| 78.79% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 42 | | adverbTagCount | 6 | | adverbTags | | 0 | "Quinn repeated flatly [flatly]" | | 1 | "Eva said quickly [quickly]" | | 2 | "she said finally [finally]" | | 3 | "Eva swallowed hard [hard]" | | 4 | "Quinn said carefully [carefully]" | | 5 | "Quinn said simply [simply]" |
| | dialogueSentences | 99 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0.143 | | effectiveRatio | 0.121 | |
| 70.87% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1888 | | totalAiIsmAdverbs | 11 | | found | | | highlights | | 0 | "suddenly" | | 1 | "very" | | 2 | "quickly" | | 3 | "precisely" | | 4 | "carefully" | | 5 | "nervously" |
| |
| 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) | |
| 78.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1888 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "synthetic" | | 1 | "etched" | | 2 | "eyebrow" | | 3 | "could feel" | | 4 | "raced" | | 5 | "intricate" | | 6 | "ensure" | | 7 | "flicked" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | 0 | "blood ran cold" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 102 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 157 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1895 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 86 | | wordCount | 948 | | uniqueNames | 15 | | maxNameDensity | 3.69 | | worstName | "Quinn" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 35 | | Rorschach | 1 | | Tube | 2 | | Camden | 1 | | Town | 1 | | Peters | 4 | | Michaels | 7 | | Young | 1 | | British | 1 | | Museum | 1 | | Eva | 22 | | Morris | 7 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Peters" | | 3 | "Michaels" | | 4 | "Eva" | | 5 | "Morris" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | 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 | 1895 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 157 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 23.11 | | std | 13.46 | | cv | 0.582 | | sampleLengths | | 0 | 43 | | 1 | 17 | | 2 | 42 | | 3 | 24 | | 4 | 6 | | 5 | 29 | | 6 | 35 | | 7 | 20 | | 8 | 23 | | 9 | 16 | | 10 | 5 | | 11 | 46 | | 12 | 9 | | 13 | 11 | | 14 | 37 | | 15 | 10 | | 16 | 10 | | 17 | 33 | | 18 | 22 | | 19 | 35 | | 20 | 19 | | 21 | 35 | | 22 | 11 | | 23 | 18 | | 24 | 8 | | 25 | 12 | | 26 | 30 | | 27 | 6 | | 28 | 39 | | 29 | 33 | | 30 | 20 | | 31 | 68 | | 32 | 40 | | 33 | 5 | | 34 | 16 | | 35 | 26 | | 36 | 23 | | 37 | 22 | | 38 | 10 | | 39 | 11 | | 40 | 25 | | 41 | 16 | | 42 | 29 | | 43 | 10 | | 44 | 39 | | 45 | 22 | | 46 | 18 | | 47 | 51 | | 48 | 2 | | 49 | 41 |
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| 88.06% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 102 | | matches | | 0 | "been torn" | | 1 | "been sealed" | | 2 | "was etched" | | 3 | "been briefed" | | 4 | "been torn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 183 | | matches | | 0 | "were, standing" | | 1 | "was crossing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 157 | | ratio | 0.051 | | matches | | 0 | "The victim – male, mid-thirties, expensive watch still on his wrist – lay splayed like a broken marionette." | | 1 | "The abandoned station's entrance had been sealed off for years – officially, at least." | | 2 | "Quinn could feel the mood shifting toward amusement – the kind that would turn this into station gossip by morning." | | 3 | "Three years ago, her former partner Morris had used that exact term – \"shade attack\" – the night before he disappeared during that warehouse case." | | 4 | "\"The Veil Market is neutral ground for supernatural exchange. Strictly regulated, despite being technically illegal by human standards. Violence is forbidden. This—\" she gestured to the body, \"—is a major breach of Market law. And the fact that you found this place at all means something's very wrong.\"" | | 5 | "And now that she looked closer, the victim's clothing showed odd symbols embroidered into the lining – visible only where his jacket had been torn." | | 6 | "Peters pulled back the victim's collar to reveal a small tattoo – an intricate design that looked almost like a key." | | 7 | "But the alternative – living with unanswered questions – had become unbearable three years ago." |
