| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 69.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 994 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | | 2 | | | 3 | | adverb | "reluctantly" | | count | 1 |
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| | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "suddenly" | | 3 | "reluctantly" |
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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) | |
| 49.70% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 994 | | totalAiIsms | 10 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | word | "down her spine" | | count | 1 |
| | 7 | | | 8 | |
| | highlights | | 0 | "calculated" | | 1 | "glistening" | | 2 | "familiar" | | 3 | "pulse" | | 4 | "navigate" | | 5 | "shimmered" | | 6 | "down her spine" | | 7 | "racing" | | 8 | "reminder" |
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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 | 2 | | narrationSentences | 68 | | matches | | 0 | "t in determination" | | 1 | "was nervous" |
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| 16.81% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 4 | | narrationSentences | 68 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "appeared to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | 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 | 985 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 749 | | uniqueNames | 11 | | maxNameDensity | 2 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 15 | | Herrera | 8 | | Saint | 1 | | Christopher | 1 | | Veil | 1 | | Market | 1 | | Tube | 2 | | Camden | 2 | | Morris | 5 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Market" | | 6 | "Morris" |
| | places | | | globalScore | 0.499 | | windowScore | 0.333 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 2 | | matches | | 0 | "talismans that seemed to pulse with energy" | | 1 | "knives that seemed to bend light around them" |
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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 | 985 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 24.02 | | std | 13.07 | | cv | 0.544 | | sampleLengths | | 0 | 50 | | 1 | 27 | | 2 | 37 | | 3 | 4 | | 4 | 29 | | 5 | 34 | | 6 | 8 | | 7 | 22 | | 8 | 25 | | 9 | 11 | | 10 | 32 | | 11 | 3 | | 12 | 32 | | 13 | 17 | | 14 | 17 | | 15 | 15 | | 16 | 44 | | 17 | 27 | | 18 | 39 | | 19 | 2 | | 20 | 12 | | 21 | 23 | | 22 | 5 | | 23 | 29 | | 24 | 20 | | 25 | 36 | | 26 | 35 | | 27 | 4 | | 28 | 27 | | 29 | 11 | | 30 | 19 | | 31 | 22 | | 32 | 21 | | 33 | 29 | | 34 | 42 | | 35 | 34 | | 36 | 16 | | 37 | 32 | | 38 | 35 | | 39 | 53 | | 40 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 68 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 132 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 83 | | ratio | 0.06 | | matches | | 0 | "The suspect—a man she'd been tracking for weeks—disappeared into an alleyway just ahead." | | 1 | "\"Coming, Detective? Or are you going to stand there chatting all night?\" The voice was familiar—the suspect." | | 2 | "The corridor led to another chamber, this one filled with cages containing creatures she couldn't identify—some with multiple eyes, others with wings that seemed too large for their bodies." | | 3 | "The suspect reached a dead end—a brick wall that appeared to have no exit." | | 4 | "The rain continued to fall above, a distant reminder of the world she knew, while before her lay the unknown—a truth she had spent three years pursuing." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 756 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.01984126984126984 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010582010582010581 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 11.87 | | std | 5.72 | | cv | 0.482 | | sampleLengths | | 0 | 19 | | 1 | 18 | | 2 | 13 | | 3 | 16 | | 4 | 4 | | 5 | 7 | | 6 | 15 | | 7 | 12 | | 8 | 4 | | 9 | 6 | | 10 | 4 | | 11 | 12 | | 12 | 17 | | 13 | 14 | | 14 | 13 | | 15 | 7 | | 16 | 5 | | 17 | 3 | | 18 | 7 | | 19 | 15 | | 20 | 25 | | 21 | 6 | | 22 | 5 | | 23 | 17 | | 24 | 15 | | 25 | 3 | | 26 | 13 | | 27 | 19 | | 28 | 8 | | 29 | 9 | | 30 | 17 | | 31 | 3 | | 32 | 12 | | 33 | 13 | | 34 | 9 | | 35 | 11 | | 36 | 11 | | 37 | 16 | | 38 | 11 | | 39 | 8 | | 40 | 14 | | 41 | 17 | | 42 | 2 | | 43 | 12 | | 44 | 16 | | 45 | 7 | | 46 | 5 | | 47 | 22 | | 48 | 7 | | 49 | 6 |
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| 66.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.43373493975903615 | | totalSentences | 83 | | uniqueOpeners | 36 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "Just a small indentation in" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 67 | | matches | | 0 | "She followed him into the" | | 1 | "It was slightly ajar, darkness" | | 2 | "She pushed the door open" | | 3 | "His hand instinctively went to" | | 4 | "He adjusted his Saint Christopher" | | 5 | "She pushed past Herrera and" | | 6 | "Her suspect moved through the" | | 7 | "She turned to find Herrera" | | 8 | "he whispered, his voice barely" | | 9 | "He gestured to the stalls" | | 10 | "Her suspect glanced back, spotting" | | 11 | "He broke into a run," | | 12 | "It was DS Morris, her" | | 13 | "he said, his voice unchanged" | | 14 | "He extended his hand" | | 15 | "Her decision would determine everything." |
| | ratio | 0.239 | |
| 27.16% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 67 | | matches | | 0 | "Rain lashed against the London" | | 1 | "Detective Harlow Quinn's boots splashed" | | 2 | "The suspect—a man she'd been" | | 3 | "Quinn's worn leather watch on" | | 4 | "The streets were empty except" | | 5 | "She followed him into the" | | 6 | "The alley dead-ended at a" | | 7 | "It was slightly ajar, darkness" | | 8 | "Quinn drew her weapon, her" | | 9 | "She pushed the door open" | | 10 | "The air grew colder as" | | 11 | "The stairs ended at another" | | 12 | "A bone token, she realized." | | 13 | "An entry requirement." | | 14 | "Tomás Herrera, his olive skin" | | 15 | "His hand instinctively went to" | | 16 | "Quinn lowered her weapon slightly" | | 17 | "He adjusted his Saint Christopher" | | 18 | "Herrera stepped closer" | | 19 | "The metal door suddenly creaked" |
| | ratio | 0.866 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 4 | | matches | | 0 | "She pushed the door open with her foot, revealing a set of concrete stairs descending into darkness." | | 1 | "Glowing vials, ancient books, talismans that seemed to pulse with energy." | | 2 | "The corridor led to another chamber, this one filled with cages containing creatures she couldn't identify—some with multiple eyes, others with wings that seeme…" | | 3 | "It was DS Morris, her former partner, who had died three years ago under unexplained circumstances." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "he whispered, his voice barely audible over the market's strange hum" | | 1 | "he said, his voice unchanged" | | 2 | "Quinn asked, her voice steady despite the turmoil inside her" |
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| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "he whispered (whisper)" | | 1 | "Quinn shouted (shout)" |
| | dialogueSentences | 28 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.5 | | effectiveRatio | 0.143 | |