| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 2 | | adverbTags | | 0 | "The crowd parted around [around]" | | 1 | "he said softly [softly]" |
| | dialogueSentences | 16 | | tagDensity | 0.438 | | leniency | 0.875 | | rawRatio | 0.286 | | effectiveRatio | 0.25 | |
| 91.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1180 | | 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) | |
| 57.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1180 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "scanned" | | 1 | "rhythmic" | | 2 | "stomach" | | 3 | "whisper" | | 4 | "velvet" | | 5 | "scanning" | | 6 | "calculating" | | 7 | "footsteps" | | 8 | "silence" |
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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 | 0 | | hedgeCount | 1 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | 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 | 1165 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 47.56% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1025 | | uniqueNames | 16 | | maxNameDensity | 2.05 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Morris | 2 | | Tuesday | 2 | | October | 1 | | Brewer | 1 | | Street | 1 | | Veil | 1 | | Market | 1 | | Glock | 2 | | Tube | 1 | | Camden | 1 | | Quinn | 21 | | Hackney | 1 | | Thames | 1 | | London | 1 |
| | persons | | 0 | "Morris" | | 1 | "Market" | | 2 | "Glock" | | 3 | "Quinn" |
| | places | | 0 | "Raven" | | 1 | "October" | | 2 | "Brewer" | | 3 | "Street" | | 4 | "Thames" | | 5 | "London" |
| | globalScore | 0.476 | | windowScore | 0.5 | |
| 85.06% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 2 | | matches | | 0 | "tasted like old pennies" | | 1 | "books that seemed to whisper" |
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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 | 1165 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 22.84 | | std | 15.16 | | cv | 0.664 | | sampleLengths | | 0 | 34 | | 1 | 11 | | 2 | 4 | | 3 | 51 | | 4 | 35 | | 5 | 1 | | 6 | 22 | | 7 | 30 | | 8 | 43 | | 9 | 6 | | 10 | 36 | | 11 | 39 | | 12 | 71 | | 13 | 34 | | 14 | 24 | | 15 | 25 | | 16 | 19 | | 17 | 12 | | 18 | 14 | | 19 | 15 | | 20 | 12 | | 21 | 44 | | 22 | 8 | | 23 | 40 | | 24 | 9 | | 25 | 19 | | 26 | 18 | | 27 | 15 | | 28 | 7 | | 29 | 21 | | 30 | 30 | | 31 | 33 | | 32 | 6 | | 33 | 12 | | 34 | 33 | | 35 | 2 | | 36 | 47 | | 37 | 11 | | 38 | 28 | | 39 | 10 | | 40 | 4 | | 41 | 39 | | 42 | 11 | | 43 | 7 | | 44 | 37 | | 45 | 23 | | 46 | 48 | | 47 | 10 | | 48 | 22 | | 49 | 22 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 198 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 108 | | ratio | 0.093 | | matches | | 0 | "Her target—tall, hooded, carrying a leather satchel—bolted east into the alley." | | 1 | "Then she spotted footprints—muddy, fresh—leading toward a rusted maintenance grate." | | 2 | "Flickering torches—actual torches—lined the walls, burning with flames that cast no smoke." | | 3 | "Stalls crammed the platform—some wooden, some wrought iron, all crowded with goods that made her stomach turn." | | 4 | "The crowd parted around her with suspicious glances—humans in trench coats, others with eyes that reflected her flashlight beam like cats'." | | 5 | "His face—pale, angular, with eyes that held too much white—widened in recognition, then hardened." | | 6 | "The curtain led into unknown territory—probably the kind of back rooms where people disappeared and turned up in the Thames three weeks later with their memories hollowed out." | | 7 | "The corridor twisted right, then left, then opened into a circular chamber with a domed ceiling painted in constellations that moved—actual movement, stars sliding across plaster like living things." | | 8 | "She rolled, came up with her Glock aimed, but he was already through the gate—down into the sewers, into darkness deeper than the market's." | | 9 | "Somewhere ahead, in the blackness, her suspect waited—or ran, or vanished into the labyrinth that ran beneath London like veins beneath skin." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 537 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.0186219739292365 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 10.79 | | std | 6.44 | | cv | 0.597 | | sampleLengths | | 0 | 13 | | 1 | 9 | | 2 | 12 | | 3 | 11 | | 4 | 4 | | 5 | 6 | | 6 | 26 | | 7 | 19 | | 8 | 15 | | 9 | 11 | | 10 | 9 | | 11 | 1 | | 12 | 11 | | 13 | 1 | | 14 | 10 | | 15 | 9 | | 16 | 9 | | 17 | 12 | | 18 | 6 | | 19 | 7 | | 20 | 2 | | 21 | 18 | | 22 | 10 | | 23 | 6 | | 24 | 4 | | 25 | 16 | | 26 | 8 | | 27 | 5 | | 28 | 3 | | 29 | 11 | | 30 | 12 | | 31 | 3 | | 32 | 13 | | 33 | 16 | | 34 | 17 | | 35 | 7 | | 36 | 15 | | 37 | 16 | | 38 | 13 | | 39 | 21 | | 40 | 8 | | 41 | 16 | | 42 | 7 | | 43 | 18 | | 44 | 5 | | 45 | 14 | | 46 | 9 | | 47 | 3 | | 48 | 2 | | 49 | 3 |
