| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Rory said quietly [quietly]" |
| | dialogueSentences | 40 | | tagDensity | 0.425 | | leniency | 0.85 | | rawRatio | 0.059 | | effectiveRatio | 0.05 | |
| 90.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1538 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "quickly" | | 2 | "perfectly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 54.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1538 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "warmth" | | 1 | "methodical" | | 2 | "weight" | | 3 | "scanning" | | 4 | "measured" | | 5 | "flickered" | | 6 | "dancing" | | 7 | "familiar" | | 8 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 63 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1524 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 73 | | wordCount | 1166 | | uniqueNames | 16 | | maxNameDensity | 2.57 | | worstName | "Eva" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Eva" | | discoveredNames | | London | 3 | | Carter | 1 | | Raven | 1 | | Nest | 1 | | Thursday | 1 | | Silas | 3 | | Jameson | 1 | | Thames | 1 | | Fifties | 1 | | Eva | 30 | | Davies | 1 | | Cardiff | 2 | | Rory | 22 | | Soho | 2 | | Evan | 2 | | Facebook | 1 |
| | persons | | 0 | "Carter" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Jameson" | | 5 | "Eva" | | 6 | "Davies" | | 7 | "Rory" | | 8 | "Evan" |
| | places | | 0 | "London" | | 1 | "Thames" | | 2 | "Fifties" | | 3 | "Cardiff" | | 4 | "Soho" |
| | globalScore | 0.214 | | windowScore | 0 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "drizzle that seemed to seep through the skin rather than fall from the sky" | | 1 | "felt like maybe they had not lost as mu" |
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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 | 1524 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 36.29 | | std | 28.6 | | cv | 0.788 | | sampleLengths | | 0 | 94 | | 1 | 104 | | 2 | 14 | | 3 | 28 | | 4 | 25 | | 5 | 27 | | 6 | 69 | | 7 | 69 | | 8 | 19 | | 9 | 25 | | 10 | 39 | | 11 | 7 | | 12 | 27 | | 13 | 27 | | 14 | 29 | | 15 | 65 | | 16 | 11 | | 17 | 34 | | 18 | 16 | | 19 | 3 | | 20 | 36 | | 21 | 3 | | 22 | 49 | | 23 | 4 | | 24 | 36 | | 25 | 70 | | 26 | 7 | | 27 | 37 | | 28 | 56 | | 29 | 12 | | 30 | 13 | | 31 | 79 | | 32 | 34 | | 33 | 32 | | 34 | 69 | | 35 | 9 | | 36 | 5 | | 37 | 117 | | 38 | 24 | | 39 | 28 | | 40 | 6 | | 41 | 66 |
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| 83.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 82 | | matches | | 0 | "were wrapped" | | 1 | "been practiced" | | 2 | "been eleven" | | 3 | "was clipped" | | 4 | "been written" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 187 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 104 | | ratio | 0.096 | | matches | | 0 | "Her delivery bag hung limp against her hip, the last order of the night—a container of salt-and-pepper squid for a regular who always tipped in crumpled fivers—already dropped off fifteen minutes ago." | | 1 | "The bar was quiet for a Thursday—three regulars huntered at the far end, a couple arguing in a booth near the jukebox." | | 2 | "She turned, scanning the dim room, and there—sitting alone at the corner table beneath a photograph of the Thames in the Fifties—was Eva." | | 3 | "She wore a grey coat that looked expensive—too expensive for the rainy Soho nights Rory knew—and her hands were wrapped around a glass of wine that she had not touched." | | 4 | "“Do I?” Eva tilted her head, and something flickered in her eyes—hurt, maybe, or anger carefully buried." | | 5 | "Rory looked down at her hands on the scarred tabletop, at the pale crescent on her wrist, that old scar from a childhood accident she and Eva had both witnessed—a fall from a garden wall, a trip to A&E, Eva holding her hand while the doctor stitched her up." | | 6 | "The jukebox switched songs—something old, a woman singing about regret and rain." | | 7 | "She remembered Eva’s wedding photos, tagged on Facebook by mutual friends she had stopped following—Eva in white lace, Eva cutting a cake, Eva dancing with a man whose name Rory had never learned." | | 8 | "Evan had never found her—had not even tried, as far as she knew—but the memory of his hands on her throat had lived in her bones like an old ache." | | 9 | "Rory looked at their hands, at Eva’s ringless fingers—the wedding band gone, the tan line still faint." |
