| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 88.52% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1742 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "reluctantly" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "reluctantly" | | 2 | "quickly" | | 3 | "lightly" |
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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) | |
| 77.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1742 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "footsteps" | | 3 | "unspoken" | | 4 | "absolutely" |
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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 | 151 | | matches | (empty) | |
| 67.17% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 7 | | hedgeCount | 1 | | narrationSentences | 151 | | filterMatches | | 0 | "think" | | 1 | "look" | | 2 | "know" | | 3 | "watch" |
| | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 151 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1745 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 26 | | unquotedAttributions | 15 | | matches | | 0 | "Rory, he said." | | 1 | "Slow Tuesday, she said." | | 2 | "You shrank, Rory said, because Eva had not, because it was the kind of stupid thing they used to say to each other." | | 3 | "So this is where you ended up, she said." | | 4 | "Brendan came around, Rory said." | | 5 | "I miss the cheap part, Rory said." | | 6 | "I heard about Evan, Eva said quietly." | | 7 | "He showed up once, Rory said." | | 8 | "Good, Eva said, too quickly." | | 9 | "You look different, Rory said, because she could not say the other thing yet." | | 10 | "You were supposed to be a drummer, Rory said." | | 11 | "I thought about calling, she said." | | 12 | "I needed you, Rory said before she could stop herself." | | 13 | "I know, Eva whispered." | | 14 | "You told her anyway, Rory said." |
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| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 122 | | wordCount | 1745 | | uniqueNames | 35 | | maxNameDensity | 1.83 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Greek | 2 | | Street | 2 | | Rory | 32 | | Raven | 1 | | Nest | 2 | | Silas | 9 | | London | 2 | | Soho | 2 | | Golden | 1 | | Empress | 1 | | Tuesday | 1 | | Prague | 1 | | St | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Cardiff | 5 | | Eva | 21 | | Evan | 3 | | God | 1 | | Christmas | 1 | | Jennifer | 1 | | Ellis | 1 | | Pre-Law | 1 | | Brendan | 2 | | Carter | 1 | | Come | 3 | | Cerys | 1 | | Mark | 2 | | Croydon | 2 | | Blue | 1 | | National | 1 | | Express | 1 | | Don | 2 | | You | 10 | | Do | 3 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Eva" | | 5 | "Evan" | | 6 | "God" | | 7 | "Jennifer" | | 8 | "Ellis" | | 9 | "Brendan" | | 10 | "Carter" | | 11 | "Come" | | 12 | "Mark" | | 13 | "Blue" | | 14 | "You" |
| | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "London" | | 3 | "Soho" | | 4 | "Prague" | | 5 | "St" | | 6 | "Shaftesbury" | | 7 | "Avenue" | | 8 | "Cardiff" | | 9 | "Cerys" | | 10 | "Croydon" |
| | globalScore | 0.583 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 93 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.573 | | wordCount | 1745 | | matches | | 0 | "not gone, but shared again for an evening at least, while the rain kept fa" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 151 | | matches | | 0 | "fit that over" | | 1 | "settled, that you" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 34.9 | | std | 27.85 | | cv | 0.798 | | sampleLengths | | 0 | 92 | | 1 | 90 | | 2 | 75 | | 3 | 6 | | 4 | 25 | | 5 | 110 | | 6 | 75 | | 7 | 14 | | 8 | 48 | | 9 | 11 | | 10 | 91 | | 11 | 7 | | 12 | 3 | | 13 | 55 | | 14 | 41 | | 15 | 25 | | 16 | 20 | | 17 | 50 | | 18 | 19 | | 19 | 35 | | 20 | 8 | | 21 | 89 | | 22 | 12 | | 23 | 30 | | 24 | 16 | | 25 | 10 | | 26 | 10 | | 27 | 34 | | 28 | 14 | | 29 | 39 | | 30 | 48 | | 31 | 9 | | 32 | 5 | | 33 | 10 | | 34 | 20 | | 35 | 55 | | 36 | 49 | | 37 | 8 | | 38 | 55 | | 39 | 46 | | 40 | 6 | | 41 | 16 | | 42 | 68 | | 43 | 15 | | 44 | 32 | | 45 | 53 | | 46 | 16 | | 47 | 5 | | 48 | 24 | | 49 | 51 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 151 | | matches | | 0 | "being asked" | | 1 | "were supposed" |
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| 95.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 318 | | matches | | 0 | "was polishing" | | 1 | "was watching" | | 2 | "was crossing" | | 3 | "were hugging" | | 4 | "was watching" |
