| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.17 | | leniency | 0.34 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 75.92% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1038 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "really" | | 1 | "very" | | 2 | "slightly" |
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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) | |
| 71.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1038 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "silence" | | 1 | "traced" | | 2 | "weight" | | 3 | "flicked" | | 4 | "flickered" | | 5 | "warmth" |
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| 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 | 0 | | narrationSentences | 39 | | matches | (empty) | |
| 69.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 39 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1038 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 7 | | wordCount | 688 | | uniqueNames | 4 | | maxNameDensity | 0.44 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 3 | | Aurora | 1 | | Ptolemy | 2 | | English | 1 |
| | persons | | 0 | "Rory" | | 1 | "Aurora" | | 2 | "Ptolemy" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 29 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite an invitation, more a lack of objection, and he took it as permission because he always did" | | 1 | "quite human, wasn't quite anything nameable" | | 2 | "quite anything nameable" |
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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 | 1038 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 83 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 16.48 | | std | 18.95 | | cv | 1.15 | | sampleLengths | | 0 | 12 | | 1 | 46 | | 2 | 5 | | 3 | 5 | | 4 | 6 | | 5 | 57 | | 6 | 2 | | 7 | 3 | | 8 | 4 | | 9 | 8 | | 10 | 57 | | 11 | 4 | | 12 | 2 | | 13 | 1 | | 14 | 37 | | 15 | 61 | | 16 | 5 | | 17 | 3 | | 18 | 7 | | 19 | 66 | | 20 | 17 | | 21 | 2 | | 22 | 12 | | 23 | 13 | | 24 | 4 | | 25 | 44 | | 26 | 18 | | 27 | 4 | | 28 | 4 | | 29 | 34 | | 30 | 5 | | 31 | 4 | | 32 | 4 | | 33 | 3 | | 34 | 29 | | 35 | 15 | | 36 | 5 | | 37 | 25 | | 38 | 37 | | 39 | 1 | | 40 | 13 | | 41 | 17 | | 42 | 6 | | 43 | 2 | | 44 | 6 | | 45 | 50 | | 46 | 3 | | 47 | 2 | | 48 | 7 | | 49 | 9 |
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| 96.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 39 | | matches | | |
| 88.89% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 120 | | matches | | 0 | "was doing" | | 1 | "was already being" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 83 | | ratio | 0 | | matches | (empty) | |
| 86.74% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.055152394775036286 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01451378809869376 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 12.51 | | std | 11.09 | | cv | 0.887 | | sampleLengths | | 0 | 7 | | 1 | 3 | | 2 | 2 | | 3 | 18 | | 4 | 22 | | 5 | 6 | | 6 | 5 | | 7 | 5 | | 8 | 6 | | 9 | 9 | | 10 | 24 | | 11 | 24 | | 12 | 2 | | 13 | 3 | | 14 | 4 | | 15 | 8 | | 16 | 28 | | 17 | 16 | | 18 | 9 | | 19 | 4 | | 20 | 4 | | 21 | 2 | | 22 | 1 | | 23 | 24 | | 24 | 13 | | 25 | 25 | | 26 | 36 | | 27 | 5 | | 28 | 3 | | 29 | 7 | | 30 | 33 | | 31 | 33 | | 32 | 17 | | 33 | 2 | | 34 | 12 | | 35 | 13 | | 36 | 4 | | 37 | 44 | | 38 | 8 | | 39 | 10 | | 40 | 4 | | 41 | 4 | | 42 | 20 | | 43 | 3 | | 44 | 11 | | 45 | 5 | | 46 | 4 | | 47 | 4 | | 48 | 3 | | 49 | 29 |
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| 81.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5060240963855421 | | totalSentences | 83 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 33 | | matches | | 0 | "Then the sound came, distant" |
| | ratio | 0.03 | |
| 13.94% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 33 | | matches | | 0 | "She opened the door anyway." | | 1 | "He knew what he was" | | 2 | "His charcoal suit had a" | | 3 | "He didn't move to come" | | 4 | "He exhaled through his nose," | | 5 | "She stepped back from the" | | 6 | "He limped past her into" | | 7 | "He lowered himself onto her" | | 8 | "He looked at her then," | | 9 | "She crossed her arms, leaned" | | 10 | "He set the cane aside," | | 11 | "She crossed the room before" | | 12 | "He went very still under" | | 13 | "Her fingers stopped at his" | | 14 | "His good eye held hers," | | 15 | "she stopped, searched for the" | | 16 | "he said, already reaching for" |
| | ratio | 0.515 | |
| 5.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 30 | | totalSentences | 33 | | matches | | 0 | "The knock came in a" | | 1 | "Rory froze with her hand" | | 2 | "Ptolemy yowled from his perch" | | 3 | "Cats didn't hide from delivery" | | 4 | "She opened the door anyway." | | 5 | "The name landed like a" | | 6 | "He knew what he was" | | 7 | "His charcoal suit had a" | | 8 | "He didn't move to come" | | 9 | "The ivory handle had a" | | 10 | "Something had tried to take" | | 11 | "Something had nearly succeeded." | | 12 | "He exhaled through his nose," | | 13 | "She stepped back from the" | | 14 | "He limped past her into" | | 15 | "He lowered himself onto her" | | 16 | "Rory crossed to the kitchenette," | | 17 | "He looked at her then," | | 18 | "She crossed her arms, leaned" | | 19 | "The books stacked along the" |
| | ratio | 0.909 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 6.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 4 | | matches | | 0 | "He limped past her into the flat, and the scent of him arrived a half-second later, bergamot and something underneath it that reminded her of matchstick heads, …" | | 1 | "He went very still under her fingers, the kind of stillness that took effort." | | 2 | "Her fingers stopped at his jaw, close enough to feel the warmth radiating off skin that wasn't quite human, wasn't quite anything nameable." | | 3 | "The honesty of it landed harder than any deflection could have, and for a moment neither of them moved, her hand still at his jaw, his gaze fixed on her like sh…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.113 | | leniency | 0.226 | | rawRatio | 0 | | effectiveRatio | 0 | |