| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2628 | | 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) | |
| 82.88% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2628 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "measured" | | 1 | "trembled" | | 2 | "traced" | | 3 | "flicked" | | 4 | "perfect" | | 5 | "silence" | | 6 | "stomach" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 303 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 303 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 303 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2625 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 2625 | | uniqueNames | 15 | | maxNameDensity | 1.18 | | worstName | "You" | | maxWindowNameDensity | 3.5 | | worstWindowName | "You" | | discoveredNames | | Rory | 3 | | Eva | 9 | | Lucien | 6 | | Brick | 1 | | Lane | 1 | | Ptolemy | 9 | | Jenga | 1 | | Silas | 1 | | God | 1 | | Thames | 1 | | Hell | 1 | | Mayfair | 1 | | You | 31 | | Do | 3 | | Don | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Ptolemy" | | 4 | "Silas" | | 5 | "God" | | 6 | "You" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Thames" | | 3 | "Hell" | | 4 | "Mayfair" | | 5 | "Do" |
| | globalScore | 0.91 | | windowScore | 0.5 | |
| 82.80% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 186 | | glossingSentenceCount | 5 | | matches | | 0 | "smelled like rain and expensive soap" | | 1 | "as if waiting for a password" | | 2 | "as if disavowing affiliation" | | 3 | "sounded like a clock wound too tight" | | 4 | "looked like ants that had been scattered" |
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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 | 2625 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 303 | | matches | | 0 | "touch that, it’s" | | 1 | "had that photograph" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 135 | | mean | 19.44 | | std | 18.78 | | cv | 0.966 | | sampleLengths | | 0 | 60 | | 1 | 4 | | 2 | 35 | | 3 | 47 | | 4 | 2 | | 5 | 40 | | 6 | 12 | | 7 | 30 | | 8 | 5 | | 9 | 3 | | 10 | 8 | | 11 | 5 | | 12 | 42 | | 13 | 73 | | 14 | 2 | | 15 | 6 | | 16 | 39 | | 17 | 5 | | 18 | 7 | | 19 | 65 | | 20 | 1 | | 21 | 3 | | 22 | 2 | | 23 | 47 | | 24 | 5 | | 25 | 10 | | 26 | 6 | | 27 | 45 | | 28 | 4 | | 29 | 17 | | 30 | 54 | | 31 | 2 | | 32 | 9 | | 33 | 4 | | 34 | 5 | | 35 | 75 | | 36 | 19 | | 37 | 9 | | 38 | 8 | | 39 | 31 | | 40 | 49 | | 41 | 8 | | 42 | 9 | | 43 | 34 | | 44 | 16 | | 45 | 8 | | 46 | 7 | | 47 | 4 | | 48 | 8 | | 49 | 53 |
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| 99.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 303 | | matches | | 0 | "been told" | | 1 | "gets mentioned" | | 2 | "was starved" | | 3 | "been rescued" | | 4 | "been scattered" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 515 | | matches | | 0 | "was leaving" | | 1 | "was dying" | | 2 | "were leaving" | | 3 | "was tailing" |
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| 95.71% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 2 | | flaggedSentences | 5 | | totalSentences | 303 | | ratio | 0.017 | | matches | | 0 | "You bleed on Eva’s books; she’ll exorcise you herself." | | 1 | "I thought— God, forget it." | | 2 | "That night behind the bar, you— Her voice roughened." | | 3 | "—you kissed me like you were leaving a place you hated and coming home in the same breath." | | 4 | "It wasn’t about the limp; it was about the blade hidden in the hollow." