| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said softly [softly]" |
| | dialogueSentences | 52 | | tagDensity | 0.212 | | leniency | 0.423 | | rawRatio | 0.091 | | effectiveRatio | 0.038 | |
| 88.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 893 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 38.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 893 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "echoed" | | 1 | "stomach" | | 2 | "racing" | | 3 | "scanning" | | 4 | "unreadable" | | 5 | "intensity" | | 6 | "warmth" | | 7 | "silence" | | 8 | "furrowing" | | 9 | "tracing" | | 10 | "pounding" |
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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 | 52 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 52 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 890 | | 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 | 10 | | wordCount | 570 | | uniqueNames | 5 | | maxNameDensity | 0.53 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 2 | | Eva | 1 | | French | 1 | | Lucien | 3 | | Ptolemy | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Ptolemy" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 90.48% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 890 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 93 | | matches | | 0 | "recognize that platinum" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 17.12 | | std | 16.72 | | cv | 0.977 | | sampleLengths | | 0 | 77 | | 1 | 38 | | 2 | 23 | | 3 | 13 | | 4 | 2 | | 5 | 10 | | 6 | 11 | | 7 | 6 | | 8 | 6 | | 9 | 59 | | 10 | 59 | | 11 | 7 | | 12 | 5 | | 13 | 20 | | 14 | 51 | | 15 | 20 | | 16 | 16 | | 17 | 15 | | 18 | 9 | | 19 | 6 | | 20 | 2 | | 21 | 1 | | 22 | 9 | | 23 | 3 | | 24 | 3 | | 25 | 24 | | 26 | 7 | | 27 | 18 | | 28 | 4 | | 29 | 2 | | 30 | 2 | | 31 | 9 | | 32 | 26 | | 33 | 6 | | 34 | 7 | | 35 | 7 | | 36 | 41 | | 37 | 13 | | 38 | 3 | | 39 | 5 | | 40 | 20 | | 41 | 40 | | 42 | 10 | | 43 | 29 | | 44 | 26 | | 45 | 15 | | 46 | 8 | | 47 | 42 | | 48 | 6 | | 49 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 52 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 105 | | matches | | |
| 81.41% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 93 | | ratio | 0.022 | | matches | | 0 | "It was sharp, deliberate—three raps that echoed through the flat." | | 1 | "He looked the same—tailored charcoal suit, crisp white shirt, the faint scent of bergamot and something darker beneath it." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 573 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.031413612565445025 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.008726003490401396 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 9.57 | | std | 6.35 | | cv | 0.664 | | sampleLengths | | 0 | 18 | | 1 | 10 | | 2 | 9 | | 3 | 8 | | 4 | 5 | | 5 | 27 | | 6 | 17 | | 7 | 17 | | 8 | 3 | | 9 | 1 | | 10 | 19 | | 11 | 4 | | 12 | 8 | | 13 | 5 | | 14 | 2 | | 15 | 3 | | 16 | 7 | | 17 | 11 | | 18 | 6 | | 19 | 6 | | 20 | 8 | | 21 | 10 | | 22 | 15 | | 23 | 26 | | 24 | 11 | | 25 | 18 | | 26 | 19 | | 27 | 11 | | 28 | 7 | | 29 | 5 | | 30 | 14 | | 31 | 6 | | 32 | 12 | | 33 | 11 | | 34 | 19 | | 35 | 9 | | 36 | 20 | | 37 | 16 | | 38 | 12 | | 39 | 3 | | 40 | 9 | | 41 | 6 | | 42 | 2 | | 43 | 1 | | 44 | 5 | | 45 | 4 | | 46 | 3 | | 47 | 3 | | 48 | 10 | | 49 | 14 |
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| 69.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.45161290322580644 | | totalSentences | 93 | | uniqueOpeners | 42 | |
| 65.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 51 | | matches | | 0 | "Instead, she leaned into his" |
| | ratio | 0.02 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 51 | | matches | | 0 | "It was sharp, deliberate—three raps" | | 1 | "She set the cup down" | | 2 | "Her stomach twisted." | | 3 | "he said, his voice low" | | 4 | "She hesitated, her hand hovering" | | 5 | "Her jaw tightened." | | 6 | "She stared at the door," | | 7 | "It had been six months" | | 8 | "He looked the same—tailored charcoal" | | 9 | "He tilted his head, a" | | 10 | "She stepped aside, and he" | | 11 | "He surveyed the flat, his" | | 12 | "he said, pulling a scroll" | | 13 | "she countered, crossing her arms" | | 14 | "He set the scroll down" | | 15 | "She laughed, short and humorless." | | 16 | "He stepped closer, his cane" | | 17 | "He frowned, his brow furrowing." | | 18 | "She cut herself off, shaking" | | 19 | "She looked away, her fingers" |
| | ratio | 0.706 | |
| 28.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 51 | | matches | | 0 | "The knock came late, just" | | 1 | "It was sharp, deliberate—three raps" | | 2 | "Ptolemy leapt off the windowsill" | | 3 | "Rory froze, the teacup halfway" | | 4 | "She set the cup down" | | 5 | "The peephole offered a distorted" | | 6 | "Her stomach twisted." | | 7 | "he said, his voice low" | | 8 | "She hesitated, her hand hovering" | | 9 | "Her jaw tightened." | | 10 | "She stared at the door," | | 11 | "It had been six months" | | 12 | "Lucien stood in the hallway," | | 13 | "He looked the same—tailored charcoal" | | 14 | "He tilted his head, a" | | 15 | "She stepped aside, and he" | | 16 | "The faint warmth lingered as" | | 17 | "He surveyed the flat, his" | | 18 | "Ptolemy reappeared, weaving between Lucien’s" | | 19 | "he said, pulling a scroll" |
| | ratio | 0.863 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 51 | | matches | (empty) | | ratio | 0 | |
| 57.14% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 3 | | matches | | 0 | "It was sharp, deliberate—three raps that echoed through the flat." | | 1 | "Not Eva, who had a key and a habit of barging in unannounced, and certainly not the delivery guys from the restaurant, who usually buzzed from downstairs." | | 2 | "He kissed her then, his mouth crashing into hers with a hunger that left her breathless." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 4 | | matches | | 0 | "He closed, his hand rising to cup her cheek" | | 1 | "he murmured, his thumb brushing against her cheekbone" | | 2 | "he whispered, his lips hovering inches from hers" | | 3 | "he replied, his lips trailing down her neck" |
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| 92.31% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 3 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "he whispered (whisper)" | | 2 | "she gasped (gasp)" |
| | dialogueSentences | 52 | | tagDensity | 0.135 | | leniency | 0.269 | | rawRatio | 0.429 | | effectiveRatio | 0.115 | |