "cutting tight, disciplined arcs." |
| | adverbCount | 83 | | adverbRatio | 0.05070250458155162 | | lyAdverbCount | 37 | | lyAdverbRatio | 0.022602321319486866 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 198 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 198 | | mean | 10.16 | | std | 6.88 | | cv | 0.677 | | sampleLengths | | 0 | 18 | | 1 | 16 | | 2 | 24 | | 3 | 25 | | 4 | 8 | | 5 | 2 | | 6 | 2 | | 7 | 3 | | 8 | 18 | | 9 | 21 | | 10 | 2 | | 11 | 27 | | 12 | 16 | | 13 | 17 | | 14 | 5 | | 15 | 15 | | 16 | 7 | | 17 | 7 | | 18 | 16 | | 19 | 24 | | 20 | 2 | | 21 | 3 | | 22 | 14 | | 23 | 4 | | 24 | 11 | | 25 | 2 | | 26 | 2 | | 27 | 3 | | 28 | 4 | | 29 | 14 | | 30 | 14 | | 31 | 4 | | 32 | 9 | | 33 | 21 | | 34 | 6 | | 35 | 11 | | 36 | 5 | | 37 | 9 | | 38 | 7 | | 39 | 3 | | 40 | 17 | | 41 | 16 | | 42 | 18 | | 43 | 8 | | 44 | 5 | | 45 | 13 | | 46 | 3 | | 47 | 3 | | 48 | 2 | | 49 | 10 |
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| 54.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.35353535353535354 | | totalSentences | 198 | | uniqueOpeners | 70 | |
| 87.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 152 | | matches | | 0 | "Only two figures waited in" | | 1 | "Instead she walked the perimeter" | | 2 | "Simply no longer there." | | 3 | "Only the compass and the" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 152 | | matches | | 0 | "Her boots rang against the" | | 1 | "She had expected the usual" | | 2 | "She clutched her worn leather" | | 3 | "She swept her torch across" | | 4 | "She kept tucking a lock" | | 5 | "she told Eva, though her" | | 6 | "She noted the absence of" | | 7 | "It came away faintly greasy," | | 8 | "She had heard similar explanations" | | 9 | "Her satchel clinked—glass vials, Quinn" | | 10 | "She was watching Eva’s hands." | | 11 | "She had seen that compass" | | 12 | "She kept her face blank." | | 13 | "It wasn’t a question." | | 14 | "She shone her torch upward." | | 15 | "She crouched once more beside" | | 16 | "She slipped the token into" | | 17 | "She looked at Eva Kowalski—childhood" | | 18 | "It was not a question." | | 19 | "She turned back to the" |
| | ratio | 0.243 | |
| 38.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 152 | | matches | | 0 | "The abandoned Tube station beneath" | | 1 | "Detective Harlow Quinn descended the" | | 2 | "Her boots rang against the" | | 3 | "The call had come in" | | 4 | "She had expected the usual" | | 5 | "The occult researcher stood half" | | 6 | "She clutched her worn leather" | | 7 | "Patel said, straightening" | | 8 | "Quinn’s voice was low, clipped" | | 9 | "She swept her torch across" | | 10 | "The body lay near the" | | 11 | "Arms folded across the chest," | | 12 | "The man’s skin looked waxen" | | 13 | "Quinn crouched, knees cracking." | | 14 | "The victim’s eyes had been" | | 15 | "Eva shifted behind her." | | 16 | "Quinn could feel the woman’s" | | 17 | "Eva said quietly" | | 18 | "Quinn rose slowly, turning." | | 19 | "She kept tucking a lock" |
| | ratio | 0.842 | |
| 32.89% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 152 | | matches | | 0 | "As though it had simply" |
| | ratio | 0.007 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 69 | | technicalSentenceCount | 4 | | matches | | 0 | "When she spotted Quinn, her freckled face tightened with something that might have been recognition or dread." | | 1 | "The way his clothes—expensive wool coat, tailored shirt—showed no creasing, as though he had been dressed after death." | | 2 | "A compass, verdigris patina thick on its casing, face etched with sigils that matched the ones on the platform." | | 3 | "The dead man smiled with a mouth that was beginning to split at the corners, revealing rows of small, sharp teeth that definitely had not been there a moment ag…" |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "she told, though her attention had already slid back to the body" | | 1 | "Eva said, voice low enough that Patel couldn’t hear," | | 2 | "she said, voice hard as flint," |
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| 71.05% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Eva whispered (whisper)" | | 2 | "Eva breathed (breathe)" |
| | dialogueSentences | 38 | | tagDensity | 0.368 | | leniency | 0.737 | | rawRatio | 0.214 | | effectiveRatio | 0.158 | |