| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1635 | | totalAiIsmAdverbs | 1 | | 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) | |
| 44.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1635 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "fractured" | | 1 | "pulsed" | | 2 | "gloom" | | 3 | "mechanical" | | 4 | "rhythmic" | | 5 | "traced" | | 6 | "echoed" | | 7 | "warmth" | | 8 | "chill" | | 9 | "unreadable" | | 10 | "silence" | | 11 | "weight" | | 12 | "flickered" | | 13 | "familiar" |
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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 | 180 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 180 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 180 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1635 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 1 | | matches | | 0 | "I know the toll, Quinn said, her hand closing in her pocket around the bone token." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 59 | | wordCount | 1635 | | uniqueNames | 23 | | maxNameDensity | 0.67 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "You" | | discoveredNames | | Soho | 2 | | Quinn | 11 | | Metropolitan | 2 | | Police | 2 | | Raven | 1 | | Nest | 3 | | Tube | 1 | | Morris | 3 | | Shoreditch | 1 | | St | 1 | | Veil | 2 | | Market | 6 | | Camden | 2 | | Brick | 1 | | Lane | 1 | | Christopher | 1 | | Herrera | 1 | | Detective | 1 | | Tomás | 7 | | Seville | 1 | | London | 1 | | Harlow | 2 | | You | 6 |
| | persons | | 0 | "Quinn" | | 1 | "Police" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Market" | | 5 | "Christopher" | | 6 | "Herrera" | | 7 | "Tomás" | | 8 | "Harlow" | | 9 | "You" |
| | places | | 0 | "Soho" | | 1 | "Nest" | | 2 | "St" | | 3 | "Veil" | | 4 | "Brick" | | 5 | "Lane" | | 6 | "Seville" | | 7 | "London" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 107 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like copper and ozone" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.612 | | wordCount | 1635 | | matches | | 0 | "not yet peaked, but the Market was already preparing to shift, folding its geome" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 180 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 17 | | mean | 96.18 | | std | 55.2 | | cv | 0.574 | | sampleLengths | | 0 | 153 | | 1 | 148 | | 2 | 110 | | 3 | 141 | | 4 | 148 | | 5 | 150 | | 6 | 144 | | 7 | 34 | | 8 | 13 | | 9 | 36 | | 10 | 25 | | 11 | 22 | | 12 | 27 | | 13 | 118 | | 14 | 90 | | 15 | 106 | | 16 | 170 |
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| 95.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 180 | | matches | | 0 | "been handed" | | 1 | "was gone" | | 2 | "was woven" | | 3 | "is supposed" | | 4 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 285 | | matches | | 0 | "was hunting" | | 1 | "was waiting" | | 2 | "was already preparing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 180 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1647 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.019429265330904676 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.007285974499089253 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 180 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 180 | | mean | 9.08 | | std | 7.31 | | cv | 0.805 | | sampleLengths | | 0 | 27 | | 1 | 17 | | 2 | 22 | | 3 | 23 | | 4 | 3 | | 5 | 2 | | 6 | 26 | | 7 | 2 | | 8 | 7 | | 9 | 18 | | 10 | 6 | | 11 | 21 | | 12 | 10 | | 13 | 27 | | 14 | 3 | | 15 | 7 | | 16 | 14 | | 17 | 14 | | 18 | 14 | | 19 | 5 | | 20 | 30 | | 21 | 3 | | 22 | 13 | | 23 | 9 | | 24 | 4 | | 25 | 22 | | 26 | 1 | | 27 | 9 | | 28 | 10 | | 29 | 17 | | 30 | 7 | | 31 | 18 | | 32 | 9 | | 33 | 20 | | 34 | 9 | | 35 | 5 | | 36 | 4 | | 37 | 4 | | 38 | 1 | | 39 | 1 | | 40 | 1 | | 41 | 12 | | 42 | 4 | | 43 | 13 | | 44 | 7 | | 45 | 3 | | 46 | 3 | | 47 | 9 | | 48 | 3 | | 49 | 8 |
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| 45.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 25 | | diversityRatio | 0.35555555555555557 | | totalSentences | 180 | | uniqueOpeners | 64 | |
| 20.83% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 160 | | matches | | 0 | "Probably carrying a drop for" |
| | ratio | 0.006 | |
| 62.50% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 63 | | totalSentences | 160 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "She stood fifty-nine inches of" | | 2 | "She didn't run." | | 3 | "She had clocked him three" | | 4 | "He veered left, cutting through" | | 5 | "Her reinforced boots splashed through" | | 6 | "It served operators who preferred" | | 7 | "She carried a warrant that" | | 8 | "She was hunting." | | 9 | "He had vanished past the" | | 10 | "Her service flashlight beam cut" | | 11 | "She stepped forward, her boots" | | 12 | "Her breath hitched." | | 13 | "She had not expected to" | | 14 | "She traced the charcoal line" | | 15 | "She had woken up in" | | 16 | "They told her it was" | | 17 | "She knew better." | | 18 | "It tasted like this station." | | 19 | "She had spent every night" |
| | ratio | 0.394 | |
| 50.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 131 | | totalSentences | 160 | | matches | | 0 | "Harlow Quinn moved through it" | | 1 | "Her closely cropped salt-and-pepper hair" | | 2 | "She stood fifty-nine inches of" | | 3 | "She didn't run." | | 4 | "The suspect ahead moved like" | | 5 | "She had clocked him three" | | 6 | "Tonight, she would close the" | | 7 | "He veered left, cutting through" | | 8 | "Quinn adjusted her angle, clearing" | | 9 | "Her reinforced boots splashed through" | | 10 | "The Raven's Nest." | | 11 | "Silas's bar did not serve" | | 12 | "It served operators who preferred" | | 13 | "Quinn had shown her badge" | | 14 | "Both times, she had been" | | 15 | "Tonight, she carried no badge." | | 16 | "She carried a warrant that" | | 17 | "She was hunting." | | 18 | "The runner skidded into a" | | 19 | "Quinn followed, shoulders brushing damp" |
| | ratio | 0.819 | |
| 31.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 160 | | matches | | | ratio | 0.006 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 12 | | matches | | 0 | "Quinn adjusted her angle, clearing the corner without breaking stride." | | 1 | "It served operators who preferred their transactions buried beneath old maps and black-and-white photographs." | | 2 | "A skeletal turnstile stood rusted shut, tangled with security chains and warnings that had faded to grey." | | 3 | "She had spent every night since chasing whispers, following money trails that dissolved into cash couriers, tracking men who vanished into places that did not a…" | | 4 | "An underground bazaar that traded in banned alchemical substances, enchanted goods, and information that could unmake careers." | | 5 | "He provided off-the-books medical care for the clique, stitching up flesh that refused to stay dead and treating wounds that should not require human hands." | | 6 | "Tomás tilted his head, studying her rigid stance, the cropped hair plastered to her temple, the worn leather watch on her left wrist catching the dim light." | | 7 | "She had spent three years piecing together the silence, tracking the fringe, following the threads that pointed to Soho, to the Nest, to men like Tomás who heal…" | | 8 | "The hum deepened, vibrating in her molars, rattling the glass vials in her chest cavity." | | 9 | "Tomás stepped back into the shadows, his shape dissolving against the peeling posters, his presence retreating into the quiet hum of the deeper tunnels." | | 10 | "The full moon had not yet peaked, but the Market was already preparing to shift, folding its geometry, bracing for its monthly migration." | | 11 | "She adjusted her grip on her service piece, felt the familiar weight of it, the reassuring promise of force that meant nothing here." |
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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 | |