| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 62 | | tagDensity | 0.323 | | leniency | 0.645 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.64% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1068 | | 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) | |
| 48.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1068 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "scanned" | | 1 | "pulsed" | | 2 | "silence" | | 3 | "weight" | | 4 | "pristine" | | 5 | "eyebrow" | | 6 | "etched" | | 7 | "structure" | | 8 | "vibrated" | | 9 | "flicked" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 73 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 73 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1060 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 1 | | matches | | 0 | "Behind her, Miller sighed." |
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| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 537 | | uniqueNames | 8 | | maxNameDensity | 3.91 | | worstName | "Harlow" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Harlow" | | discoveredNames | | Detective | 1 | | Harlow | 21 | | Quinn | 1 | | Miller | 12 | | Tube | 1 | | Kowalski | 1 | | Eva | 11 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Miller" | | 3 | "Kowalski" | | 4 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 89.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared fresher than the surrounding graffiti" |
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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 | 1060 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 18.93 | | std | 10.46 | | cv | 0.553 | | sampleLengths | | 0 | 31 | | 1 | 19 | | 2 | 24 | | 3 | 3 | | 4 | 24 | | 5 | 34 | | 6 | 31 | | 7 | 27 | | 8 | 21 | | 9 | 1 | | 10 | 10 | | 11 | 25 | | 12 | 4 | | 13 | 17 | | 14 | 4 | | 15 | 4 | | 16 | 25 | | 17 | 3 | | 18 | 20 | | 19 | 9 | | 20 | 40 | | 21 | 4 | | 22 | 18 | | 23 | 12 | | 24 | 35 | | 25 | 10 | | 26 | 43 | | 27 | 6 | | 28 | 16 | | 29 | 24 | | 30 | 23 | | 31 | 12 | | 32 | 37 | | 33 | 7 | | 34 | 32 | | 35 | 4 | | 36 | 33 | | 37 | 20 | | 38 | 31 | | 39 | 16 | | 40 | 25 | | 41 | 12 | | 42 | 25 | | 43 | 25 | | 44 | 22 | | 45 | 10 | | 46 | 27 | | 47 | 23 | | 48 | 17 | | 49 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 73 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 102 | | matches | (empty) | |
| 68.32% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 115 | | ratio | 0.026 | | matches | | 0 | "His clothes—expensive suit—were pristine except for the dark stain spreading across his chest." | | 1 | "Something caught her eye—a small circular indentation on the victim's right hand, between thumb and forefinger." | | 2 | "Nothing seemed out of place except—" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 542 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.016605166051660517 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.007380073800738007 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 9.22 | | std | 6.12 | | cv | 0.664 | | sampleLengths | | 0 | 15 | | 1 | 8 | | 2 | 6 | | 3 | 2 | | 4 | 19 | | 5 | 10 | | 6 | 14 | | 7 | 3 | | 8 | 9 | | 9 | 15 | | 10 | 5 | | 11 | 6 | | 12 | 8 | | 13 | 15 | | 14 | 8 | | 15 | 10 | | 16 | 13 | | 17 | 7 | | 18 | 20 | | 19 | 5 | | 20 | 16 | | 21 | 1 | | 22 | 10 | | 23 | 6 | | 24 | 13 | | 25 | 6 | | 26 | 4 | | 27 | 17 | | 28 | 4 | | 29 | 4 | | 30 | 5 | | 31 | 16 | | 32 | 4 | | 33 | 3 | | 34 | 6 | | 35 | 9 | | 36 | 5 | | 37 | 4 | | 38 | 5 | | 39 | 25 | | 40 | 15 | | 41 | 4 | | 42 | 12 | | 43 | 6 | | 44 | 7 | | 45 | 5 | | 46 | 3 | | 47 | 23 | | 48 | 9 | | 49 | 5 |
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| 75.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4608695652173913 | | totalSentences | 115 | | uniqueOpeners | 53 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "Then they approached the staircase." |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 67 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "She checked her worn leather" | | 2 | "She moved with military precision," | | 3 | "His arms outstretched, face frozen" | | 4 | "His clothes—expensive suit—were pristine except" | | 5 | "Her gaze swept over discarded" | | 6 | "She ran her fingers over" | | 7 | "She pressed against the wall" | | 8 | "She clutched a worn leather" | | 9 | "She adjusted her glasses, tucking" | | 10 | "She approached the body, careful" | | 11 | "She examined the victim's hands," | | 12 | "She reached into the victim's" | | 13 | "She turned to the hidden" | | 14 | "It creaked open, revealing a" |
| | ratio | 0.224 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 67 | | matches | | 0 | "The rain lashed against the" | | 1 | "Her closely cropped salt-and-pepper hair" | | 2 | "She checked her worn leather" | | 3 | "DS Miller shifted from foot" | | 4 | "Harlow scanned the exterior of" | | 5 | "Camden's nightlife pulsed blocks away," | | 6 | "Miller motioned toward the dark" | | 7 | "Harlow stepped into the station." | | 8 | "The air grew thick and" | | 9 | "Emergency lights cast long shadows" | | 10 | "She moved with military precision," | | 11 | "The body lay sprawled near" | | 12 | "His arms outstretched, face frozen" | | 13 | "His clothes—expensive suit—were pristine except" | | 14 | "Miller shone his torch on" | | 15 | "Harlow knelt beside the body." | | 16 | "Something caught her eye—a small" | | 17 | "Harlow stood and walked the" | | 18 | "Her gaze swept over discarded" | | 19 | "Nothing seemed out of place" |
| | ratio | 0.97 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | 0 | "DS Miller shifted, his breath forming clouds in the cold night air" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "She pressed (press)" | | 1 | "Harlow pressed (press)" |
| | dialogueSentences | 62 | | tagDensity | 0.065 | | leniency | 0.129 | | rawRatio | 0.5 | | effectiveRatio | 0.065 | |