| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 92.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1277 | | 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) | |
| 37.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1277 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "fractured" | | 1 | "scanned" | | 2 | "silence" | | 3 | "rhythmic" | | 4 | "vibrated" | | 5 | "dancing" | | 6 | "kaleidoscope" | | 7 | "velvet" | | 8 | "flicker" | | 9 | "cacophony" | | 10 | "silk" | | 11 | "resonance" | | 12 | "weight" | | 13 | "racing" | | 14 | "gloom" |
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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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 91 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1273 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.14% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1129 | | uniqueNames | 7 | | maxNameDensity | 1.42 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 2 | | Harlow | 1 | | Quinn | 16 | | London | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Tomás" |
| | places | | | globalScore | 0.791 | | windowScore | 0.833 | |
| 82.43% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared pale almost translucent" | | 1 | "tasted like ash and bitter almonds" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.786 | | wordCount | 1273 | | matches | | 0 | "not out of respect, but as if she were a ghost they chose not to acknowledge" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 107 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 25.98 | | std | 19.82 | | cv | 0.763 | | sampleLengths | | 0 | 49 | | 1 | 2 | | 2 | 62 | | 3 | 41 | | 4 | 30 | | 5 | 42 | | 6 | 2 | | 7 | 66 | | 8 | 2 | | 9 | 56 | | 10 | 24 | | 11 | 5 | | 12 | 74 | | 13 | 19 | | 14 | 3 | | 15 | 58 | | 16 | 44 | | 17 | 49 | | 18 | 4 | | 19 | 26 | | 20 | 2 | | 21 | 20 | | 22 | 15 | | 23 | 14 | | 24 | 23 | | 25 | 23 | | 26 | 40 | | 27 | 32 | | 28 | 50 | | 29 | 29 | | 30 | 5 | | 31 | 20 | | 32 | 6 | | 33 | 30 | | 34 | 3 | | 35 | 41 | | 36 | 11 | | 37 | 52 | | 38 | 43 | | 39 | 8 | | 40 | 10 | | 41 | 4 | | 42 | 11 | | 43 | 22 | | 44 | 44 | | 45 | 7 | | 46 | 5 | | 47 | 24 | | 48 | 21 |
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| 97.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 91 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 176 | | matches | | |
| 62.75% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 107 | | ratio | 0.028 | | matches | | 0 | "As she descended, the sounds of the city—the sirens, the rain, the distant bass of Soho—faded into a muffled, rhythmic thrumming." | | 1 | "She saw the flicker of something in his eyes—pity, perhaps, or a warning." | | 2 | "The logic of the street, the rules of the precinct, the certainty of the law—all of it felt thin and fragile here." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1136 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.01936619718309859 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006161971830985915 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 11.9 | | std | 6.37 | | cv | 0.535 | | sampleLengths | | 0 | 17 | | 1 | 20 | | 2 | 12 | | 3 | 2 | | 4 | 11 | | 5 | 4 | | 6 | 16 | | 7 | 11 | | 8 | 20 | | 9 | 7 | | 10 | 11 | | 11 | 10 | | 12 | 13 | | 13 | 12 | | 14 | 16 | | 15 | 2 | | 16 | 14 | | 17 | 13 | | 18 | 15 | | 19 | 2 | | 20 | 13 | | 21 | 10 | | 22 | 12 | | 23 | 14 | | 24 | 17 | | 25 | 2 | | 26 | 14 | | 27 | 21 | | 28 | 3 | | 29 | 18 | | 30 | 8 | | 31 | 16 | | 32 | 5 | | 33 | 4 | | 34 | 21 | | 35 | 11 | | 36 | 14 | | 37 | 24 | | 38 | 19 | | 39 | 3 | | 40 | 14 | | 41 | 21 | | 42 | 23 | | 43 | 17 | | 44 | 17 | | 45 | 10 | | 46 | 6 | | 47 | 28 | | 48 | 15 | | 49 | 4 |
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| 40.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.2803738317757009 | | totalSentences | 107 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 88 | | matches | | 0 | "He bolted, a lithe figure" | | 1 | "She pushed past a group" | | 2 | "She cleared the fence, her" | | 3 | "He pressed against a section" | | 4 | "She scanned the brickwork, her" | | 5 | "She stepped closer, her eyes" | | 6 | "It widened, revealing a stairwell" | | 7 | "It grew dry, smelling of" | | 8 | "She stepped into the fray," | | 9 | "He wore a clean white" | | 10 | "He held a tray of" | | 11 | "She hadn't drawn her badge," | | 12 | "His warm brown eyes held" | | 13 | "He tilted his head, the" | | 14 | "He stepped closer, the scent" | | 15 | "She saw the flicker of" | | 16 | "She didn't care." | | 17 | "Her eyes remained fixed on" | | 18 | "He was moving toward a" | | 19 | "She rounded a corner, her" |
| | ratio | 0.318 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 88 | | matches | | 0 | "Rain lashed against the pavement," | | 1 | "Detective Harlow Quinn tightened her" | | 2 | "The shout dissolved into the" | | 3 | "The suspect didn't flinch." | | 4 | "He bolted, a lithe figure" | | 5 | "Quinn lunged forward, her lungs" | | 6 | "She pushed past a group" | | 7 | "The chase surged toward a" | | 8 | "The man vaulted a chain-link" | | 9 | "Quinn scrambled after him, her" | | 10 | "She cleared the fence, her" | | 11 | "The alley dead-ended against a" | | 12 | "He pressed against a section" | | 13 | "Quinn skidded to a halt," | | 14 | "She scanned the brickwork, her" | | 15 | "The silence of the alley" | | 16 | "She stepped closer, her eyes" | | 17 | "A low hum vibrated through" | | 18 | "The air grew thick with" | | 19 | "A hairline fracture appeared in" |
| | ratio | 0.955 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 6 | | matches | | 0 | "It widened, revealing a stairwell that spiraled downward into a darkness far deeper than any London sewer." | | 1 | "The stairs felt endless, carved from stone that felt uncomfortably warm to the touch." | | 2 | "Beyond it, a cavernous space stretched out, illuminated by floating lanterns that cast dancing, amber shadows." | | 3 | "A merchant with skin the color of bruised plums held up a vial of shimmering, pearlescent liquid, his eyes glowing in the dim light." | | 4 | "Signs hung from rusted iron posts, written in scripts that made Quinn’s eyes ache if she stared too long." | | 5 | "She rounded a corner, her boots skidding on a patch of spilled, glowing blue liquid." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |