| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 21 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.20% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1788 | | 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) | |
| 16.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1788 | | totalAiIsms | 30 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "pulse" | | 1 | "wavered" | | 2 | "pumping" | | 3 | "echoed" | | 4 | "thundered" | | 5 | "footsteps" | | 6 | "velvet" | | 7 | "depths" | | 8 | "weight" | | 9 | "flicked" | | 10 | "trembled" | | 11 | "vibrated" | | 12 | "mechanical" | | 13 | "steeled" | | 14 | "silk" | | 15 | "flickered" | | 16 | "shattered" | | 17 | "gloom" | | 18 | "pounding" | | 19 | "glint" | | 20 | "familiar" | | 21 | "raced" | | 22 | "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 | 1 | | narrationSentences | 254 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 254 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 266 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1765 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 1682 | | uniqueNames | 19 | | maxNameDensity | 0.89 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 15 | | Raven | 1 | | Nest | 1 | | Angel | 1 | | Road | 1 | | Tube | 1 | | Veil | 1 | | Market | 3 | | Cantabrigian | 1 | | Morris | 1 | | Two | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 1 | | Rainwater | 1 | | Ahead | 3 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Nest" | | 3 | "Market" | | 4 | "Cantabrigian" | | 5 | "Morris" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Tomás" | | 9 | "Rainwater" | | 10 | "One" |
| | places | | 0 | "Raven" | | 1 | "Angel" | | 2 | "Road" | | 3 | "Tube" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 137 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a serrated dagger" |
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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 | 1765 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 266 | | matches | (empty) | |
| 86.33% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 25.58 | | std | 11.57 | | cv | 0.452 | | sampleLengths | | 0 | 33 | | 1 | 17 | | 2 | 44 | | 3 | 26 | | 4 | 32 | | 5 | 32 | | 6 | 52 | | 7 | 37 | | 8 | 17 | | 9 | 49 | | 10 | 39 | | 11 | 40 | | 12 | 8 | | 13 | 14 | | 14 | 40 | | 15 | 33 | | 16 | 25 | | 17 | 56 | | 18 | 24 | | 19 | 33 | | 20 | 35 | | 21 | 29 | | 22 | 37 | | 23 | 3 | | 24 | 21 | | 25 | 21 | | 26 | 16 | | 27 | 16 | | 28 | 6 | | 29 | 37 | | 30 | 13 | | 31 | 30 | | 32 | 32 | | 33 | 8 | | 34 | 35 | | 35 | 15 | | 36 | 35 | | 37 | 29 | | 38 | 28 | | 39 | 35 | | 40 | 33 | | 41 | 29 | | 42 | 29 | | 43 | 37 | | 44 | 22 | | 45 | 26 | | 46 | 18 | | 47 | 9 | | 48 | 14 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 254 | | matches | | 0 | "was abandoned" | | 1 | "was pocked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 359 | | matches | | |
| 35.45% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 266 | | ratio | 0.038 | | matches | | 0 | "She’d heard whispers of this place—an underground marketplace that traded in enchantments and forbidden lore." | | 1 | "The crowd shifted—faces painted, cloaked, half-human, half-creature." | | 2 | "She recognized the accent—fellini students turned occultists." | | 3 | "One tumbled to the floor—skull-shaped, ridged with runes." | | 4 | "Memory of DS Morris surged—gone three years, swallowed by these corridors of myth and fear." | | 5 | "The token-holder’s mask shifted—feathers of black and ivory." | | 6 | "The token warmed under her palm—bone turning slick." | | 7 | "She caught the glint of a medallion at his throat—Saint Christopher, tarnished, familiar." | | 8 | "The world narrowed to two heartbeats—his hand in hers, their only exit." | | 9 | "She mouthed a silent vow—to survive." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1705 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.0187683284457478 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.005865102639296188 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 266 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 266 | | mean | 6.64 | | std | 3.63 | | cv | 0.547 | | sampleLengths | | 0 | 14 | | 1 | 7 | | 2 | 12 | | 3 | 6 | | 4 | 8 | | 5 | 3 | | 6 | 17 | | 7 | 5 | | 8 | 12 | | 9 | 6 | | 10 | 4 | | 11 | 15 | | 12 | 7 | | 13 | 4 | | 14 | 12 | | 15 | 9 | | 16 | 6 | | 17 | 5 | | 18 | 8 | | 19 | 13 | | 20 | 5 | | 21 | 6 | | 22 | 4 | | 23 | 6 | | 24 | 3 | | 25 | 2 | | 26 | 4 | | 27 | 11 | | 28 | 22 | | 29 | 4 | | 30 | 12 | | 31 | 12 | | 32 | 4 | | 33 | 5 | | 34 | 10 | | 35 | 2 | | 36 | 5 | | 37 | 9 | | 38 | 12 | | 39 | 5 | | 40 | 11 | | 41 | 12 | | 42 | 3 | | 43 | 15 | | 44 | 5 | | 45 | 4 | | 46 | 12 | | 47 | 4 | | 48 | 21 | | 49 | 7 |
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| 50.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.3383458646616541 | | totalSentences | 266 | | uniqueOpeners | 90 | |
| 42.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 233 | | matches | | 0 | "Then sprinted through a half-hidden" | | 1 | "Right to distant shouts." | | 2 | "Only the ladder and the" |
| | ratio | 0.013 | |
| 92.96% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 74 | | totalSentences | 233 | | matches | | 0 | "She tightened her leather-gloved grip" | | 1 | "She vaulted over a pile" | | 2 | "His silhouette wavered, legs pumping." | | 3 | "She noted the sign without" | | 4 | "He accelerated toward a grated" | | 5 | "Her watch slapped against her" | | 6 | "She landed on the tiled" | | 7 | "His boots clattered below." | | 8 | "Her voice echoed off the" | | 9 | "She broke into a trot." | | 10 | "Her pulse thundered." | | 11 | "She’d heard whispers of this" | | 12 | "She didn’t carry one." | | 13 | "She recognized the accent—fellini students" | | 14 | "She ducked beneath a low" | | 15 | "She paused, a heartbeat’s hesitation," | | 16 | "She couldn’t lose him here." | | 17 | "He yanked open a trapdoor" | | 18 | "It rang hollow." | | 19 | "She crouched, squinted." |
| | ratio | 0.318 | |
| 63.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 185 | | totalSentences | 233 | | matches | | 0 | "Rain spattered her collar as" | | 1 | "The alley’s sludge clung to" | | 2 | "Quinn’s pulse tapped against her" | | 3 | "She tightened her leather-gloved grip" | | 4 | "Every step counted." | | 5 | "She vaulted over a pile" | | 6 | "His silhouette wavered, legs pumping." | | 7 | "The neon glow from The" | | 8 | "She noted the sign without" | | 9 | "He accelerated toward a grated" | | 10 | "Followers of folklore whispered of" | | 11 | "Quinn leapt after him." | | 12 | "The metal grate bit into" | | 13 | "Water gushed from the opening," | | 14 | "The suspect vanished into shadow." | | 15 | "Quinn slid down three steps" | | 16 | "Her watch slapped against her" | | 17 | "Military precision kept her moving." | | 18 | "Rain roared through broken vents" | | 19 | "Halfway down, she hesitated." |
| | ratio | 0.794 | |
| 21.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 233 | | matches | | 0 | "Before she could answer, the" |
| | ratio | 0.004 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "She tapped, the leather strap squeaking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 21 | | tagDensity | 0.048 | | leniency | 0.095 | | rawRatio | 1 | | effectiveRatio | 0.095 | |