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2628 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 73 | | adverbRatio | 0.027777777777777776 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.0030441400304414 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 303 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 303 | | mean | 8.66 | | std | 6.08 | | cv | 0.702 | | sampleLengths | | 0 | 7 | | 1 | 20 | | 2 | 9 | | 3 | 24 | | 4 | 2 | | 5 | 1 | | 6 | 1 | | 7 | 16 | | 8 | 13 | | 9 | 1 | | 10 | 5 | | 11 | 9 | | 12 | 8 | | 13 | 9 | | 14 | 5 | | 15 | 16 | | 16 | 2 | | 17 | 9 | | 18 | 31 | | 19 | 9 | | 20 | 3 | | 21 | 16 | | 22 | 11 | | 23 | 3 | | 24 | 5 | | 25 | 3 | | 26 | 4 | | 27 | 4 | | 28 | 5 | | 29 | 8 | | 30 | 7 | | 31 | 21 | | 32 | 6 | | 33 | 7 | | 34 | 10 | | 35 | 26 | | 36 | 19 | | 37 | 3 | | 38 | 8 | | 39 | 2 | | 40 | 6 | | 41 | 23 | | 42 | 16 | | 43 | 2 | | 44 | 3 | | 45 | 7 | | 46 | 10 | | 47 | 4 | | 48 | 1 | | 49 | 16 |
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| 39.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 31 | | diversityRatio | 0.2607260726072607 | | totalSentences | 303 | | uniqueOpeners | 79 | |
| 37.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 270 | | matches | | 0 | "Then you walked away and" | | 1 | "Only the street lamps smeared" | | 2 | "Only when someone tells me" |
| | ratio | 0.011 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 168 | | totalSentences | 270 | | matches | | 0 | "She unlatched the first deadbolt," | | 1 | "Her chest tightened as if" | | 2 | "She slid the last bolt." | | 3 | "He put a gloved hand" | | 4 | "Her grip flexed around the" | | 5 | "She folded the towel, gave" | | 6 | "You’ve got nerve." | | 7 | "His gaze dropped to the" | | 8 | "He rested the ivory handle" | | 9 | "I’ve been told." | | 10 | "You don’t do Brick Lane." | | 11 | "I do tonight." | | 12 | "She held her ground." | | 13 | "I know whose it is." | | 14 | "He watched her, expression clean" | | 15 | "He smelled like rain and" | | 16 | "She let the door swing" | | 17 | "He stepped past her without" | | 18 | "He always walked like a" | | 19 | "He looked for a second" |
| | ratio | 0.622 | |
| 45.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 224 | | totalSentences | 270 | | matches | | 0 | "The first knock rattled all" | | 1 | "Ptolemy’s ears pricked from the" | | 2 | "Curry, onions and rain crept" | | 3 | "Rory wiped soy sauce off" | | 4 | "She unlatched the first deadbolt," | | 5 | "Her chest tightened as if" | | 6 | "She slid the last bolt." | | 7 | "Lucien filled the doorway like" | | 8 | "He put a gloved hand" | | 9 | "Her grip flexed around the" | | 10 | "Ptolemy stuck his tabby face" | | 11 | "She folded the towel, gave" | | 12 | "You’ve got nerve." | | 13 | "His gaze dropped to the" | | 14 | "He rested the ivory handle" | | 15 | "I’ve been told." | | 16 | "You don’t do Brick Lane." | | 17 | "I do tonight." | | 18 | "She held her ground." | | 19 | "This isn’t my place." |
| | ratio | 0.83 | |
| 92.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 270 | | matches | | 0 | "If you’re offering." | | 1 | "If you say no, I" | | 2 | "If you had that photograph," | | 3 | "Because you collect keys." | | 4 | "Because people collect lives and" |
| | ratio | 0.019 | |
| 96.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 107 | | technicalSentenceCount | 7 | | matches | | 0 | "The flat swallowed him, and his attention pulled over the riot of books and scribbled notes that mapped the coffee table and most of the floor." | | 1 | "He removed his gloves and slid them into his breast pocket, then set the cane beside the bookshelf that leaned like a drunk." | | 2 | "He watched her tear open a plaster, attention steady in a way that made the room tilt." | | 3 | "She pulled her hand back from the notes as though they were hot." | | 4 | "The part of her that had slept with the sound of his voice under her night, like a radio in another room, woke and stretched." | | 5 | "I was tailing a man who has a photograph of you in his pocket." | | 6 | "He flicked the switch and the flat sank into the kind of half-dark that forgave a crowd of sins." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |