| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 70 | | tagDensity | 0.243 | | leniency | 0.486 | | rawRatio | 0.059 | | effectiveRatio | 0.029 | |
| 79.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1454 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "very" | | 3 | "slowly" | | 4 | "softly" |
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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) | |
| 41.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1454 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "scanned" | | 3 | "familiar" | | 4 | "methodical" | | 5 | "glinting" | | 6 | "silence" | | 7 | "could feel" | | 8 | "jaw clenched" | | 9 | "predator" | | 10 | "stomach" | | 11 | "pristine" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 124 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 124 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 178 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1447 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 933 | | uniqueNames | 8 | | maxNameDensity | 1.07 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Evan | 1 | | Cardiff | 1 | | Rory | 7 | | Silas | 10 | | Europe | 1 | | Prague | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Evan" | | 3 | "Rory" | | 4 | "Silas" |
| | places | | 0 | "Cardiff" | | 1 | "Europe" | | 2 | "Prague" |
| | globalScore | 0.964 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.691 | | wordCount | 1447 | | matches | | 0 | "not with anger, but something colder" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 178 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 85 | | mean | 17.02 | | std | 15.98 | | cv | 0.938 | | sampleLengths | | 0 | 71 | | 1 | 48 | | 2 | 34 | | 3 | 2 | | 4 | 63 | | 5 | 8 | | 6 | 6 | | 7 | 26 | | 8 | 3 | | 9 | 27 | | 10 | 1 | | 11 | 63 | | 12 | 12 | | 13 | 7 | | 14 | 11 | | 15 | 15 | | 16 | 6 | | 17 | 19 | | 18 | 37 | | 19 | 7 | | 20 | 33 | | 21 | 4 | | 22 | 16 | | 23 | 13 | | 24 | 4 | | 25 | 10 | | 26 | 12 | | 27 | 38 | | 28 | 12 | | 29 | 9 | | 30 | 2 | | 31 | 25 | | 32 | 2 | | 33 | 11 | | 34 | 21 | | 35 | 36 | | 36 | 5 | | 37 | 49 | | 38 | 17 | | 39 | 33 | | 40 | 5 | | 41 | 6 | | 42 | 2 | | 43 | 29 | | 44 | 61 | | 45 | 15 | | 46 | 16 | | 47 | 2 | | 48 | 18 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 170 | | matches | (empty) | |
| 78.65% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 178 | | ratio | 0.022 | | matches | | 0 | "She didn’t drink much these days—not since Evan—but sometimes the weight of the hours between shifts pressed too hard." | | 1 | "She studied his hands—knuckles slightly crooked from old fights, nails trimmed short." | | 2 | "He paused at the bookshelf behind the corner booth—always the third from the left, the one with the chipped spine." | | 3 | "But she could see the weight in it—the unwritten rules, the silence expected." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 588 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.03231292517006803 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.006802721088435374 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 178 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 178 | | mean | 8.13 | | std | 6.11 | | cv | 0.751 | | sampleLengths | | 0 | 18 | | 1 | 20 | | 2 | 14 | | 3 | 19 | | 4 | 33 | | 5 | 5 | | 6 | 10 | | 7 | 17 | | 8 | 13 | | 9 | 4 | | 10 | 2 | | 11 | 5 | | 12 | 15 | | 13 | 3 | | 14 | 10 | | 15 | 6 | | 16 | 22 | | 17 | 2 | | 18 | 8 | | 19 | 6 | | 20 | 12 | | 21 | 8 | | 22 | 3 | | 23 | 1 | | 24 | 2 | | 25 | 3 | | 26 | 5 | | 27 | 2 | | 28 | 6 | | 29 | 7 | | 30 | 7 | | 31 | 1 | | 32 | 16 | | 33 | 10 | | 34 | 15 | | 35 | 22 | | 36 | 9 | | 37 | 3 | | 38 | 6 | | 39 | 1 | | 40 | 4 | | 41 | 7 | | 42 | 9 | | 43 | 6 | | 44 | 6 | | 45 | 5 | | 46 | 8 | | 47 | 6 | | 48 | 12 | | 49 | 3 |
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| 54.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3539325842696629 | | totalSentences | 178 | | uniqueOpeners | 63 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 107 | | matches | | 0 | "Just a quiet acknowledgment of" | | 1 | "Then the stool beside her" | | 2 | "Just nodded once, then stepped" | | 3 | "Then she closed the door." |
| | ratio | 0.037 | |
| 36.82% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 107 | | matches | | 0 | "She didn’t drink much these" | | 1 | "She scanned the room, eyes" | | 2 | "She should’ve known he wouldn’t" | | 3 | "He poured without another word." | | 4 | "She took the glass, the" | | 5 | "She didn’t look." | | 6 | "She exhaled through her nose." | | 7 | "She set the glass down" | | 8 | "His auburn hair was more" | | 9 | "He wore a black T-shirt" | | 10 | "She let her gaze flick" | | 11 | "She laughed despite herself." | | 12 | "He leaned back, one arm" | | 13 | "She studied his hands—knuckles slightly" | | 14 | "He’d retired from MI6 by" | | 15 | "He nodded toward the door." | | 16 | "He tilted his head" | | 17 | "She could feel the old" | | 18 | "She took a slow sip." | | 19 | "Her jaw clenched." |
| | ratio | 0.458 | |
| 48.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 107 | | matches | | 0 | "The Raven's Nest hummed with" | | 1 | "Rory pushed through the door," | | 2 | "The green neon sign above" | | 3 | "She didn’t drink much these" | | 4 | "She scanned the room, eyes" | | 5 | "Silas wasn’t behind the counter." | | 6 | "She should’ve known he wouldn’t" | | 7 | "Rory slid onto a stool" | | 8 | "The bartender, a young guy" | | 9 | "He poured without another word." | | 10 | "She took the glass, the" | | 11 | "The drink burned going down," | | 12 | "A familiar weight settled, the" | | 13 | "The air between them thickened" | | 14 | "She didn’t look." | | 15 | "She exhaled through her nose." | | 16 | "Time had carved new lines" | | 17 | "She set the glass down" | | 18 | "His auburn hair was more" | | 19 | "The hazel eyes still sharp," |
| | ratio | 0.822 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 107 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "She rubbed, the faint scar still there, pale against her skin" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 70 | | tagDensity | 0.086 | | leniency | 0.171 | | rawRatio | 0 | | effectiveRatio | 0 | |