| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.18% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 797 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
| | 2 | |
| | highlights | | 0 | "suddenly" | | 1 | "barely above a whisper" | | 2 | "very" |
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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) | |
| 24.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 797 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "raced" | | 1 | "echoed" | | 2 | "sense of" | | 3 | "footsteps" | | 4 | "scanned" | | 5 | "pounding" | | 6 | "cacophony" | | 7 | "gloom" | | 8 | "familiar" | | 9 | "whisper" | | 10 | "trembled" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 801 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 691 | | uniqueNames | 7 | | maxNameDensity | 3.18 | | worstName | "Harlow" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Harlow" | | discoveredNames | | Detective | 1 | | Harlow | 22 | | Quinn | 1 | | Tomás | 6 | | Raven | 1 | | Nest | 1 | | Soho | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Raven" |
| | places | | | globalScore | 0 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 801 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 64 | | matches | | |
| 93.91% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 26.7 | | std | 12.78 | | cv | 0.479 | | sampleLengths | | 0 | 40 | | 1 | 33 | | 2 | 33 | | 3 | 65 | | 4 | 41 | | 5 | 43 | | 6 | 30 | | 7 | 28 | | 8 | 14 | | 9 | 27 | | 10 | 40 | | 11 | 23 | | 12 | 12 | | 13 | 26 | | 14 | 15 | | 15 | 16 | | 16 | 17 | | 17 | 15 | | 18 | 49 | | 19 | 16 | | 20 | 17 | | 21 | 28 | | 22 | 32 | | 23 | 10 | | 24 | 11 | | 25 | 36 | | 26 | 19 | | 27 | 17 | | 28 | 32 | | 29 | 16 |
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| 84.62% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 51 | | matches | | 0 | "was swallowed" | | 1 | "being watched" | | 2 | "were connected" |
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| 80.95% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 112 | | matches | | 0 | "were closing" | | 1 | "was trying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 64 | | ratio | 0.094 | | matches | | 0 | "This was no ordinary suspect - Harlow had been hunting this one for weeks, piecing together the clues that tied them to a string of unsolved cases." | | 1 | "This wasn't a normal subway tunnel - it had a sense of age and secrecy that made the hairs on the back of her neck stand on end." | | 2 | "There - the faint patter of footsteps, growing fainter by the second." | | 3 | "Peculiar items glinted in the flickering light - crystals, talismans, jars filled with strange liquids." | | 4 | "There - a flash of movement at the far end of the market." | | 5 | "Silas - the owner of the Raven's Nest bar, a fixture in the Soho community and, as Harlow had long suspected, the ringleader of a criminal clique with ties to the supernatural." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 495 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.012121212121212121 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.010101010101010102 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 12.52 | | std | 6.29 | | cv | 0.503 | | sampleLengths | | 0 | 22 | | 1 | 18 | | 2 | 27 | | 3 | 6 | | 4 | 15 | | 5 | 18 | | 6 | 16 | | 7 | 9 | | 8 | 3 | | 9 | 9 | | 10 | 28 | | 11 | 11 | | 12 | 12 | | 13 | 18 | | 14 | 21 | | 15 | 22 | | 16 | 15 | | 17 | 15 | | 18 | 13 | | 19 | 15 | | 20 | 14 | | 21 | 11 | | 22 | 16 | | 23 | 7 | | 24 | 14 | | 25 | 19 | | 26 | 11 | | 27 | 12 | | 28 | 7 | | 29 | 5 | | 30 | 16 | | 31 | 10 | | 32 | 3 | | 33 | 12 | | 34 | 8 | | 35 | 8 | | 36 | 3 | | 37 | 14 | | 38 | 10 | | 39 | 5 | | 40 | 13 | | 41 | 19 | | 42 | 17 | | 43 | 7 | | 44 | 9 | | 45 | 10 | | 46 | 7 | | 47 | 16 | | 48 | 12 | | 49 | 17 |
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| 68.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.421875 | | totalSentences | 64 | | uniqueOpeners | 27 | |
| 65.36% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 51 | | matches | | 0 | "Suddenly, a figure stepped out" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 51 | | matches | | 0 | "She blinked, her eyes adjusting" | | 1 | "She took a deep breath" | | 2 | "she shouted, but her voice" | | 3 | "She couldn't shake the feeling" | | 4 | "she breathed, recognizing the former" | | 5 | "She knew he had his" | | 6 | "she said, her voice softening" | | 7 | "He turned and led Harlow" | | 8 | "They emerged into a dimly" | | 9 | "It was a woman, her" |
| | ratio | 0.196 | |
| 18.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 51 | | matches | | 0 | "Rain pounded the pavement as" | | 1 | "The sharp sound of her" | | 2 | "This was no ordinary suspect" | | 3 | "Harlow didn't hesitate, taking the" | | 4 | "The air grew thick and" | | 5 | "She blinked, her eyes adjusting" | | 6 | "The walls were rough-hewn, the" | | 7 | "This wasn't a normal subway" | | 8 | "Harlow paused, ears straining to" | | 9 | "There - the faint patter" | | 10 | "She took a deep breath" | | 11 | "The tunnel opened up into" | | 12 | "Harlow emerged into a sprawling" | | 13 | "Peculiar items glinted in the" | | 14 | "Harlow's eyes narrowed as she" | | 15 | "There - a flash of" | | 16 | "Harlow surged forward, weaving between" | | 17 | "she shouted, but her voice" | | 18 | "The suspect darted down a" | | 19 | "Harlow gritted her teeth and" |
| | ratio | 0.882 | |
| 98.04% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 51 | | matches | | 0 | "Now, finally, she had her" |
| | ratio | 0.02 | |
| 81.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 3 | | matches | | 0 | "This was no ordinary suspect - Harlow had been hunting this one for weeks, piecing together the clues that tied them to a string of unsolved cases." | | 1 | "This wasn't a normal subway tunnel - it had a sense of age and secrecy that made the hairs on the back of her neck stand on end." | | 2 | "Harlow surged forward, weaving between the stalls and vendors, her heart pounding in her ears." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 4 | | matches | | 0 | "she shouted, but her voice was swallowed by the cacophony around her" | | 1 | "Tomás said, his voice barely above a whisper" | | 2 | "she said, her voice softening" | | 3 | "the woman purred, her voice dripping with menace" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she breathed (breathe)" | | 2 | "Tomás whispered (whisper)" |
| | dialogueSentences | 20 | | tagDensity | 0.3 | | leniency | 0.6 | | rawRatio | 0.5 | | effectiveRatio | 0.3 | |