| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.284 | | leniency | 0.567 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1377 | | totalAiIsmAdverbs | 1 | | 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) | |
| 78.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1377 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "scanned" | | 1 | "etched" | | 2 | "could feel" | | 3 | "etching" | | 4 | "pristine" | | 5 | "echoed" |
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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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1377 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 888 | | uniqueNames | 5 | | maxNameDensity | 1.91 | | worstName | "Sinclair" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Sinclair" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Sinclair | 17 | | Quinn | 12 | | Knightsbridge | 1 |
| | persons | | | places | (empty) | | globalScore | 0.543 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a train that hadn't run in th" |
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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 | 1377 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 153 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 18.61 | | std | 16.1 | | cv | 0.865 | | sampleLengths | | 0 | 8 | | 1 | 37 | | 2 | 24 | | 3 | 55 | | 4 | 3 | | 5 | 43 | | 6 | 4 | | 7 | 17 | | 8 | 58 | | 9 | 4 | | 10 | 17 | | 11 | 2 | | 12 | 8 | | 13 | 45 | | 14 | 4 | | 15 | 23 | | 16 | 5 | | 17 | 15 | | 18 | 60 | | 19 | 40 | | 20 | 20 | | 21 | 35 | | 22 | 43 | | 23 | 6 | | 24 | 13 | | 25 | 11 | | 26 | 1 | | 27 | 27 | | 28 | 40 | | 29 | 12 | | 30 | 43 | | 31 | 3 | | 32 | 16 | | 33 | 8 | | 34 | 26 | | 35 | 10 | | 36 | 38 | | 37 | 20 | | 38 | 4 | | 39 | 1 | | 40 | 24 | | 41 | 5 | | 42 | 40 | | 43 | 6 | | 44 | 22 | | 45 | 2 | | 46 | 53 | | 47 | 1 | | 48 | 8 | | 49 | 4 |
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| 88.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 105 | | matches | | 0 | "been closed" | | 1 | "was etched" | | 2 | "been drawn" | | 3 | "been disturbed" | | 4 | "been pulled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 154 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 153 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 891 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.03928170594837262 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004489337822671156 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 9 | | std | 6.46 | | cv | 0.718 | | sampleLengths | | 0 | 8 | | 1 | 2 | | 2 | 2 | | 3 | 2 | | 4 | 31 | | 5 | 11 | | 6 | 13 | | 7 | 8 | | 8 | 9 | | 9 | 20 | | 10 | 7 | | 11 | 11 | | 12 | 3 | | 13 | 26 | | 14 | 17 | | 15 | 4 | | 16 | 12 | | 17 | 5 | | 18 | 4 | | 19 | 13 | | 20 | 3 | | 21 | 16 | | 22 | 5 | | 23 | 11 | | 24 | 6 | | 25 | 4 | | 26 | 14 | | 27 | 3 | | 28 | 2 | | 29 | 4 | | 30 | 4 | | 31 | 3 | | 32 | 5 | | 33 | 13 | | 34 | 2 | | 35 | 3 | | 36 | 2 | | 37 | 17 | | 38 | 4 | | 39 | 5 | | 40 | 18 | | 41 | 5 | | 42 | 15 | | 43 | 6 | | 44 | 17 | | 45 | 22 | | 46 | 15 | | 47 | 12 | | 48 | 13 | | 49 | 7 |
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| 72.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.46405228758169936 | | totalSentences | 153 | | uniqueOpeners | 71 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 90 | | matches | | 0 | "Just a man suspended in" | | 1 | "Instead, she walked back to" | | 2 | "Just a little." | | 3 | "Then the lights went out." |
| | ratio | 0.044 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 90 | | matches | | 0 | "Her boots crunched on broken" | | 1 | "She crouched and looked up." | | 2 | "She walked to the platform" | | 3 | "Her feet squelched in the" | | 4 | "She knelt and carefully extracted" | | 5 | "She tucked it into an" | | 6 | "She walked the perimeter again," | | 7 | "They looked older than the" | | 8 | "She was certain of it." | | 9 | "She turned to face Sinclair" | | 10 | "She swept her arm toward" | | 11 | "She didn't answer." | | 12 | "She'd missed something on first" | | 13 | "He joined her." | | 14 | "She pulled out her phone" | | 15 | "He'd worked with Quinn long" | | 16 | "She pulled it out." | | 17 | "She watched the needle tremble" |
| | ratio | 0.2 | |
| 65.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 90 | | matches | | 0 | "The body hung six feet" | | 1 | "DC Sinclair flipped open his" | | 2 | "Quinn ducked under the yellow" | | 3 | "Her boots crunched on broken" | | 4 | "The station had been closed" | | 5 | "Rust had eaten through the" | | 6 | "The departure board hung crooked," | | 7 | "Sinclair consulted his notes" | | 8 | "Quinn circled the body." | | 9 | "The man's face had settled" | | 10 | "She crouched and looked up." | | 11 | "The ceiling was fifteen feet" | | 12 | "Nothing to hang a man" | | 13 | "Quinn leaned closer." | | 14 | "The man's brogues were spotless." | | 15 | "The leather gleamed under the" | | 16 | "Quinn stood and scanned the" | | 17 | "The tunnel mouth gaped to" | | 18 | "Chip wrappers and lager cans" | | 19 | "She walked to the platform" |
| | ratio | 0.789 | |
| 55.56% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 90 | | matches | | 0 | "As if something had been" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "The fingers uncurled and curled again, and the dead man's mouth fell open, and from somewhere inside him came a voice that wasn't his." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.015 | | leniency | 0.03 | | rawRatio | 0 | | effectiveRatio | 0 | |