| 84.62% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 3 | | adverbTags | | 0 | "Crane stopped visibly [visibly]" | | 1 | "Quinn moved back [back]" | | 2 | "she said suddenly [suddenly]" |
| | dialogueSentences | 52 | | tagDensity | 0.269 | | leniency | 0.538 | | rawRatio | 0.214 | | effectiveRatio | 0.115 | |
| 77.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1346 | | totalAiIsmAdverbs | 6 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | | | 4 | |
| | highlights | | 0 | "slowly" | | 1 | "deliberately" | | 2 | "really" | | 3 | "very" | | 4 | "suddenly" |
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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) | |
| 51.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1346 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "flickered" | | 3 | "standard" | | 4 | "mechanical" | | 5 | "racing" | | 6 | "scanned" | | 7 | "constructed" | | 8 | "could feel" | | 9 | "silence" | | 10 | "chill" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1337 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 797 | | uniqueNames | 11 | | maxNameDensity | 1.63 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 13 | | Crane | 5 | | Morris | 3 | | London | 1 | | British | 1 | | Museum | 1 | | Martin | 1 | | Ashford | 1 | | Kowalski | 1 | | Aurora | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Crane" | | 3 | "Morris" | | 4 | "Martin" | | 5 | "Ashford" | | 6 | "Kowalski" | | 7 | "Aurora" |
| | places | | | globalScore | 0.684 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.748 | | wordCount | 1337 | | matches | | 0 | "not unusual for him apparently, but" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 23.88 | | std | 17.17 | | cv | 0.719 | | sampleLengths | | 0 | 56 | | 1 | 23 | | 2 | 20 | | 3 | 8 | | 4 | 44 | | 5 | 3 | | 6 | 16 | | 7 | 52 | | 8 | 2 | | 9 | 13 | | 10 | 28 | | 11 | 1 | | 12 | 13 | | 13 | 39 | | 14 | 25 | | 15 | 3 | | 16 | 21 | | 17 | 48 | | 18 | 6 | | 19 | 3 | | 20 | 6 | | 21 | 9 | | 22 | 41 | | 23 | 1 | | 24 | 9 | | 25 | 6 | | 26 | 27 | | 27 | 20 | | 28 | 10 | | 29 | 35 | | 30 | 22 | | 31 | 4 | | 32 | 54 | | 33 | 3 | | 34 | 36 | | 35 | 39 | | 36 | 11 | | 37 | 24 | | 38 | 55 | | 39 | 13 | | 40 | 41 | | 41 | 4 | | 42 | 66 | | 43 | 35 | | 44 | 47 | | 45 | 25 | | 46 | 45 | | 47 | 18 | | 48 | 18 | | 49 | 14 |
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| 95.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 75 | | matches | | 0 | "been transferred" | | 1 | "were positioned" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 148 | | matches | (empty) | |
| 16.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 113 | | ratio | 0.044 | | matches | | 0 | "The air carried something else beneath the usual damp and rust—an acrid chemical bite she couldn't quite place." | | 1 | "\"Martin Ashford. Forty-two. Worked at—\" Crane consulted his notebook \"—British Museum. Conservation department.\"" | | 2 | "They weren't just at odd angles—they were positioned deliberately, fingers extended toward something." | | 3 | "Walls here were different—older brick, some sort of symbol carved near the entrance." | | 4 | "She walked toward the exit, passing the concerned faces of colleagues who didn't understand why she moved so fast, why her jaw was set so tight, why her eyes had that look—the look of someone who had finally found the edge of the map and was ready to step off." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 575 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.03826086956521739 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.019130434782608695 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 11.83 | | std | 9.45 | | cv | 0.799 | | sampleLengths | | 0 | 24 | | 1 | 15 | | 2 | 17 | | 3 | 12 | | 4 | 11 | | 5 | 9 | | 6 | 11 | | 7 | 2 | | 8 | 6 | | 9 | 8 | | 10 | 11 | | 11 | 5 | | 12 | 20 | | 13 | 3 | | 14 | 16 | | 15 | 16 | | 16 | 8 | | 17 | 10 | | 18 | 18 | | 19 | 2 | | 20 | 13 | | 21 | 5 | | 22 | 11 | | 23 | 7 | | 24 | 5 | | 25 | 1 | | 26 | 13 | | 27 | 26 | | 28 | 8 | | 29 | 5 | | 30 | 25 | | 31 | 3 | | 32 | 4 | | 33 | 17 | | 34 | 6 | | 35 | 12 | | 36 | 6 | | 37 | 2 | | 38 | 13 | | 39 | 9 | | 40 | 6 | | 41 | 3 | | 42 | 6 | | 43 | 9 | | 44 | 7 | | 45 | 18 | | 46 | 13 | | 47 | 3 | | 48 | 1 | | 49 | 4 |
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| 77.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.49557522123893805 | | totalSentences | 113 | | uniqueOpeners | 56 | |
| 47.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 70 | | matches | | 0 | "Officially a accident, officially closed." |
| | ratio | 0.014 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 70 | | matches | | 0 | "She recognized the number before" | | 1 | "Her torch found only rubble" | | 2 | "She approached it again, circling" | | 3 | "They weren't just at odd" | | 4 | "She moved toward it, ignoring" | | 5 | "She stopped, frowning." | | 6 | "He caught up, breathless." | | 7 | "He examined the carving, shaking" | | 8 | "She didn't answer." | | 9 | "She lifted his palm, turning" | | 10 | "She released his hand, standing" | | 11 | "she said suddenly" | | 12 | "His face changed." | | 13 | "She pointed toward the tracks" | | 14 | "She looked down at Martin" | | 15 | "She could feel it in" | | 16 | "She pulled out her phone," | | 17 | "She could feel it in" | | 18 | "She walked toward the exit," |
| | ratio | 0.271 | |
| 31.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 70 | | matches | | 0 | "The body lay at the" | | 1 | "Detective Harlow Quinn crouched beside" | | 2 | "DS Crane hovered at her" | | 3 | "Quinn stood, brushing dust from" | | 4 | "She recognized the number before" | | 5 | "DS Morris had died in" | | 6 | "Quinn had never accepted it," | | 7 | "Quinn walked the platform's length," | | 8 | "Someone had tried to clean" | | 9 | "The air carried something else" | | 10 | "Crane consulted his notebook \"—British" | | 11 | "Something flickered in Quinn's mind." | | 12 | "The name meant nothing, but" | | 13 | "A friend of a friend" | | 14 | "Someone had mentioned it recently." | | 15 | "Quinn stopped at the edge" | | 16 | "Her torch found only rubble" | | 17 | "Crane flipped a page." | | 18 | "Quinn turned back to the" | | 19 | "Something nagged at her, an" |
| | ratio | 0.857 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 44.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 4 | | matches | | 0 | "Three years of dead ends and transferred files and colleagues who stopped meeting her eyes." | | 1 | "The girl Aurora talked about sometimes, the one who worked in restricted archives, who studied the kind of history that didn't make it into textbooks." | | 2 | "Behind her, the forensic team descended on the platform, photographing, measuring, bagging evidence that would tell a story she'd have to write herself." | | 3 | "She walked toward the exit, passing the concerned faces of colleagues who didn't understand why she moved so fast, why her jaw was set so tight, why her eyes ha…" |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn scanned, the angles of light, the shadows" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 52 | | tagDensity | 0.019 | | leniency | 0.038 | | rawRatio | 0 | | effectiveRatio | 0 | |