| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 2 | | adverbTags | | 0 | "Eva’s gaze snapped back [back]" | | 1 | "Eva said softly [softly]" |
| | dialogueSentences | 67 | | tagDensity | 0.09 | | leniency | 0.179 | | rawRatio | 0.333 | | effectiveRatio | 0.06 | |
| 83.22% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1490 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "really" | | 3 | "suddenly" |
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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) | |
| 26.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1490 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "tracing" | | 1 | "familiar" | | 2 | "rhythmic" | | 3 | "marble" | | 4 | "chaotic" | | 5 | "scanned" | | 6 | "silence" | | 7 | "comfortable" | | 8 | "traced" | | 9 | "reminder" | | 10 | "weight" | | 11 | "calculated" | | 12 | "crystal" | | 13 | "dance" | | 14 | "measured" | | 15 | "flicker" | | 16 | "searing" | | 17 | "flickered" | | 18 | "glistening" | | 19 | "thundered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1488 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 828 | | uniqueNames | 8 | | maxNameDensity | 1.93 | | worstName | "Eva" | | maxWindowNameDensity | 4 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 15 | | Soho | 1 | | Eva | 16 | | Paris | 1 | | Raven | 1 | | Nest | 1 | | Bodleian | 1 | | Welsh | 1 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Paris" | | 2 | "Bodleian" | | 3 | "Welsh" |
| | globalScore | 0.534 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a physical blow" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1488 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 88 | | mean | 16.91 | | std | 14.19 | | cv | 0.839 | | sampleLengths | | 0 | 22 | | 1 | 28 | | 2 | 3 | | 3 | 58 | | 4 | 1 | | 5 | 28 | | 6 | 62 | | 7 | 1 | | 8 | 15 | | 9 | 12 | | 10 | 3 | | 11 | 2 | | 12 | 4 | | 13 | 35 | | 14 | 10 | | 15 | 7 | | 16 | 47 | | 17 | 6 | | 18 | 15 | | 19 | 13 | | 20 | 36 | | 21 | 8 | | 22 | 34 | | 23 | 14 | | 24 | 14 | | 25 | 4 | | 26 | 1 | | 27 | 16 | | 28 | 10 | | 29 | 7 | | 30 | 13 | | 31 | 33 | | 32 | 29 | | 33 | 17 | | 34 | 11 | | 35 | 22 | | 36 | 4 | | 37 | 18 | | 38 | 16 | | 39 | 5 | | 40 | 6 | | 41 | 23 | | 42 | 19 | | 43 | 22 | | 44 | 6 | | 45 | 3 | | 46 | 8 | | 47 | 67 | | 48 | 4 | | 49 | 2 |
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| 92.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 80 | | matches | | 0 | "was gone" | | 1 | "was pulled" | | 2 | "was torn" |
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| 57.14% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 140 | | matches | | 0 | "was auditing" | | 1 | "wasn't just looking" | | 2 | "was spreading" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 141 | | ratio | 0.014 | | matches | | 0 | "Eva wasn't just looking at her; she was auditing her." | | 1 | "A flicker of something—longing, perhaps, or pure, unadulterated exhaustion—passed over her features." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 833 | | adjectiveStacks | 2 | | stackExamples | | 0 | "grainier, rougher under her" | | 1 | "small, crescent-shaped scar" |
| | adverbCount | 21 | | adverbRatio | 0.025210084033613446 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008403361344537815 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 10.55 | | std | 7.16 | | cv | 0.679 | | sampleLengths | | 0 | 3 | | 1 | 19 | | 2 | 5 | | 3 | 23 | | 4 | 3 | | 5 | 22 | | 6 | 2 | | 7 | 15 | | 8 | 5 | | 9 | 2 | | 10 | 12 | | 11 | 1 | | 12 | 2 | | 13 | 26 | | 14 | 3 | | 15 | 9 | | 16 | 16 | | 17 | 19 | | 18 | 15 | | 19 | 1 | | 20 | 7 | | 21 | 8 | | 22 | 12 | | 23 | 3 | | 24 | 2 | | 25 | 4 | | 26 | 12 | | 27 | 23 | | 28 | 10 | | 29 | 7 | | 30 | 17 | | 31 | 27 | | 32 | 3 | | 33 | 6 | | 34 | 15 | | 35 | 13 | | 36 | 8 | | 37 | 16 | | 38 | 12 | | 39 | 8 | | 40 | 10 | | 41 | 24 | | 42 | 14 | | 43 | 9 | | 44 | 5 | | 45 | 4 | | 46 | 1 | | 47 | 4 | | 48 | 12 | | 49 | 10 |
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| 38.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.28368794326241137 | | totalSentences | 141 | | uniqueOpeners | 40 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Suddenly, the heavy door creaked" |
| | ratio | 0.013 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 75 | | matches | | 0 | "It didn't shatter, but the" | | 1 | "She stared at the puddle." | | 2 | "Her heart hammered against her" | | 3 | "She didn't turn around immediately." | | 4 | "She waited for the sensation" | | 5 | "It was Eva." | | 6 | "Her blonde hair, once a" | | 7 | "She scanned the room, her" | | 8 | "She looked at the faded" | | 9 | "It wasn't the comfortable silence" | | 10 | "They remained hard, polished stones." | | 11 | "She didn't drink." | | 12 | "She merely held it, watching" | | 13 | "She closed her eyes for" | | 14 | "She took a swallow." | | 15 | "She smoothed her coat, the" | | 16 | "She didn't wait for an" | | 17 | "She walked towards the door," | | 18 | "She watched the heavy oak" | | 19 | "It wasn't the smooth, confident" |
| | ratio | 0.333 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 75 | | matches | | 0 | "The glass slipped." | | 1 | "It didn't shatter, but the" | | 2 | "She stared at the puddle." | | 3 | "A single bead of whiskey" | | 4 | "The voice cut through the" | | 5 | "Her heart hammered against her" | | 6 | "She didn't turn around immediately." | | 7 | "She waited for the sensation" | | 8 | "The neon green glow from" | | 9 | "It was Eva." | | 10 | "The girl who had once" | | 11 | "Her blonde hair, once a" | | 12 | "Rory gripped the edge of" | | 13 | "The wood felt grainier, rougher" | | 14 | "Eva leaned against the bar," | | 15 | "She scanned the room, her" | | 16 | "Eva’s gaze snapped back to" | | 17 | "She looked at the faded" | | 18 | "A silence stretched between them," | | 19 | "It wasn't the comfortable silence" |
| | ratio | 0.933 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 75 | | matches | | 0 | "Before Rory could speak, the" |
| | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "She scanned the room, her eyes lingering on the faded maps and the dusty black-and-white photographs lining the walls of The Raven's Nest." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva said, her voice dropping an octave" | | 1 | "he wheezed, a spray of red flecking his lips" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Eva’s gaze snapped back (snap)" | | 1 | "he wheezed (wheeze)" |
| | dialogueSentences | 67 | | tagDensity | 0.06 | | leniency | 0.119 | | rawRatio | 0.5 | | effectiveRatio | 0.06 | |