| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.52% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 954 | | totalAiIsmAdverbs | 2 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 954 | | totalAiIsms | 22 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "scanned" | | 3 | "quickened" | | 4 | "raced" | | 5 | "calculating" | | 6 | "charged" | | 7 | "scanning" | | 8 | "cacophony" | | 9 | "could feel" | | 10 | "weight" | | 11 | "unwavering" | | 12 | "unravel" | | 13 | "unreadable" | | 14 | "resolve" | | 15 | "anticipation" |
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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 | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "The air was thick with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 74 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 76 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 952 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 53.43% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 932 | | uniqueNames | 6 | | maxNameDensity | 1.93 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 18 | | Tube | 1 | | Veil | 2 | | Market | 2 |
| | persons | | | places | | | globalScore | 0.534 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | 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 | 952 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 57.60% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 43.27 | | std | 15.21 | | cv | 0.352 | | sampleLengths | | 0 | 59 | | 1 | 62 | | 2 | 50 | | 3 | 51 | | 4 | 61 | | 5 | 53 | | 6 | 55 | | 7 | 50 | | 8 | 56 | | 9 | 43 | | 10 | 53 | | 11 | 19 | | 12 | 26 | | 13 | 10 | | 14 | 37 | | 15 | 56 | | 16 | 48 | | 17 | 39 | | 18 | 31 | | 19 | 10 | | 20 | 46 | | 21 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 74 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 139 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 76 | | ratio | 0.013 | | matches | | 0 | "He glanced back, his expression one of surprise and something else—fear." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 934 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.022483940042826552 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0053533190578158455 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 76 | | echoCount | 0 | | echoWords | (empty) | |
| 96.99% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 76 | | mean | 12.53 | | std | 4.92 | | cv | 0.392 | | sampleLengths | | 0 | 18 | | 1 | 13 | | 2 | 14 | | 3 | 12 | | 4 | 2 | | 5 | 15 | | 6 | 3 | | 7 | 19 | | 8 | 25 | | 9 | 12 | | 10 | 15 | | 11 | 13 | | 12 | 10 | | 13 | 15 | | 14 | 24 | | 15 | 12 | | 16 | 13 | | 17 | 18 | | 18 | 9 | | 19 | 11 | | 20 | 10 | | 21 | 11 | | 22 | 15 | | 23 | 14 | | 24 | 13 | | 25 | 18 | | 26 | 23 | | 27 | 14 | | 28 | 19 | | 29 | 6 | | 30 | 18 | | 31 | 7 | | 32 | 19 | | 33 | 11 | | 34 | 15 | | 35 | 11 | | 36 | 11 | | 37 | 11 | | 38 | 6 | | 39 | 15 | | 40 | 13 | | 41 | 9 | | 42 | 15 | | 43 | 16 | | 44 | 6 | | 45 | 13 | | 46 | 12 | | 47 | 14 | | 48 | 7 | | 49 | 3 |
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| 39.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.25 | | totalSentences | 76 | | uniqueOpeners | 19 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 77.53% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 73 | | matches | | 0 | "Her eyes, sharp and unyielding," | | 1 | "She pushed through the mass" | | 2 | "She could hear the suspect's" | | 3 | "Her mind raced, calculating the" | | 4 | "She dodged a taxi, her" | | 5 | "She knew of the place," | | 6 | "She took a breath, the" | | 7 | "She moved cautiously, her eyes" | | 8 | "She caught a glimpse of" | | 9 | "She followed, her movements fluid" | | 10 | "She could feel the weight" | | 11 | "She rounded a corner, the" | | 12 | "He glanced back, his expression" | | 13 | "she said, her voice steady," | | 14 | "he warned, his voice edged" | | 15 | "He held it up, a" | | 16 | "It was a key, a" | | 17 | "She weighed her options, the" | | 18 | "She couldn't turn back now," | | 19 | "She nodded, a silent agreement," |
| | ratio | 0.356 | |
| 7.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 73 | | matches | | 0 | "Detective Harlow Quinn moved with" | | 1 | "Her eyes, sharp and unyielding," | | 2 | "The suspect had slipped through" | | 3 | "Quinn's heart quickened." | | 4 | "She pushed through the mass" | | 5 | "The suspect, a man in" | | 6 | "Quinn followed, her breath steady" | | 7 | "The alley was a labyrinth" | | 8 | "She could hear the suspect's" | | 9 | "Her mind raced, calculating the" | | 10 | "The alley opened onto a" | | 11 | "Quinn hesitated for a fraction" | | 12 | "She dodged a taxi, her" | | 13 | "The chase led them deeper" | | 14 | "The suspect veered suddenly, disappearing" | | 15 | "Quinn hesitated at the top," | | 16 | "She knew of the place," | | 17 | "The Veil Market, a hidden" | | 18 | "She took a breath, the" | | 19 | "The steps were slick, the" |
| | ratio | 0.904 | |
| 68.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 73 | | matches | | | ratio | 0.014 | |
| 48.52% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 7 | | matches | | 0 | "She could hear the suspect's footsteps, a rapid staccato that matched her own." | | 1 | "The steps were slick, the dim light casting long shadows that danced along the walls." | | 2 | "The Veil Market sprawled before her, a maze of stalls and vendors, each offering wares that defied explanation." | | 3 | "The air was thick with the scent of incense and something metallic, the atmosphere charged with an energy that prickled at her skin." | | 4 | "The suspect hesitated, his gaze flicking to the shadows that surrounded them." | | 5 | "But the suspect was her link, her chance to unravel the threads of a case that had haunted her for years." | | 6 | "The door creaked open, revealing a staircase that descended into darkness." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice steady, the authority in her tone unmistakable" | | 1 | "he said, his voice low, the warning clear" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0.333 | | effectiveRatio | 0.333 | |