| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "the doorman said quietly [quietly]" |
| | dialogueSentences | 9 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.25 | | effectiveRatio | 0.222 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 887 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 77.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 887 | | totalAiIsms | 4 | | found | | 0 | | | 1 | | | 2 | | word | "the last thing" | | count | 1 |
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| | highlights | | 0 | "throbbed" | | 1 | "pulse" | | 2 | "the last thing" |
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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 | 57 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 57 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 62 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 3 | | totalWords | 887 | | ratio | 0.003 | | matches | | 0 | "Camden" | | 1 | "unexplained" | | 2 | "inconclusive" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 828 | | uniqueNames | 13 | | maxNameDensity | 0.72 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 6 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Herrera | 1 | | Raven | 1 | | Nest | 1 | | Dean | 1 | | Street | 1 | | Camden | 2 | | Tube | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Morris" |
| | places | | 0 | "Chalk" | | 1 | "Farm" | | 2 | "Road" | | 3 | "Dean" | | 4 | "Street" | | 5 | "Camden" |
| | globalScore | 1 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | 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 | 887 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 42.24 | | std | 25.63 | | cv | 0.607 | | sampleLengths | | 0 | 76 | | 1 | 65 | | 2 | 20 | | 3 | 54 | | 4 | 73 | | 5 | 64 | | 6 | 5 | | 7 | 57 | | 8 | 40 | | 9 | 56 | | 10 | 53 | | 11 | 7 | | 12 | 16 | | 13 | 61 | | 14 | 8 | | 15 | 3 | | 16 | 52 | | 17 | 87 | | 18 | 24 | | 19 | 16 | | 20 | 50 |
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| 74.48% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 57 | | matches | | 0 | "been painted" | | 1 | "been pried" | | 2 | "was gone" | | 3 | "been carved" | | 4 | "been locked" |
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| 98.22% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 131 | | matches | | 0 | "was calling" | | 1 | "was crying" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 62 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 829 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.033775633293124246 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0024125452352231603 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 62 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 62 | | mean | 14.31 | | std | 9.19 | | cv | 0.642 | | sampleLengths | | 0 | 24 | | 1 | 33 | | 2 | 14 | | 3 | 1 | | 4 | 4 | | 5 | 21 | | 6 | 32 | | 7 | 12 | | 8 | 16 | | 9 | 4 | | 10 | 3 | | 11 | 19 | | 12 | 21 | | 13 | 6 | | 14 | 5 | | 15 | 26 | | 16 | 8 | | 17 | 23 | | 18 | 16 | | 19 | 22 | | 20 | 16 | | 21 | 12 | | 22 | 14 | | 23 | 5 | | 24 | 7 | | 25 | 5 | | 26 | 11 | | 27 | 34 | | 28 | 13 | | 29 | 9 | | 30 | 18 | | 31 | 28 | | 32 | 6 | | 33 | 22 | | 34 | 14 | | 35 | 16 | | 36 | 23 | | 37 | 7 | | 38 | 6 | | 39 | 10 | | 40 | 24 | | 41 | 30 | | 42 | 7 | | 43 | 8 | | 44 | 3 | | 45 | 4 | | 46 | 30 | | 47 | 8 | | 48 | 6 | | 49 | 4 |
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| 77.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5161290322580645 | | totalSentences | 62 | | uniqueOpeners | 32 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 55 | | matches | | 0 | "Somewhere beyond the arch, water" | | 1 | "Somewhere inside, a woman was" | | 2 | "Somewhere else, a child was" | | 3 | "Then she stepped past him" |
| | ratio | 0.073 | |
| 96.36% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 55 | | matches | | 0 | "Her eyes stayed on the" | | 1 | "She had watched him leave" | | 2 | "She had watched him stop" | | 3 | "she shouted, and her voice" | | 4 | "He didn't look back." | | 5 | "Her left wrist throbbed where" | | 6 | "Her knees said she was" | | 7 | "Her lungs argued the point." | | 8 | "He cut left across the" | | 9 | "She came through the gap" | | 10 | "She drew a breath, reached" | | 11 | "She keyed it anyway, said" | | 12 | "He was tall, older than" | | 13 | "He tipped his head toward" | | 14 | "She thought of Morris." | | 15 | "She had told him he" | | 16 | "She had been wrong about" |
| | ratio | 0.309 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 55 | | matches | | 0 | "The rain had found its" | | 1 | "Her eyes stayed on the" | | 2 | "Tomás Herrera ran like a" | | 3 | "She had watched him leave" | | 4 | "She had watched him stop" | | 5 | "The second was when he" | | 6 | "she shouted, and her voice" | | 7 | "He didn't look back." | | 8 | "Quinn pushed harder." | | 9 | "Her left wrist throbbed where" | | 10 | "Her knees said she was" | | 11 | "Her lungs argued the point." | | 12 | "He cut left across the" | | 13 | "She came through the gap" | | 14 | "Water pooled in the cracks" | | 15 | "The sign above the doors" | | 16 | "Someone had nailed a sheet" | | 17 | "The iron had been pried" | | 18 | "Tomás was already through it." | | 19 | "Quinn stopped at the threshold" |
| | ratio | 0.691 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 55 | | matches | (empty) | | ratio | 0 | |
| 8.93% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 6 | | matches | | 0 | "Tomás Herrera ran like a man who had once carried stretchers for a living." | | 1 | "Inside, a flight of stairs led down into a darkness that smelled of wet brick and something sweeter underneath, like incense left too long in a closed room." | | 2 | "Hanging from a leather cord around his neck was a small pale token, carved from something that gleamed like ivory under the lanterns." | | 3 | "Beyond the arch she could make out the shapes of stalls, canvas awnings, figures moving between them with the unhurried purpose of people who did not expect to …" | | 4 | "Of the last thing he'd said to her before the call came in, something about a witness who had been dead for six days and still answering his door." | | 5 | "Quinn unbuttoned her wet coat, letting it fall open so he could see the holster at her hip, a gesture that meant nothing to him and everything to her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 9 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.333 | | effectiveRatio | 0.222 | |