| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 3 | | adverbTags | | 0 | "He gestured around [around]" | | 1 | "Eva said breathlessly [breathlessly]" | | 2 | "she said firmly [firmly]" |
| | dialogueSentences | 34 | | tagDensity | 0.529 | | leniency | 1 | | rawRatio | 0.167 | | effectiveRatio | 0.167 | |
| 73.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1124 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "carefully" | | 1 | "gently" | | 2 | "really" | | 3 | "eagerly" |
| |
| 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) | |
| 42.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1124 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "glinting" | | 1 | "etched" | | 2 | "eyebrow" | | 3 | "tracing" | | 4 | "absolutely" | | 5 | "navigating" | | 6 | "furrowed" | | 7 | "firmly" | | 8 | "complex" | | 9 | "racing" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "couldn't help but" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "couldn't help but wonder" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 51 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1127 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 616 | | uniqueNames | 15 | | maxNameDensity | 3.25 | | worstName | "Harlow" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 2 | | Detective | 1 | | Harlow | 20 | | Quinn | 1 | | Alec | 2 | | Bellerose | 2 | | Liam | 6 | | Tate | 1 | | Veil | 1 | | Market | 1 | | Eva | 12 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Shades | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Alec" | | 3 | "Bellerose" | | 4 | "Liam" | | 5 | "Tate" | | 6 | "Market" | | 7 | "Eva" | | 8 | "Kowalski" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1127 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 80.82% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 37.57 | | std | 16.26 | | cv | 0.433 | | sampleLengths | | 0 | 49 | | 1 | 56 | | 2 | 30 | | 3 | 10 | | 4 | 55 | | 5 | 69 | | 6 | 50 | | 7 | 12 | | 8 | 31 | | 9 | 16 | | 10 | 42 | | 11 | 13 | | 12 | 49 | | 13 | 37 | | 14 | 50 | | 15 | 27 | | 16 | 34 | | 17 | 26 | | 18 | 40 | | 19 | 39 | | 20 | 41 | | 21 | 21 | | 22 | 22 | | 23 | 72 | | 24 | 19 | | 25 | 45 | | 26 | 46 | | 27 | 49 | | 28 | 22 | | 29 | 55 |
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| 91.50% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 51 | | matches | | 0 | "was said" | | 1 | "was connected" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 116 | | matches | | |
| 57.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 67 | | ratio | 0.03 | | matches | | 0 | "Harlow recognized the victim immediately - it was Alec Bellerose, a known associate of the supernatural clique she'd been investigating." | | 1 | "As she knelt down, she noticed something glinting in the dim light - a small brass compass, its face etched with strange symbols." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 615 | | adjectiveStacks | 2 | | stackExamples | | 0 | "legendary supernatural black market," | | 1 | "likely far more complex" |
| | adverbCount | 23 | | adverbRatio | 0.03739837398373984 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.01788617886178862 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 16.82 | | std | 9.73 | | cv | 0.579 | | sampleLengths | | 0 | 30 | | 1 | 19 | | 2 | 19 | | 3 | 20 | | 4 | 17 | | 5 | 10 | | 6 | 14 | | 7 | 6 | | 8 | 10 | | 9 | 4 | | 10 | 23 | | 11 | 28 | | 12 | 3 | | 13 | 21 | | 14 | 18 | | 15 | 27 | | 16 | 14 | | 17 | 23 | | 18 | 13 | | 19 | 12 | | 20 | 6 | | 21 | 25 | | 22 | 10 | | 23 | 6 | | 24 | 23 | | 25 | 19 | | 26 | 8 | | 27 | 5 | | 28 | 10 | | 29 | 39 | | 30 | 4 | | 31 | 12 | | 32 | 21 | | 33 | 9 | | 34 | 11 | | 35 | 30 | | 36 | 18 | | 37 | 9 | | 38 | 3 | | 39 | 31 | | 40 | 7 | | 41 | 19 | | 42 | 13 | | 43 | 27 | | 44 | 13 | | 45 | 26 | | 46 | 10 | | 47 | 31 | | 48 | 9 | | 49 | 12 |
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| 82.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4925373134328358 | | totalSentences | 67 | | uniqueOpeners | 33 | |
| 68.03% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 49 | | matches | | 0 | "Just then, a voice called" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 49 | | matches | | 0 | "Her boots crunched on the" | | 1 | "He gestured around the cavernous" | | 2 | "It was a place of" | | 3 | "she said, stepping closer to" | | 4 | "It was Eva Kowalski, the" | | 5 | "She glanced down at the" | | 6 | "she breathed, reaching out to" | | 7 | "he asked, his brow furrowed" | | 8 | "she said firmly" | | 9 | "he said, turning to relay" | | 10 | "She had a sinking feeling" | | 11 | "she said, turning to Liam" | | 12 | "she said, her brow furrowed" |
| | ratio | 0.265 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 49 | | matches | | 0 | "The gray predawn light was" | | 1 | "Her boots crunched on the" | | 2 | "The body lay crumpled in" | | 3 | "Harlow recognized the victim immediately" | | 4 | "The young man had been" | | 5 | "Harlow's partner, DS Liam Tate," | | 6 | "Harlow asked, her gaze fixed" | | 7 | "Liam shook his head." | | 8 | "He gestured around the cavernous" | | 9 | "Harlow nodded, unsurprised." | | 10 | "The Veil Market was a" | | 11 | "It was a place of" | | 12 | "she said, stepping closer to" | | 13 | "Liam asked, peering over her" | | 14 | "Harlow murmured, frowning" | | 15 | "Harlow looked up to see" | | 16 | "It was Eva Kowalski, the" | | 17 | "Harlow greeted her, rising to" | | 18 | "Eva said breathlessly, adjusting her" | | 19 | "Harlow arched an eyebrow." |
| | ratio | 0.857 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 49 | | matches | | 0 | "If the Shades were indeed" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 1 | | matches | | 0 | "It was Eva Kowalski, the research assistant from the British Museum who had been assisting Harlow with her investigation." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 3 | | matches | | 0 | "he asked, his brow furrowed" | | 1 | "Eva replied, her green eyes bright with excitement" | | 2 | "Eva explained, her voice hushed" |
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| 61.76% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 3 | | fancyTags | | 0 | "Harlow murmured (murmur)" | | 1 | "she breathed (breathe)" | | 2 | "Eva explained (explain)" |
| | dialogueSentences | 34 | | tagDensity | 0.441 | | leniency | 0.882 | | rawRatio | 0.2 | | effectiveRatio | 0.176 | |