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| 95.26% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 973 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.03802672147995889 | | lyAdverbCount | 25 | | lyAdverbRatio | 0.025693730729701953 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 157 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 157 | | mean | 12.07 | | std | 8.27 | | cv | 0.685 | | sampleLengths | | 0 | 20 | | 1 | 20 | | 2 | 3 | | 3 | 13 | | 4 | 4 | | 5 | 12 | | 6 | 18 | | 7 | 12 | | 8 | 16 | | 9 | 8 | | 10 | 3 | | 11 | 3 | | 12 | 19 | | 13 | 10 | | 14 | 14 | | 15 | 21 | | 16 | 9 | | 17 | 5 | | 18 | 6 | | 19 | 4 | | 20 | 19 | | 21 | 7 | | 22 | 9 | | 23 | 5 | | 24 | 10 | | 25 | 25 | | 26 | 11 | | 27 | 9 | | 28 | 5 | | 29 | 6 | | 30 | 17 | | 31 | 7 | | 32 | 13 | | 33 | 10 | | 34 | 10 | | 35 | 12 | | 36 | 17 | | 37 | 4 | | 38 | 10 | | 39 | 12 | | 40 | 21 | | 41 | 14 | | 42 | 12 | | 43 | 7 | | 44 | 16 | | 45 | 19 | | 46 | 6 | | 47 | 5 | | 48 | 9 | | 49 | 9 |
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| 66.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.43312101910828027 | | totalSentences | 157 | | uniqueOpeners | 68 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 90 | | matches | | 0 | "His throat had been torn" | | 1 | "Her focus remained on the" | | 2 | "She knelt beside a different" | | 3 | "she ordered, handing it to" | | 4 | "She clutched a worn leather" | | 5 | "She turned to Michaels" | | 6 | "She'd assumed it was case-related" | | 7 | "she said finally" | | 8 | "she gestured to the body," | | 9 | "She'd never told anyone it" | | 10 | "She turned to Michaels" | | 11 | "She might do the same." |
| | ratio | 0.133 | |
| 37.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 90 | | matches | | 0 | "Blood stained the frost-rimed concrete" | | 1 | "The abandoned Tube station beneath" | | 2 | "the forensic examiner said, gesturing" | | 3 | "Quinn crouched beside the corpse," | | 4 | "The victim – male, mid-thirties," | | 5 | "His throat had been torn" | | 6 | "Quinn tilted her head, studying" | | 7 | "Peters shifted uncomfortably." | | 8 | "Quinn stood, her knees protesting" | | 9 | "The abandoned station's entrance had" | | 10 | "Quinn barely acknowledged him." | | 11 | "Her focus remained on the" | | 12 | "Quinn stood and walked the" | | 13 | "The forensic team had set" | | 14 | "She knelt beside a different" | | 15 | "Something glinted in the crack" | | 16 | "she ordered, handing it to" | | 17 | "Michaels asked, trying to get" | | 18 | "Quinn said, though she'd never" | | 19 | "The face was etched with" |
| | ratio | 0.844 | |
| 55.56% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 90 | | matches | | | ratio | 0.011 | |
| 15.31% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 5 | | matches | | 0 | "Blood stained the frost-rimed concrete in an abstract pattern that reminded Detective Harlow Quinn of a Rorschach test gone wrong." | | 1 | "Yet here they were, standing on a platform that shouldn't exist on any modern Tube map, with a very fresh corpse." | | 2 | "Her focus remained on the body, on the pattern of blood splatter that followed no natural trajectory she recognized." | | 3 | "The forensic team had set up harsh spotlights that cast everything in clinical white, but the darkness beyond seemed to swallow the light unnaturally quickly." | | 4 | "As they ascended the stairs, leaving the crime scene behind, Quinn couldn't shake the feeling that she was crossing a threshold that went beyond the physical." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 42 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn stood, her knees protesting after eighteen years of crouching over bodies" | | 1 | "Michaels asked, trying to get a look" | | 2 | "Eva interrupted, her green eyes darting nervously around the platform" |
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| 69.19% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 24 | | fancyCount | 8 | | fancyTags | | 0 | "she noted (note)" | | 1 | "she ordered (order)" | | 2 | "Eva interrupted (interrupt)" | | 3 | "Quinn repeated flatly (repeat)" | | 4 | "Eva whispered (whisper)" | | 5 | "Eva interjected (interject)" | | 6 | "Eva suggested (suggest)" | | 7 | "Eva whispered (whisper)" |
| | dialogueSentences | 99 | | tagDensity | 0.242 | | leniency | 0.485 | | rawRatio | 0.333 | | effectiveRatio | 0.162 | |