| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 489 | | 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) | |
| 7.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 489 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "gleaming" | | 1 | "flickered" | | 2 | "standard" | | 3 | "echoed" | | 4 | "mechanical" | | 5 | "intricate" | | 6 | "pulsed" |
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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 | 45 | | matches | (empty) | |
| 15.87% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 45 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 45 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 481 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 76.78% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 478 | | uniqueNames | 10 | | maxNameDensity | 1.46 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 7 | | Raven | 1 | | Nest | 1 | | Silas | 1 | | Morris | 2 | | London | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Silas" | | 3 | "Morris" |
| | places | | | globalScore | 0.768 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 33 | | glossingSentenceCount | 4 | | matches | | 0 | "seemed impossibly large for its subterranean location" | | 1 | "devices that seemed to move without human interaction, carved tokens that pulsed with an inner light" | | 2 | "looked like preserved human hearts in gla" | | 3 | "looked like living smoke for a bone token" |
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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 | 481 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 45 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 32.07 | | std | 19.37 | | cv | 0.604 | | sampleLengths | | 0 | 39 | | 1 | 41 | | 2 | 50 | | 3 | 15 | | 4 | 5 | | 5 | 49 | | 6 | 25 | | 7 | 41 | | 8 | 45 | | 9 | 61 | | 10 | 15 | | 11 | 62 | | 12 | 23 | | 13 | 5 | | 14 | 5 |
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| 81.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 45 | | matches | | 0 | "was stretched" | | 1 | "being obeyed" | | 2 | "was plastered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 86 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 45 | | ratio | 0.111 | | matches | | 0 | "Her target—a wiry figure in a dark windbreaker—darted between parked cars and delivery trucks." | | 1 | "Quinn recognized the bar—she'd interviewed the owner, Silas, during previous investigations." | | 2 | "Her leather watch—a gift from her late partner Morris—was water-spotted but still keeping precise time." | | 3 | "Her instincts—honed by years of investigating cases that brushed against inexplicable boundaries—urged immediate pursuit." | | 4 | "The ambient sounds changed—from street noise to something more enclosed, more alien." |
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| 99.50% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 493 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.04056795131845842 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.012170385395537525 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 45 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 45 | | mean | 10.69 | | std | 6.25 | | cv | 0.585 | | sampleLengths | | 0 | 19 | | 1 | 20 | | 2 | 14 | | 3 | 10 | | 4 | 17 | | 5 | 12 | | 6 | 14 | | 7 | 11 | | 8 | 13 | | 9 | 15 | | 10 | 5 | | 11 | 14 | | 12 | 15 | | 13 | 11 | | 14 | 9 | | 15 | 14 | | 16 | 5 | | 17 | 6 | | 18 | 21 | | 19 | 2 | | 20 | 4 | | 21 | 14 | | 22 | 15 | | 23 | 7 | | 24 | 12 | | 25 | 2 | | 26 | 3 | | 27 | 6 | | 28 | 17 | | 29 | 14 | | 30 | 30 | | 31 | 3 | | 32 | 8 | | 33 | 4 | | 34 | 12 | | 35 | 17 | | 36 | 15 | | 37 | 18 | | 38 | 8 | | 39 | 8 | | 40 | 7 | | 41 | 3 | | 42 | 1 | | 43 | 1 | | 44 | 5 |
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| 94.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5777777777777777 | | totalSentences | 45 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 41 | | matches | | 0 | "Her target—a wiry figure in" | | 1 | "Its distinctive green neon sign" | | 2 | "Her command carried the practiced" | | 3 | "Her leather watch—a gift from" | | 4 | "Her instincts—honed by years of" | | 5 | "She'd heard rumors, dismissed them" | | 6 | "Her suspect was visible fifty" | | 7 | "Her watch ticked." | | 8 | "She took another step forward." |
| | ratio | 0.22 | |
| 57.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 33 | | totalSentences | 41 | | matches | | 0 | "The rain slashed diagonal against" | | 1 | "Detective Harlow Quinn's boots struck" | | 2 | "Her target—a wiry figure in" | | 3 | "Quinn's hand instinctively brushed her" | | 4 | "The suspect cut left, diving" | | 5 | "Its distinctive green neon sign" | | 6 | "Quinn recognized the bar—she'd interviewed" | | 7 | "Something about this neighborhood always" | | 8 | "Her command carried the practiced" | | 9 | "The figure didn't break stride." | | 10 | "Quinn's salt-and-pepper hair was plastered" | | 11 | "Her leather watch—a gift from" | | 12 | "Circumstances that hinted at something" | | 13 | "The suspect's movements were too" | | 14 | "Each motion suggested training, precision." | | 15 | "Something underneath this chase felt" | | 16 | "Protocol suggested calling backup." | | 17 | "Her instincts—honed by years of" | | 18 | "The staircase descended into darkness," | | 19 | "Quinn drew her weapon, checking" |
| | ratio | 0.805 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 5 | | matches | | 0 | "Her instincts—honed by years of investigating cases that brushed against inexplicable boundaries—urged immediate pursuit." | | 1 | "The staircase descended into darkness, each metal step producing a hollow ring that echoed strangely." | | 2 | "Vendor stalls lined a cavernous space that seemed impossibly large for its subterranean location." | | 3 | "Merchants sold objects that defied rational explanation: bottled liquids that shifted color, intricate mechanical devices that seemed to move without human inte…" | | 4 | "A bent figure with too many fingers exchanged something that looked like living smoke for a bone token." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |