| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 1 | | adverbTags | | 0 | "Quinn's fingers tightened around [around]" |
| | dialogueSentences | 38 | | tagDensity | 0.395 | | leniency | 0.789 | | rawRatio | 0.067 | | effectiveRatio | 0.053 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 994 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 54.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 994 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "shattered" | | 1 | "etched" | | 2 | "silence" | | 3 | "loomed" | | 4 | "traced" | | 5 | "raced" | | 6 | "flickered" |
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| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
| | 1 | | label | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" | | 2 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 95 | | matches | (empty) | |
| 97.74% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 95 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 994 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 34.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 734 | | uniqueNames | 9 | | maxNameDensity | 2.32 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Quinn | 17 | | Kowalski | 1 | | Tube | 1 | | Camden | 1 | | Market | 2 | | French | 2 | | Eva | 14 | | Morris | 1 | | Shade | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Kowalski" | | 2 | "Eva" | | 3 | "Morris" |
| | places | (empty) | | globalScore | 0.342 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | 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 | 994 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 22.09 | | std | 14.23 | | cv | 0.644 | | sampleLengths | | 0 | 7 | | 1 | 42 | | 2 | 33 | | 3 | 47 | | 4 | 20 | | 5 | 61 | | 6 | 21 | | 7 | 23 | | 8 | 4 | | 9 | 27 | | 10 | 41 | | 11 | 10 | | 12 | 13 | | 13 | 4 | | 14 | 44 | | 15 | 36 | | 16 | 2 | | 17 | 33 | | 18 | 4 | | 19 | 28 | | 20 | 45 | | 21 | 6 | | 22 | 18 | | 23 | 30 | | 24 | 6 | | 25 | 28 | | 26 | 10 | | 27 | 35 | | 28 | 30 | | 29 | 16 | | 30 | 7 | | 31 | 37 | | 32 | 14 | | 33 | 27 | | 34 | 21 | | 35 | 17 | | 36 | 35 | | 37 | 20 | | 38 | 21 | | 39 | 8 | | 40 | 6 | | 41 | 27 | | 42 | 21 | | 43 | 5 | | 44 | 4 |
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| 97.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 95 | | matches | | 0 | "been used" | | 1 | "was involved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 131 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 117 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 736 | | adjectiveStacks | 2 | | stackExamples | | 0 | "old rectangular green French" | | 1 | "old rectangular green French" |
| | adverbCount | 16 | | adverbRatio | 0.021739130434782608 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005434782608695652 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 8.5 | | std | 5.59 | | cv | 0.658 | | sampleLengths | | 0 | 7 | | 1 | 20 | | 2 | 11 | | 3 | 6 | | 4 | 5 | | 5 | 15 | | 6 | 11 | | 7 | 7 | | 8 | 3 | | 9 | 9 | | 10 | 19 | | 11 | 16 | | 12 | 11 | | 13 | 9 | | 14 | 16 | | 15 | 29 | | 16 | 3 | | 17 | 2 | | 18 | 11 | | 19 | 2 | | 20 | 13 | | 21 | 6 | | 22 | 4 | | 23 | 19 | | 24 | 4 | | 25 | 11 | | 26 | 8 | | 27 | 8 | | 28 | 2 | | 29 | 8 | | 30 | 10 | | 31 | 6 | | 32 | 15 | | 33 | 6 | | 34 | 4 | | 35 | 10 | | 36 | 3 | | 37 | 4 | | 38 | 4 | | 39 | 7 | | 40 | 15 | | 41 | 18 | | 42 | 8 | | 43 | 28 | | 44 | 2 | | 45 | 3 | | 46 | 11 | | 47 | 19 | | 48 | 2 | | 49 | 2 |
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| 36.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.29914529914529914 | | totalSentences | 117 | | uniqueOpeners | 35 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 85 | | matches | | 0 | "She stared at the fine" | | 1 | "She brushed dust from the" | | 2 | "She swept the lamp in" | | 3 | "It pointed toward the nearest" | | 4 | "She had eighteen years of" | | 5 | "She had lost DS Morris" | | 6 | "She suspected the clique was" | | 7 | "She traced a faint line" | | 8 | "She snapped a photo of" | | 9 | "She set her boot on" | | 10 | "She reached for the knife." | | 11 | "She turned it over." | | 12 | "Her nervous habit of tucking" | | 13 | "She did not fire." |
| | ratio | 0.165 | |
| 1.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 85 | | matches | | 0 | "The bone token shattered under" | | 1 | "She stared at the fine" | | 2 | "The face etched with protective" | | 3 | "Verdigris patina clung to the" | | 4 | "The needle did not settle." | | 5 | "Eva Kowalski tucked a curly" | | 6 | "The worn leather satchel full" | | 7 | "Quinn's jaw tightened." | | 8 | "The closely cropped salt-and-pepper hair" | | 9 | "The worn leather watch on" | | 10 | "Military precision kept her shoulders" | | 11 | "Eva crouched beside a toppled" | | 12 | "The Market had left a" | | 13 | "A neat circle of chalk," | | 14 | "The bone token entry requirement" | | 15 | "She brushed dust from the" | | 16 | "Eva lifted a small glass" | | 17 | "The liquid inside had evaporated" | | 18 | "She swept the lamp in" | | 19 | "The station's arched ceiling loomed," |
| | ratio | 0.918 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 1 | | matches | | 0 | "A neat circle of chalk, a little old rectangular green French silver whittling knife lying point first in the centre, a single shallow footprint in dust that le…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 38 | | tagDensity | 0.132 | | leniency | 0.263 | | rawRatio | 0.2 | | effectiveRatio | 0.053 | |