| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1007 | | 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) | |
| 10.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1007 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "fractured" | | 1 | "rhythmic" | | 2 | "vibrated" | | 3 | "silence" | | 4 | "pulsed" | | 5 | "weight" | | 6 | "chill" | | 7 | "warmth" | | 8 | "footsteps" | | 9 | "gloom" | | 10 | "scanning" | | 11 | "velvet" | | 12 | "raced" | | 13 | "quickened" |
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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 | 72 | | matches | (empty) | |
| 63.49% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 72 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1001 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 81.22% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 945 | | uniqueNames | 9 | | maxNameDensity | 1.38 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 13 | | London | 2 | | Underground | 1 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Underground" | | 3 | "Market" | | 4 | "Police" |
| | places | | | globalScore | 0.812 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 1 | | matches | | 0 | "silks that seemed to shift color with every breath hawked necklaces made of teeth and silver wire" |
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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 | 1001 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 34.52 | | std | 19.66 | | cv | 0.57 | | sampleLengths | | 0 | 63 | | 1 | 41 | | 2 | 40 | | 3 | 3 | | 4 | 55 | | 5 | 51 | | 6 | 32 | | 7 | 39 | | 8 | 15 | | 9 | 3 | | 10 | 57 | | 11 | 45 | | 12 | 10 | | 13 | 65 | | 14 | 30 | | 15 | 49 | | 16 | 55 | | 17 | 6 | | 18 | 53 | | 19 | 2 | | 20 | 23 | | 21 | 4 | | 22 | 44 | | 23 | 26 | | 24 | 50 | | 25 | 51 | | 26 | 43 | | 27 | 32 | | 28 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 72 | | matches | | |
| 66.67% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 150 | | matches | | 0 | "was nearing" | | 1 | "wasn't just pursuing" | | 2 | "was entering" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 2 | | flaggedSentences | 6 | | totalSentences | 78 | | ratio | 0.077 | | matches | | 0 | "Instead, he pulled a jagged, yellowed shard from his pocket—a piece of bone carved into a precise geometric shape." | | 1 | "The sound of the city—the distant sirens, the splashing tires, the hum of electricity—faded, replaced by a heavy, unnatural silence that pressed against her eardrums." | | 2 | "The stairs beneath her feet weren't concrete anymore; they were smooth, dark stone, worn down by centuries of footsteps that shouldn't exist in a modern subway system." | | 3 | "The voices drifted in fragments of languages Quinn didn't recognize—glottal stops and melodic trills that set her teeth on edge." | | 4 | "He paused to exchange a coin—a heavy, dark metal disk—with a merchant whose face was obscured by a heavy veil of lace." | | 5 | "This wasn't a crime scene; it was a breach of reality." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 957 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.01567398119122257 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003134796238244514 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 12.83 | | std | 6.1 | | cv | 0.476 | | sampleLengths | | 0 | 19 | | 1 | 10 | | 2 | 19 | | 3 | 15 | | 4 | 12 | | 5 | 12 | | 6 | 17 | | 7 | 3 | | 8 | 15 | | 9 | 10 | | 10 | 12 | | 11 | 3 | | 12 | 10 | | 13 | 5 | | 14 | 16 | | 15 | 11 | | 16 | 13 | | 17 | 15 | | 18 | 6 | | 19 | 19 | | 20 | 11 | | 21 | 11 | | 22 | 15 | | 23 | 6 | | 24 | 5 | | 25 | 9 | | 26 | 25 | | 27 | 5 | | 28 | 10 | | 29 | 3 | | 30 | 8 | | 31 | 22 | | 32 | 27 | | 33 | 13 | | 34 | 12 | | 35 | 20 | | 36 | 10 | | 37 | 7 | | 38 | 11 | | 39 | 24 | | 40 | 23 | | 41 | 10 | | 42 | 20 | | 43 | 12 | | 44 | 15 | | 45 | 22 | | 46 | 13 | | 47 | 24 | | 48 | 18 | | 49 | 6 |
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| 33.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.28205128205128205 | | totalSentences | 78 | | uniqueOpeners | 22 | |
| 92.59% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 72 | | matches | | 0 | "Instead, he pulled a jagged," | | 1 | "Then she looked at the" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 72 | | matches | | 0 | "Her salt-and-pepper hair, cropped close" | | 1 | "He moved with a frantic," | | 2 | "Her boots skidded on the" | | 3 | "She checked the worn leather" | | 4 | "He ducked into a narrow" | | 5 | "He didn't fumble with a" | | 6 | "He pressed the object against" | | 7 | "She pressed her back against" | | 8 | "She peered into the threshold." | | 9 | "She stepped inside." | | 10 | "He moved through the crowd" | | 11 | "He paused to exchange a" | | 12 | "She reached for her radio," | | 13 | "He wore a clean, white" | | 14 | "He held a tray of" | | 15 | "He was nearing a heavy" | | 16 | "She was entering a world" | | 17 | "He looked back over his" | | 18 | "He didn't stop, but his" | | 19 | "She tightened her grip on" |
| | ratio | 0.278 | |
| 15.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 72 | | matches | | 0 | "The rain hammered the Soho" | | 1 | "Each drop struck the asphalt" | | 2 | "Detective Harlow Quinn wiped a" | | 3 | "Her salt-and-pepper hair, cropped close" | | 4 | "He moved with a frantic," | | 5 | "The man’s dark coat whipped" | | 6 | "Quinn lunged forward." | | 7 | "Her boots skidded on the" | | 8 | "She checked the worn leather" | | 9 | "The seconds ticked away, indifferent" | | 10 | "The command died in the" | | 11 | "The suspect didn't look back." | | 12 | "He ducked into a narrow" | | 13 | "Quinn followed, her hand hovering" | | 14 | "The alley narrowed, the brick" | | 15 | "The man reached a heavy" | | 16 | "He didn't fumble with a" | | 17 | "He pressed the object against" | | 18 | "A low, subterranean thrum vibrated" | | 19 | "The iron door groaned, sliding" |
| | ratio | 0.889 | |
| 69.44% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 72 | | matches | | 0 | "If she went down there," |
| | ratio | 0.014 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 6 | | matches | | 0 | "The temperature climbed, turning from the biting London chill to a stagnant, humid warmth that smelled of clove, ozone, and dried blood." | | 1 | "The stairs beneath her feet weren't concrete anymore; they were smooth, dark stone, worn down by centuries of footsteps that shouldn't exist in a modern subway …" | | 2 | "The light didn't come from flickering fluorescent tubes but from floating lanterns that drifted through the air like bioluminescent jellyfish." | | 3 | "The voices drifted in fragments of languages Quinn didn't recognize—glottal stops and melodic trills that set her teeth on edge." | | 4 | "He wore a clean, white apron over a dark shirt, and his eyes held a warmth that felt entirely out of place in this tomb." | | 5 | "A merchant nearby began to chant, a low, guttural vibration that made the very air shimmer." |
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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 | |