| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva said finally [finally]" | | 1 | "Eva said quietly [quietly]" |
| | dialogueSentences | 45 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.1 | | effectiveRatio | 0.089 | |
| 86.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1430 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "very" | | 3 | "carefully" |
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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) | |
| 82.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1430 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "lilt" | | 1 | "silence" | | 2 | "weight" |
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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 | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 64 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 87 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1453 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 14.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 809 | | uniqueNames | 10 | | maxNameDensity | 2.72 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 2 | | Rory | 22 | | Welsh | 1 | | Cardiff | 1 | | London | 1 | | Eva | 18 | | Recalibrated | 1 | | Eva-like | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Eva" |
| | places | | | globalScore | 0.14 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.688 | | wordCount | 1453 | | matches | | 0 | "not finished, but I'm someone" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 88 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 39.27 | | std | 33.32 | | cv | 0.848 | | sampleLengths | | 0 | 90 | | 1 | 16 | | 2 | 1 | | 3 | 29 | | 4 | 112 | | 5 | 6 | | 6 | 45 | | 7 | 44 | | 8 | 32 | | 9 | 48 | | 10 | 2 | | 11 | 31 | | 12 | 7 | | 13 | 96 | | 14 | 4 | | 15 | 49 | | 16 | 27 | | 17 | 53 | | 18 | 3 | | 19 | 25 | | 20 | 28 | | 21 | 58 | | 22 | 44 | | 23 | 2 | | 24 | 55 | | 25 | 34 | | 26 | 137 | | 27 | 10 | | 28 | 87 | | 29 | 53 | | 30 | 75 | | 31 | 28 | | 32 | 4 | | 33 | 71 | | 34 | 10 | | 35 | 3 | | 36 | 34 |
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| 99.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 64 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 142 | | matches | | 0 | "was lying" | | 1 | "was drying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 88 | | ratio | 0.068 | | matches | | 0 | "The dinner crowd had thinned to a handful of regulars hunched over their pints like figures in an old photograph — fitting, given the walls." | | 1 | "So was the coat draped over the booth's bench — camel-coloured, real wool, the kind of coat that cost more than Rory's rent." | | 2 | "They hugged the way people hug when they've been picturing it for years and find the reality slightly misaligned — a beat too long, an elbow in the wrong place." | | 3 | "When the drinks came — whisky, because Eva had been right, it was that kind of place — Rory studied her friend across the rim of the glass." | | 4 | "\"Writing.\" Eva's face did something complicated — delight and confusion and something almost like fear, all trying to surface at once." | | 5 | "She didn't cry; Rory suspected she'd trained herself out of it, somewhere along the partner track." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 807 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.03469640644361834 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.01486988847583643 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 16.51 | | std | 15.52 | | cv | 0.94 | | sampleLengths | | 0 | 21 | | 1 | 40 | | 2 | 4 | | 3 | 25 | | 4 | 11 | | 5 | 2 | | 6 | 3 | | 7 | 1 | | 8 | 21 | | 9 | 8 | | 10 | 10 | | 11 | 24 | | 12 | 39 | | 13 | 12 | | 14 | 23 | | 15 | 4 | | 16 | 5 | | 17 | 1 | | 18 | 30 | | 19 | 7 | | 20 | 4 | | 21 | 4 | | 22 | 41 | | 23 | 3 | | 24 | 19 | | 25 | 13 | | 26 | 32 | | 27 | 16 | | 28 | 2 | | 29 | 16 | | 30 | 15 | | 31 | 7 | | 32 | 28 | | 33 | 10 | | 34 | 2 | | 35 | 2 | | 36 | 17 | | 37 | 22 | | 38 | 15 | | 39 | 4 | | 40 | 24 | | 41 | 19 | | 42 | 1 | | 43 | 5 | | 44 | 21 | | 45 | 6 | | 46 | 21 | | 47 | 32 | | 48 | 3 | | 49 | 25 |
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| 70.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4772727272727273 | | totalSentences | 88 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 54 | | matches | | 0 | "Only one person in the" | | 1 | "Then she reached across the" |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 54 | | matches | | 0 | "It was nearly eleven." | | 1 | "She was halfway to the" | | 2 | "They hugged the way people" | | 3 | "It came out flatter than" | | 4 | "It didn't last." | | 5 | "She broke off, jaw working" | | 6 | "She didn't cry; Rory suspected" | | 7 | "He didn't look at them." | | 8 | "He had the professional's gift" | | 9 | "she chose the words carefully," | | 10 | "They exchanged numbers like a" |
| | ratio | 0.204 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 54 | | matches | | 0 | "The green neon of the" | | 1 | "Rory pushed through the door" | | 2 | "It was nearly eleven." | | 3 | "The dinner crowd had thinned" | | 4 | "She was halfway to the" | | 5 | "The other one." | | 6 | "Rory stopped with her hand" | | 7 | "The woman rising from the" | | 8 | "That was the first thing," | | 9 | "Eva had been dark-haired all" | | 10 | "The blonde was expensive, glossed" | | 11 | "They hugged the way people" | | 12 | "Eva smelled of perfume Rory" | | 13 | "Eva had never smoked." | | 14 | "Eva laughed, and the laugh" | | 15 | "Rory slid into the booth," | | 16 | "Eva gestured at the dim" | | 17 | "Eva signalled the bar with" | | 18 | "The changes kept arriving in" | | 19 | "The careful, polished stillness of" |
| | ratio | 0.833 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 57.14% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 3 | | matches | | 0 | "Rory pushed through the door with a delivery bag still slung over her shoulder, smelling of sesame oil and wet wool, and Silas glanced up from the taps with the…" | | 1 | "So was the coat draped over the booth's bench — camel-coloured, real wool, the kind of coat that cost more than Rory's rent." | | 2 | "And underneath all of it, something Rory couldn't name at first: a tightness around Eva's eyes that hadn't been there at twenty-two." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva laughed, and the laugh was the old laugh, and for a second Rory was eighteen again, sharing chips on a wall overlooking the bay" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "Eva laughed (laugh)" | | 1 | "Eva admitted (admit)" | | 2 | "Rory admitted (admit)" |
| | dialogueSentences | 45 | | tagDensity | 0.178 | | leniency | 0.356 | | rawRatio | 0.375 | | effectiveRatio | 0.133 | |