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| 98.06% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 758 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.04221635883905013 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005277044854881266 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 14.65 | | std | 10.5 | | cv | 0.716 | | sampleLengths | | 0 | 22 | | 1 | 25 | | 2 | 32 | | 3 | 9 | | 4 | 6 | | 5 | 20 | | 6 | 22 | | 7 | 20 | | 8 | 27 | | 9 | 15 | | 10 | 10 | | 11 | 4 | | 12 | 17 | | 13 | 11 | | 14 | 12 | | 15 | 13 | | 16 | 4 | | 17 | 23 | | 18 | 2 | | 19 | 1 | | 20 | 19 | | 21 | 37 | | 22 | 10 | | 23 | 3 | | 24 | 22 | | 25 | 30 | | 26 | 14 | | 27 | 3 | | 28 | 16 | | 29 | 19 | | 30 | 6 | | 31 | 13 | | 32 | 7 | | 33 | 19 | | 34 | 7 | | 35 | 8 | | 36 | 19 | | 37 | 22 | | 38 | 5 | | 39 | 17 | | 40 | 12 | | 41 | 5 | | 42 | 49 | | 43 | 4 | | 44 | 7 | | 45 | 11 | | 46 | 3 | | 47 | 12 | | 48 | 12 | | 49 | 7 |
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| 43.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3269230769230769 | | totalSentences | 104 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 75 | | matches | | 0 | "Instead, she pushed open the" | | 1 | "Then Eva smiled." | | 2 | "Then Eva laughed, a dry," |
| | ratio | 0.04 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 75 | | matches | | 0 | "Her delivery bag hung limp" | | 1 | "She should have gone straight" | | 2 | "He glanced up at her" | | 3 | "he said, the word carrying" | | 4 | "She shrugged off her jacket," | | 5 | "She turned, scanning the dim" | | 6 | "She looked different." | | 7 | "She wore a grey coat" | | 8 | "It was a careful thing," | | 9 | "she said, using the old" | | 10 | "She slid into the booth" | | 11 | "They had been eleven." | | 12 | "She just held it, the" | | 13 | "She remembered Eva’s wedding photos," | | 14 | "She had scrolled past them" | | 15 | "It was not an accusation." | | 16 | "It was not even a" | | 17 | "She looked away, at the" | | 18 | "It was the truth." | | 19 | "She had spent those first" |
| | ratio | 0.333 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 75 | | matches | | 0 | "The rain had settled into" | | 1 | "Aurora Carter stood beneath the" | | 2 | "Her delivery bag hung limp" | | 3 | "She should have gone straight" | | 4 | "The warmth hit her first," | | 5 | "The bar was quiet for" | | 6 | "The maps on the walls" | | 7 | "Silas stood behind the bar," | | 8 | "He glanced up at her" | | 9 | "he said, the word carrying" | | 10 | "She shrugged off her jacket," | | 11 | "Silas set the glass down" | | 12 | "Rory’s blood went cold." | | 13 | "She turned, scanning the dim" | | 14 | "Eva *Rowan* now, married name," | | 15 | "Eva, who had been her" | | 16 | "Eva, who had not spoken" | | 17 | "She looked different." | | 18 | "The woman at the table" | | 19 | "She wore a grey coat" |
| | ratio | 0.92 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 75 | | matches | | 0 | "Now it was just memory." |
| | ratio | 0.013 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 4 | | matches | | 0 | "Silas stood behind the bar, polishing a glass with the methodical attention of a man who had spent decades learning to look at nothing while seeing everything." | | 1 | "She wore a grey coat that looked expensive—too expensive for the rainy Soho nights Rory knew—and her hands were wrapped around a glass of wine that she had not …" | | 2 | "It was a careful thing, measured and precise, a smile that had been practiced in mirrors." | | 3 | "Silas busied himself at the bar, polishing glasses that were already clean, giving them the privacy they had both come seeking." |
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| 7.35% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 4 | | matches | | 0 | "he said, the word carrying the weight of years" | | 1 | "She shrugged, the damp fabric clinging to her arms" | | 2 | "Rory said, and the nonsequitur hung between them, strange and fragile" | | 3 | "Rory said, and the words came out raw and quiet, stripped of all the armor she had worn for so long" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 40 | | tagDensity | 0.225 | | leniency | 0.45 | | rawRatio | 0 | | effectiveRatio | 0 | |