| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said again [again]" |
| | dialogueSentences | 80 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0.04 | | effectiveRatio | 0.025 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1840 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 83.70% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1840 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "familiar" | | 1 | "eyebrow" | | 2 | "trembled" | | 3 | "dancing" | | 4 | "determined" | | 5 | "silence" |
| |
| 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 | 1 | | narrationSentences | 132 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 132 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 187 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1840 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 103 | | wordCount | 1388 | | uniqueNames | 11 | | maxNameDensity | 3.39 | | worstName | "Rory" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 39 | | Rory | 47 | | Silas | 7 | | Brendan | 1 | | Carter | 1 | | Jennifer | 2 | | London | 1 | | Evan | 2 | | Tube | 1 | | Nest | 1 | | Victoria | 1 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Brendan" | | 4 | "Carter" | | 5 | "Jennifer" | | 6 | "Evan" |
| | places | | 0 | "London" | | 1 | "Nest" | | 2 | "Victoria" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | 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 | 1840 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 187 | | matches | | 0 | "complained that a" | | 1 | "remembered that party" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 97 | | mean | 18.97 | | std | 18.2 | | cv | 0.959 | | sampleLengths | | 0 | 18 | | 1 | 69 | | 2 | 26 | | 3 | 28 | | 4 | 4 | | 5 | 57 | | 6 | 27 | | 7 | 2 | | 8 | 6 | | 9 | 10 | | 10 | 14 | | 11 | 35 | | 12 | 9 | | 13 | 3 | | 14 | 4 | | 15 | 47 | | 16 | 6 | | 17 | 3 | | 18 | 27 | | 19 | 37 | | 20 | 13 | | 21 | 3 | | 22 | 51 | | 23 | 13 | | 24 | 7 | | 25 | 54 | | 26 | 7 | | 27 | 3 | | 28 | 49 | | 29 | 7 | | 30 | 9 | | 31 | 6 | | 32 | 45 | | 33 | 5 | | 34 | 2 | | 35 | 61 | | 36 | 13 | | 37 | 2 | | 38 | 9 | | 39 | 15 | | 40 | 14 | | 41 | 18 | | 42 | 2 | | 43 | 7 | | 44 | 5 | | 45 | 63 | | 46 | 5 | | 47 | 2 | | 48 | 6 | | 49 | 42 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 132 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 259 | | matches | | 0 | "was polishing" | | 1 | "were gripping" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 187 | | ratio | 0.005 | | matches | | 0 | "She had cut it falling through a greenhouse pane at eleven; Eva had held a towel around it all the way to the hospital and cried harder than Rory had." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1391 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.023005032350826744 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.005751258087706686 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 187 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 187 | | mean | 9.84 | | std | 6.9 | | cv | 0.701 | | sampleLengths | | 0 | 18 | | 1 | 7 | | 2 | 19 | | 3 | 5 | | 4 | 20 | | 5 | 18 | | 6 | 13 | | 7 | 13 | | 8 | 7 | | 9 | 13 | | 10 | 8 | | 11 | 4 | | 12 | 7 | | 13 | 30 | | 14 | 8 | | 15 | 12 | | 16 | 15 | | 17 | 12 | | 18 | 2 | | 19 | 6 | | 20 | 7 | | 21 | 3 | | 22 | 13 | | 23 | 1 | | 24 | 11 | | 25 | 14 | | 26 | 10 | | 27 | 9 | | 28 | 3 | | 29 | 4 | | 30 | 9 | | 31 | 21 | | 32 | 9 | | 33 | 8 | | 34 | 6 | | 35 | 3 | | 36 | 23 | | 37 | 4 | | 38 | 12 | | 39 | 8 | | 40 | 17 | | 41 | 10 | | 42 | 3 | | 43 | 3 | | 44 | 22 | | 45 | 21 | | 46 | 8 | | 47 | 10 | | 48 | 3 | | 49 | 5 |
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| 43.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.29411764705882354 | | totalSentences | 187 | | uniqueOpeners | 55 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 111 | | matches | (empty) | | ratio | 0 | |
| 90.27% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 111 | | matches | | 0 | "She had her back to" | | 1 | "Her dark coat was damp" | | 2 | "His gaze went from Rory" | | 3 | "He set down the glass" | | 4 | "She wore a charcoal suit" | | 5 | "He favoured his left leg," | | 6 | "His silver signet ring flashed" | | 7 | "He took the bag without" | | 8 | "She looked towards the front" | | 9 | "She had never considered what" | | 10 | "She used to sing on" | | 11 | "She tucked her left hand" | | 12 | "She had cut it falling" | | 13 | "She hadn’t asked for one." | | 14 | "He went to the other" | | 15 | "She hadn’t known how frightened" | | 16 | "It had been Eva who" | | 17 | "She’d made it sound simple" | | 18 | "She took a sip of" | | 19 | "It was worse than she’d" |
| | ratio | 0.324 | |
| 27.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 111 | | matches | | 0 | "Rory knew the woman at" | | 1 | "She had her back to" | | 2 | "Her dark coat was damp" | | 3 | "None of that was familiar." | | 4 | "Rory stopped beneath the green" | | 5 | "Rain slipped from the delivery" | | 6 | "Silas looked up from behind" | | 7 | "His gaze went from Rory" | | 8 | "He set down the glass" | | 9 | "the woman said" | | 10 | "Eva’s face was thinner than" | | 11 | "The freckles were still there," | | 12 | "She wore a charcoal suit" | | 13 | "Rory had imagined meeting her" | | 14 | "Rory shifted the bag higher" | | 15 | "Eva glanced at the ceiling," | | 16 | "Silas came out from behind" | | 17 | "He favoured his left leg," | | 18 | "His silver signet ring flashed" | | 19 | "He took the bag without" |
| | ratio | 0.865 | |
| 90.09% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 111 | | matches | | 0 | "Now she could think only" | | 1 | "Now she sat with both" |
| | ratio | 0.018 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 80 | | tagDensity | 0.238 | | leniency | 0.475 | | rawRatio | 0 | | effectiveRatio | 0 | |