| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.51 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 82.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1135 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "softly" | | 1 | "tightly" | | 2 | "really" | | 3 | "carefully" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 7.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1135 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "furrowed" | | 1 | "glistening" | | 2 | "scanning" | | 3 | "glint" | | 4 | "intricate" | | 5 | "quivered" | | 6 | "flicker" | | 7 | "raced" | | 8 | "racing" | | 9 | "sense of" | | 10 | "resolve" | | 11 | "pounding" | | 12 | "charged" | | 13 | "electric" | | 14 | "resonated" | | 15 | "pulse" | | 16 | "shimmered" | | 17 | "pulsed" |
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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 | 2 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 68 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 91 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1134 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 736 | | uniqueNames | 8 | | maxNameDensity | 3.4 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 25 | | Tube | 1 | | Camden | 1 | | Mark | 1 | | Thompson | 18 | | Eva | 1 | | Kowalski | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Mark" | | 3 | "Thompson" | | 4 | "Eva" | | 5 | "Kowalski" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0.167 | |
| 5.77% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 3 | | matches | | 0 | "as if expecting answers to materialize from the shadows" | | 1 | "sound that seemed to vibrate in her bones" | | 2 | "as if sensing the energy radiating from the rift" |
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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 | 1134 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 91 | | matches | (empty) | |
| 96.61% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 25.2 | | std | 12.3 | | cv | 0.488 | | sampleLengths | | 0 | 71 | | 1 | 42 | | 2 | 41 | | 3 | 21 | | 4 | 35 | | 5 | 18 | | 6 | 40 | | 7 | 12 | | 8 | 49 | | 9 | 8 | | 10 | 23 | | 11 | 19 | | 12 | 39 | | 13 | 29 | | 14 | 27 | | 15 | 21 | | 16 | 31 | | 17 | 24 | | 18 | 14 | | 19 | 33 | | 20 | 25 | | 21 | 37 | | 22 | 13 | | 23 | 34 | | 24 | 23 | | 25 | 31 | | 26 | 13 | | 27 | 22 | | 28 | 20 | | 29 | 29 | | 30 | 22 | | 31 | 29 | | 32 | 11 | | 33 | 21 | | 34 | 11 | | 35 | 33 | | 36 | 10 | | 37 | 9 | | 38 | 25 | | 39 | 10 | | 40 | 18 | | 41 | 19 | | 42 | 24 | | 43 | 11 | | 44 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 68 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 147 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 91 | | ratio | 0.011 | | matches | | 0 | "Detective Harlow Quinn stepped into the dimly lit chamber of the abandoned Tube station beneath Camden, the air thick with the scent of damp concrete and something else—something metallic." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 737 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.023066485753052916 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.012211668928086838 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 91 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 91 | | mean | 12.46 | | std | 6.86 | | cv | 0.551 | | sampleLengths | | 0 | 29 | | 1 | 9 | | 2 | 21 | | 3 | 12 | | 4 | 13 | | 5 | 18 | | 6 | 11 | | 7 | 17 | | 8 | 10 | | 9 | 14 | | 10 | 12 | | 11 | 9 | | 12 | 7 | | 13 | 19 | | 14 | 9 | | 15 | 9 | | 16 | 9 | | 17 | 15 | | 18 | 25 | | 19 | 12 | | 20 | 13 | | 21 | 19 | | 22 | 17 | | 23 | 8 | | 24 | 8 | | 25 | 15 | | 26 | 14 | | 27 | 5 | | 28 | 35 | | 29 | 4 | | 30 | 7 | | 31 | 19 | | 32 | 3 | | 33 | 13 | | 34 | 14 | | 35 | 21 | | 36 | 5 | | 37 | 26 | | 38 | 24 | | 39 | 9 | | 40 | 5 | | 41 | 22 | | 42 | 11 | | 43 | 19 | | 44 | 6 | | 45 | 10 | | 46 | 27 | | 47 | 13 | | 48 | 8 | | 49 | 26 |
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| 80.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4945054945054945 | | totalSentences | 91 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 68 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 68 | | matches | | 0 | "Her sharp jaw tightened as" | | 1 | "It was DS Mark Thompson," | | 2 | "She pointed to the victim’s" | | 3 | "She stepped closer, crouching down" | | 4 | "she replied, her voice low" | | 5 | "She gestured to the victim’s" | | 6 | "she murmured, flipping through the" | | 7 | "she said, her voice firm" | | 8 | "she instructed, her senses heightened" | | 9 | "They moved deeper into the" | | 10 | "she replied, her pulse quickening" | | 11 | "They pressed on, the hum" | | 12 | "She felt drawn to it," | | 13 | "she said, her gaze fixed" |
| | ratio | 0.206 | |
| 33.53% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 68 | | matches | | 0 | "Detective Harlow Quinn stepped into" | | 1 | "Her sharp jaw tightened as" | | 2 | "It was DS Mark Thompson," | | 3 | "Quinn approached, her worn leather" | | 4 | "The victim lay face down," | | 5 | "Blood pooled around him, glistening" | | 6 | "Quinn knelt beside the body," | | 7 | "Thompson said, glancing up at" | | 8 | "Quinn shook her head, her" | | 9 | "She pointed to the victim’s" | | 10 | "Thompson frowned, his gaze shifting" | | 11 | "Quinn stood, scanning the surroundings" | | 12 | "Thompson suggested, but his voice" | | 13 | "Quinn’s eyes caught a glint" | | 14 | "She stepped closer, crouching down" | | 15 | "The face bore intricate etchings" | | 16 | "Thompson asked, his curiosity piqued" | | 17 | "she replied, her voice low" | | 18 | "Thompson scoffed, but Quinn could" | | 19 | "She gestured to the victim’s" |
| | ratio | 0.853 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 68 | | matches | | 0 | "Now, it lay in ruins," | | 1 | "If anyone could make sense" |
| | ratio | 0.029 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "The air felt charged, electric, as if something lay just beyond the veil of reality." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 13 | | matches | | 0 | "Thompson suggested, but his voice lacked conviction" | | 1 | "Thompson asked, his curiosity piqued" | | 2 | "she replied, her voice low" | | 3 | "Thompson countered, but his tone lacked its earlier bravado" | | 4 | "she said, her voice firm" | | 5 | "Thompson replied, but his voice lacked conviction" | | 6 | "she instructed, her senses heightened" | | 7 | "Thompson whispered, his voice barely audible" | | 8 | "she replied, her pulse quickening" | | 9 | "Thompson’s voice trailed, awe mingling with fear" | | 10 | "Quinn breathed, her eyes wide" | | 11 | "Thompson urged, his voice tense" | | 12 | "Thompson shot back, his eyes darting between the rift and Quinn" |
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| 47.96% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 5 | | fancyTags | | 0 | "Thompson suggested (suggest)" | | 1 | "she murmured (murmur)" | | 2 | "Thompson whispered (whisper)" | | 3 | "Quinn breathed (breathe)" | | 4 | "Thompson urged (urge)" |
| | dialogueSentences | 49 | | tagDensity | 0.306 | | leniency | 0.612 | | rawRatio | 0.333 | | effectiveRatio | 0.204 | |