| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 58 | | tagDensity | 0.31 | | leniency | 0.621 | | rawRatio | 0.056 | | effectiveRatio | 0.034 | |
| 66.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1195 | | totalAiIsmAdverbs | 8 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | adverb | "reluctantly" | | count | 1 |
| | 5 | | | 6 | | | 7 | |
| | highlights | | 0 | "sharply" | | 1 | "lightly" | | 2 | "cautiously" | | 3 | "softly" | | 4 | "reluctantly" | | 5 | "quickly" | | 6 | "gently" | | 7 | "tightly" |
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| 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) | |
| 24.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1195 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "echoing" | | 1 | "gleaming" | | 2 | "pulse" | | 3 | "eyebrow" | | 4 | "pounding" | | 5 | "scanned" | | 6 | "intensity" | | 7 | "unreadable" | | 8 | "stomach" | | 9 | "racing" | | 10 | "flicker" | | 11 | "silence" | | 12 | "warmth" | | 13 | "weight" | | 14 | "reminder" | | 15 | "navigate" |
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| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
| | 2 | | label | "sent a shiver through" | | count | 1 |
| | 3 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "stomach dropped" | | 1 | "fists clenched" | | 2 | "sent a jolt through" | | 3 | "a flicker of hope" |
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| 92.95% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 78 | | matches | | 0 | "g with anger" | | 1 | "a flicker of guilt" | | 2 | "a flicker of hope" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1186 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 817 | | uniqueNames | 4 | | maxNameDensity | 0.49 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 4 | | Moreau | 1 | | French | 1 | | Lucien | 3 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Lucien" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like coming home, like finding a p" |
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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 | 1186 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 118 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 23.25 | | std | 15.12 | | cv | 0.65 | | sampleLengths | | 0 | 68 | | 1 | 60 | | 2 | 27 | | 3 | 21 | | 4 | 20 | | 5 | 17 | | 6 | 13 | | 7 | 57 | | 8 | 9 | | 9 | 60 | | 10 | 6 | | 11 | 14 | | 12 | 15 | | 13 | 21 | | 14 | 17 | | 15 | 15 | | 16 | 18 | | 17 | 53 | | 18 | 23 | | 19 | 9 | | 20 | 12 | | 21 | 31 | | 22 | 10 | | 23 | 14 | | 24 | 19 | | 25 | 24 | | 26 | 12 | | 27 | 23 | | 28 | 16 | | 29 | 24 | | 30 | 31 | | 31 | 15 | | 32 | 12 | | 33 | 13 | | 34 | 14 | | 35 | 22 | | 36 | 32 | | 37 | 15 | | 38 | 18 | | 39 | 27 | | 40 | 37 | | 41 | 10 | | 42 | 23 | | 43 | 35 | | 44 | 13 | | 45 | 15 | | 46 | 11 | | 47 | 59 | | 48 | 14 | | 49 | 9 |
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| 96.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 78 | | matches | | |
| 82.35% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 170 | | matches | | 0 | "was holding" | | 1 | "was watching" | | 2 | "was, standing" |
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| 70.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 118 | | ratio | 0.025 | | matches | | 0 | "Three sharp raps followed—firm, deliberate, unmistakable." | | 1 | "His heterochromatic eyes—one amber, one black—were fixed on the door, as if he already knew she was watching." | | 2 | "Her breath caught as she read it—government letterhead, a list of names, hers circled in red ink." |