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| 86.09% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 151 | | ratio | 0.02 | | matches | | 0 | "Silas said you — God, look at you." | | 1 | "I'm glad someone —" | | 2 | "I was going to come help you find somewhere, but then Mark's mother got sick and we moved to bloody Croydon for six months and — I kept thinking you'd settled, that you didn't need me turning up with an overnight bag and opinions." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1758 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 63 | | adverbRatio | 0.03583617747440273 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.009101251422070534 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 151 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 151 | | mean | 11.56 | | std | 10.91 | | cv | 0.944 | | sampleLengths | | 0 | 20 | | 1 | 32 | | 2 | 40 | | 3 | 10 | | 4 | 22 | | 5 | 24 | | 6 | 34 | | 7 | 7 | | 8 | 25 | | 9 | 43 | | 10 | 3 | | 11 | 3 | | 12 | 4 | | 13 | 21 | | 14 | 20 | | 15 | 16 | | 16 | 25 | | 17 | 18 | | 18 | 31 | | 19 | 16 | | 20 | 13 | | 21 | 8 | | 22 | 8 | | 23 | 30 | | 24 | 14 | | 25 | 7 | | 26 | 15 | | 27 | 26 | | 28 | 6 | | 29 | 5 | | 30 | 19 | | 31 | 48 | | 32 | 6 | | 33 | 18 | | 34 | 7 | | 35 | 1 | | 36 | 2 | | 37 | 9 | | 38 | 36 | | 39 | 10 | | 40 | 29 | | 41 | 4 | | 42 | 8 | | 43 | 23 | | 44 | 2 | | 45 | 12 | | 46 | 4 | | 47 | 4 | | 48 | 18 | | 49 | 3 |
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| 56.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.39072847682119205 | | totalSentences | 151 | | uniqueOpeners | 59 | |
| 78.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 127 | | matches | | 0 | "Then the woman at the" | | 1 | "All that quick, out-of-the-box thinking" | | 2 | "Still hiding behind it." |
| | ratio | 0.024 | |
| 46.77% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 127 | | matches | | 0 | "She could see it through" | | 1 | "He was polishing a glass" | | 2 | "You're off early." | | 3 | "He smiled under his neatly" | | 4 | "His hazel eyes moved past" | | 5 | "He carried himself with that" | | 6 | "She had learned not to" | | 7 | "She slid onto the stool" | | 8 | "She ordered a half and" | | 9 | "She was watching Silas's hands," | | 10 | "It was the laugh she" | | 11 | "Her hair, which had been" | | 12 | "She was thinner in the" | | 13 | "She held herself differently, contained," | | 14 | "Their eyes met and Eva" | | 15 | "She stood so fast she" | | 16 | "You live here now?" | | 17 | "You shrank, Rory said, because" | | 18 | "He remembered names." | | 19 | "He remembered everyone." |
| | ratio | 0.433 | |
| 62.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 101 | | totalSentences | 127 | | matches | | 0 | "The rain had turned Greek" | | 1 | "She could see it through" | | 2 | "The bar was dim the" | | 3 | "The air smelled of wood" | | 4 | "Silas looked up from behind" | | 5 | "He was polishing a glass" | | 6 | "Rory, he said." | | 7 | "You're off early." | | 8 | "Yu-Fei sent me home with" | | 9 | "He smiled under his neatly" | | 10 | "His hazel eyes moved past" | | 11 | "The silver signet ring on" | | 12 | "He carried himself with that" | | 13 | "She had learned not to" | | 14 | "She slid onto the stool" | | 15 | "The little crescent-shaped scar there," | | 16 | "Cardiff, age nine, the low" | | 17 | "Teilo's when someone dared someone" | | 18 | "She ordered a half and" | | 19 | "The door opened and let" |
| | ratio | 0.795 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 127 | | matches | (empty) | | ratio | 0 | |
| 87.05% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 5 | | matches | | 0 | "He carried himself with that quiet authority that made new drinkers sit up straighter without quite knowing why." | | 1 | "Her hair, which had been long and violently red through all of sixth form, all of that first year at Cardiff when they shared a kitchen with three other girls a…" | | 2 | "I kept listening for his key in a lock that wasn't his." | | 3 | "Rory glanced toward Silas, who was watching the door again with that patient, professional stillness, toward the bookshelf in the back that wasn't just a booksh…" | | 4 | "Silas, overhearing, lifted his glass-polishing cloth in a salute that said he absolutely would judge them, kindly, and they both laughed, and the weight shifted…" |
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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 | |