| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 85.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1011 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "sharply" | | 1 | "slightly" | | 2 | "cautiously" |
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| 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) | |
| 45.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1011 | | totalAiIsms | 11 | | found | | 0 | | | 1 | | | 2 | | word | "practiced ease" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | |
| | highlights | | 0 | "beacon" | | 1 | "gleaming" | | 2 | "practiced ease" | | 3 | "oppressive" | | 4 | "rhythmic" | | 5 | "flicker" | | 6 | "maw" | | 7 | "etched" | | 8 | "pulsed" | | 9 | "intricate" | | 10 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 73 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 73 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | 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 | 2 | | markdownWords | 6 | | totalWords | 1012 | | ratio | 0.006 | | matches | | 0 | "The Raven’s Nest" | | 1 | "The Raven’s Nest" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.65% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1012 | | uniqueNames | 23 | | maxNameDensity | 1.09 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Great | 1 | | Windmill | 1 | | Street | 3 | | Raven | 2 | | Quinn | 11 | | Soho | 2 | | Herrera | 1 | | London | 1 | | Saint | 2 | | Christopher | 2 | | Rupert | 1 | | Greek | 1 | | Morris | 4 | | Charing | 1 | | Cross | 1 | | Road | 2 | | Tottenham | 1 | | Court | 1 | | Camden | 2 | | Veil | 2 | | Market | 2 | | Glock | 2 | | Tomás | 9 |
| | persons | | 0 | "Raven" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" | | 6 | "Tomás" |
| | places | | 0 | "Windmill" | | 1 | "Street" | | 2 | "Soho" | | 3 | "London" | | 4 | "Rupert" | | 5 | "Greek" | | 6 | "Charing" | | 7 | "Cross" | | 8 | "Road" | | 9 | "Tottenham" | | 10 | "Court" | | 11 | "Camden" | | 12 | "Market" | | 13 | "Glock" |
| | globalScore | 0.957 | | windowScore | 1 | |
| 25.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 3 | | matches | | 0 | "something close to recognition" | | 1 | "carvings that seemed to shift and writhe in the dim light" | | 2 | "looked like shadows given form, creatures" |
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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 | 1012 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 73 | | matches | (empty) | |
| 61.97% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 19 | | mean | 53.26 | | std | 19.54 | | cv | 0.367 | | sampleLengths | | 0 | 74 | | 1 | 56 | | 2 | 78 | | 3 | 87 | | 4 | 58 | | 5 | 46 | | 6 | 55 | | 7 | 52 | | 8 | 37 | | 9 | 58 | | 10 | 46 | | 11 | 52 | | 12 | 53 | | 13 | 8 | | 14 | 74 | | 15 | 14 | | 16 | 45 | | 17 | 75 | | 18 | 44 |
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| 86.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 73 | | matches | | 0 | "were connected" | | 1 | "was obscured" | | 2 | "being screamed" | | 3 | "was equipped" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 153 | | matches | | 0 | "was going" | | 1 | "was heading" | | 2 | "were overflowing" | | 3 | "was making" | | 4 | "was doing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 73 | | ratio | 0.014 | | matches | | 0 | "Quinn hesitated at the edge of the opening, the noise of the market washing over her – a low hum of chatter, the clink of strange coins, the occasional unearthly cry." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1015 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faint, greenish light pulsed" |
| | adverbCount | 25 | | adverbRatio | 0.024630541871921183 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01083743842364532 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 13.86 | | std | 7.64 | | cv | 0.551 | | sampleLengths | | 0 | 20 | | 1 | 14 | | 2 | 24 | | 3 | 11 | | 4 | 5 | | 5 | 22 | | 6 | 20 | | 7 | 14 | | 8 | 20 | | 9 | 24 | | 10 | 24 | | 11 | 10 | | 12 | 29 | | 13 | 25 | | 14 | 15 | | 15 | 15 | | 16 | 3 | | 17 | 20 | | 18 | 9 | | 19 | 11 | | 20 | 13 | | 21 | 5 | | 22 | 17 | | 23 | 16 | | 24 | 13 | | 25 | 9 | | 26 | 6 | | 27 | 1 | | 28 | 3 | | 29 | 25 | | 30 | 9 | | 31 | 2 | | 32 | 12 | | 33 | 12 | | 34 | 19 | | 35 | 5 | | 36 | 2 | | 37 | 2 | | 38 | 12 | | 39 | 13 | | 40 | 12 | | 41 | 8 | | 42 | 14 | | 43 | 13 | | 44 | 19 | | 45 | 4 | | 46 | 11 | | 47 | 14 | | 48 | 11 | | 49 | 10 |
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| 47.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3424657534246575 | | totalSentences | 73 | | uniqueOpeners | 25 | |
| 49.02% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 68 | | matches | | 0 | "Too late for anything good." |
| | ratio | 0.015 | |
| 78.82% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 68 | | matches | | 0 | "She pushed a damp strand" | | 1 | "Her worn leather watch on" | | 2 | "She’d been watching *The Raven’s" | | 3 | "He moved with a practiced" | | 4 | "He was going somewhere in" | | 5 | "He cut down Rupert Street," | | 6 | "She’d lost Morris, lost him" | | 7 | "She knew it." | | 8 | "He sped up, a renewed" | | 9 | "He must have known she" | | 10 | "She accelerated, closing the distance." | | 11 | "They burst out onto Charing" | | 12 | "He was heading for Tottenham" | | 13 | "She'd been hearing rumors, whispers" | | 14 | "She’d never had concrete proof," | | 15 | "She had to know." | | 16 | "She descended the steps, one" | | 17 | "She moved cautiously, her hand" | | 18 | "Her military bearing, honed over" | | 19 | "It was a market, but" |
| | ratio | 0.353 | |
| 18.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 68 | | matches | | 0 | "The downpour had turned Great" | | 1 | "Harlow Quinn squinted, the rain" | | 2 | "She pushed a damp strand" | | 3 | "Her worn leather watch on" | | 4 | "She’d been watching *The Raven’s" | | 5 | "Tomás Herrera had slipped out" | | 6 | "Quinn took off after him," | | 7 | "Tomás was quick, his short" | | 8 | "He moved with a practiced" | | 9 | "Quinn kept pace, her gaze" | | 10 | "He was going somewhere in" | | 11 | "He cut down Rupert Street," | | 12 | "Quinn’s breath hitched, a stitch" | | 13 | "She’d lost Morris, lost him" | | 14 | "This clique, these people hovering" | | 15 | "She knew it." | | 16 | "Tomás glanced over his shoulder," | | 17 | "He sped up, a renewed" | | 18 | "He must have known she" | | 19 | "The realization tightened Quinn’s jaw," |
| | ratio | 0.882 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 85.71% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 4 | | matches | | 0 | "Quinn kept pace, her gaze locked on the Saint Christopher medallion that bounced against his back, a small, silver target in the oppressive night." | | 1 | "She'd been hearing rumors, whispers among informants about a black market that moved with the full moon, a place hidden, selling things that shouldn't exist." | | 2 | "Stalls fashioned from salvaged materials were overflowing with strange, glowing objects, vials of shimmering liquids, and intricate carvings that seemed to shif…" | | 3 | "She saw things that looked like shadows given form, creatures with too many limbs, and others whose eyes glowed with an unsettling inner light." |
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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 | |