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| 97.74% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 822 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.04257907542579075 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.0170316301703163 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 10.05 | | std | 5.94 | | cv | 0.591 | | sampleLengths | | 0 | 16 | | 1 | 9 | | 2 | 13 | | 3 | 6 | | 4 | 3 | | 5 | 7 | | 6 | 14 | | 7 | 9 | | 8 | 25 | | 9 | 18 | | 10 | 8 | | 11 | 24 | | 12 | 3 | | 13 | 16 | | 14 | 5 | | 15 | 11 | | 16 | 9 | | 17 | 9 | | 18 | 8 | | 19 | 9 | | 20 | 4 | | 21 | 6 | | 22 | 28 | | 23 | 23 | | 24 | 5 | | 25 | 4 | | 26 | 15 | | 27 | 18 | | 28 | 9 | | 29 | 6 | | 30 | 12 | | 31 | 6 | | 32 | 7 | | 33 | 7 | | 34 | 9 | | 35 | 6 | | 36 | 15 | | 37 | 6 | | 38 | 8 | | 39 | 9 | | 40 | 10 | | 41 | 5 | | 42 | 9 | | 43 | 9 | | 44 | 7 | | 45 | 18 | | 46 | 13 | | 47 | 15 | | 48 | 17 | | 49 | 3 |
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| 60.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3813559322033898 | | totalSentences | 118 | | uniqueOpeners | 45 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Instead, he reached into his" |
| | ratio | 0.013 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 57 | | totalSentences | 76 | | matches | | 0 | "She froze, the sound echoing" | | 1 | "Her chest tightened." | | 2 | "She wiped her hands on" | | 3 | "She peeked through the peephole," | | 4 | "His heterochromatic eyes—one amber, one" | | 5 | "he said, his voice smooth" | | 6 | "She exhaled sharply and unlocked" | | 7 | "He raised an eyebrow, his" | | 8 | "she scoffed, her grip tightening" | | 9 | "His smile faded, replaced by" | | 10 | "She hesitated again, her heart" | | 11 | "She’d sworn she wouldn’t let" | | 12 | "she muttered, stepping aside" | | 13 | "He entered the flat with" | | 14 | "His eyes scanned the room," | | 15 | "she shot back, crossing her" | | 16 | "He tilted his head, studying" | | 17 | "She self-consciously tucked a strand" | | 18 | "He took a step closer," | | 19 | "she demanded, her voice sharper" |
| | ratio | 0.75 | |
| 6.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 76 | | matches | | 0 | "The knock on the door" | | 1 | "She froze, the sound echoing" | | 2 | "Ptolemy leaped off the counter," | | 3 | "Her chest tightened." | | 4 | "She wiped her hands on" | | 5 | "She peeked through the peephole," | | 6 | "Lucien Moreau stood in the" | | 7 | "His heterochromatic eyes—one amber, one" | | 8 | "Rory hesitated, her hand hovering" | | 9 | "he said, his voice smooth" | | 10 | "She exhaled sharply and unlocked" | | 11 | "He raised an eyebrow, his" | | 12 | "she scoffed, her grip tightening" | | 13 | "His smile faded, replaced by" | | 14 | "She hesitated again, her heart" | | 15 | "The last time they’d seen" | | 16 | "She’d sworn she wouldn’t let" | | 17 | "she muttered, stepping aside" | | 18 | "He entered the flat with" | | 19 | "His eyes scanned the room," |
| | ratio | 0.908 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "His heterochromatic eyes—one amber, one black—were fixed on the door, as if he already knew she was watching." | | 1 | "The cat sniffed it briefly before rubbing against his fingers, purring softly." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 11 | | matches | | 0 | "she scoffed, her grip tightening on the doorframe" | | 1 | "she demanded, her voice sharper than she intended" | | 2 | "he replied, his tone calm but firm" | | 3 | "she repeated, her voice trembling with anger" | | 4 | "he asked, his gaze piercing" | | 5 | "he interrupted, his voice firm" | | 6 | "she demanded, her voice rising" | | 7 | "he said, his voice softer now" | | 8 | "he said, his tone pleading" | | 9 | "she whispered, her voice breaking the silence" | | 10 | "he murmured, his forehead resting against hers" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 10 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Rory muttered (mutter)" | | 2 | "she demanded (demand)" | | 3 | "she repeated (repeat)" | | 4 | "he agreed (agree)" | | 5 | "he interrupted (interrupt)" | | 6 | "she spat (spit)" | | 7 | "she demanded (demand)" | | 8 | "she whispered (whisper)" | | 9 | "he murmured (murmur)" |
| | dialogueSentences | 58 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0.625 | | effectiveRatio | 0.345 | |