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| 55.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3611111111111111 | | totalSentences | 108 | | uniqueOpeners | 39 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 91 | | matches | | 0 | "Then she spotted footprints—muddy, fresh—leading" | | 1 | "Just her, her Glock, and" | | 2 | "Somewhere ahead, in the blackness," |
| | ratio | 0.033 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 91 | | matches | | 0 | "Her target—tall, hooded, carrying a" | | 1 | "Her lungs burned within thirty" | | 2 | "She pushed up, gun drawn," | | 3 | "She scanned the dark corners," | | 4 | "She glanced back at the" | | 5 | "She clicked her flashlight on," | | 6 | "Her shoes squelched." | | 7 | "She'd seen enough in this" | | 8 | "She moved through the central" | | 9 | "Her heart kicked." | | 10 | "She'd heard the entry requirements" | | 11 | "she said, her voice steady" | | 12 | "His face—pale, angular, with eyes" | | 13 | "His accent placed him north" | | 14 | "He laughed, high and brittle," | | 15 | "She glanced back at the" | | 16 | "They clicked against her shoulders" | | 17 | "She heard the man's footsteps" | | 18 | "He turned slowly, the crowbar" | | 19 | "His eyes scanned her face," |
| | ratio | 0.297 | |
| 36.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 91 | | matches | | 0 | "Quinn's boots hit the pavement" | | 1 | "Rain sheeted down her collar" | | 2 | "The green neon sign bled" | | 3 | "Her target—tall, hooded, carrying a" | | 4 | "Quinn sprinted after him." | | 5 | "Her lungs burned within thirty" | | 6 | "DS Morris had vanished on" | | 7 | "The hooded man cut left" | | 8 | "Quinn skidded on the slick" | | 9 | "She pushed up, gun drawn," | | 10 | "She scanned the dark corners," | | 11 | "Quinn holstered her weapon and" | | 12 | "The grate lifted with a" | | 13 | "A ladder disappeared into blackness" | | 14 | "She glanced back at the" | | 15 | "Rain blurred the neon into" | | 16 | "Quinn gripped the ladder and" | | 17 | "The darkness swallowed her." | | 18 | "She clicked her flashlight on," | | 19 | "The tunnel ran east, lined" |
| | ratio | 0.846 | |
| 54.95% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 91 | | matches | | | ratio | 0.011 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 11 | | matches | | 0 | "Eighteen years on the force taught her to pace herself, but three years of dead-end grief had carved an itch beneath her ribs that wouldn't quit." | | 1 | "She clicked her flashlight on, the beam cutting through damp air that tasted like old pennies." | | 2 | "Flickering torches—actual torches—lined the walls, burning with flames that cast no smoke." | | 3 | "Stalls crammed the platform—some wooden, some wrought iron, all crowded with goods that made her stomach turn." | | 4 | "Jars of bubbling green liquid sat beside stacks of leather-bound books that seemed to whisper." | | 5 | "His face—pale, angular, with eyes that held too much white—widened in recognition, then hardened." | | 6 | "The corridor beyond was narrow, lit by phosphorescent moss that glowed sickly green." | | 7 | "She heard the man's footsteps ahead, splashing through shallow water that pooled on the flagstones." | | 8 | "The corridor twisted right, then left, then opened into a circular chamber with a domed ceiling painted in constellations that moved—actual movement, stars slid…" | | 9 | "She stood at the edge, rain still dripping from her hair, her breath coming hard." | | 10 | "Somewhere ahead, in the blackness, her suspect waited—or ran, or vanished into the labyrinth that ran beneath London like veins beneath skin." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice steady despite the tremor in her hands" | | 1 | "He smiled, and his teeth were too sharp, filed to points" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |