| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.636 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 774 | | 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) | |
| 28.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 774 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "glinting" | | 1 | "maw" | | 2 | "echoed" | | 3 | "footsteps" | | 4 | "flicker" | | 5 | "pulsed" | | 6 | "weight" | | 7 | "flickered" | | 8 | "familiar" |
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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 | | |
| 91.67% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 50 | | matches | | 0 | "filled with sympathy" | | 1 | "d with sympathy" |
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| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 50 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "tried to" | | 2 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 54 | | 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 | 780 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.63% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 678 | | uniqueNames | 14 | | maxNameDensity | 1.33 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Morris | 3 | | Raven | 1 | | Nest | 1 | | Camden | 1 | | High | 1 | | Street | 1 | | Tube | 1 | | Quinn | 9 | | Tomás | 3 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Spanish | 1 |
| | persons | | 0 | "Morris" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Camden" | | 3 | "High" | | 4 | "Street" |
| | globalScore | 0.836 | | windowScore | 1 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 2 | | matches | | 0 | "items that seemed to shift and change when she tried to focus on them" | | 1 | "quite human" |
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| 71.79% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.282 | | wordCount | 780 | | matches | | 0 | "not of pain, but of something worse" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 54 | | matches | (empty) | |
| 68.27% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 37.14 | | std | 14.45 | | cv | 0.389 | | sampleLengths | | 0 | 51 | | 1 | 50 | | 2 | 59 | | 3 | 47 | | 4 | 46 | | 5 | 21 | | 6 | 49 | | 7 | 41 | | 8 | 65 | | 9 | 10 | | 10 | 36 | | 11 | 14 | | 12 | 28 | | 13 | 30 | | 14 | 23 | | 15 | 32 | | 16 | 40 | | 17 | 19 | | 18 | 29 | | 19 | 42 | | 20 | 48 |
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| 98.25% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 50 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 114 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 54 | | ratio | 0.111 | | matches | | 0 | "Three years of dead ends since Morris disappeared, and finally, a solid lead – she wasn't about to lose it now." | | 1 | "The figure ahead wore dark clothes, but she caught glimpses of something glinting at their neck – maybe jewelry, maybe a weapon." | | 2 | "This station had been abandoned for years; she'd passed it countless times during her beats." | | 3 | "A flicker of movement caught her eye – her suspect disappearing around a corner deeper in the station." | | 4 | "A man materialized from the shadows beside her – Tomás Herrera, the disgraced paramedic she'd interviewed last month about a string of mysterious injuries." | | 5 | "A scream echoed from the lower levels – not of pain, but of something worse." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 678 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.02359882005899705 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008849557522123894 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 54 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 54 | | mean | 14.44 | | std | 6.35 | | cv | 0.44 | | sampleLengths | | 0 | 16 | | 1 | 14 | | 2 | 21 | | 3 | 21 | | 4 | 14 | | 5 | 15 | | 6 | 14 | | 7 | 23 | | 8 | 22 | | 9 | 14 | | 10 | 13 | | 11 | 5 | | 12 | 15 | | 13 | 13 | | 14 | 13 | | 15 | 8 | | 16 | 12 | | 17 | 21 | | 18 | 13 | | 19 | 8 | | 20 | 15 | | 21 | 3 | | 22 | 10 | | 23 | 18 | | 24 | 23 | | 25 | 11 | | 26 | 11 | | 27 | 23 | | 28 | 13 | | 29 | 7 | | 30 | 10 | | 31 | 24 | | 32 | 12 | | 33 | 10 | | 34 | 4 | | 35 | 18 | | 36 | 10 | | 37 | 18 | | 38 | 12 | | 39 | 10 | | 40 | 13 | | 41 | 32 | | 42 | 15 | | 43 | 12 | | 44 | 13 | | 45 | 14 | | 46 | 5 | | 47 | 7 | | 48 | 22 | | 49 | 15 |
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| 87.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5370370370370371 | | totalSentences | 54 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 48 | | matches | | 0 | "Just like the darkness that" | | 1 | "Instead, Quinn found herself at" |
| | ratio | 0.042 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 48 | | matches | | 0 | "Her quarry was quick, but" | | 1 | "They burst out onto Camden" | | 2 | "She paused at the top" | | 3 | "Her hand went to her" | | 4 | "Her voice echoed into the" | | 5 | "Her footsteps echoed in the" | | 6 | "she whispered, her grip tightening" | | 7 | "His Saint Christopher medallion caught" | | 8 | "he said, his Spanish accent" | | 9 | "She kept her voice steady" | | 10 | "He touched the scar on" | | 11 | "she asked, though she already" | | 12 | "She had to make a" | | 13 | "Her watch ticked steadily against" |
| | ratio | 0.292 | |
| 22.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 48 | | matches | | 0 | "Quinn's boots pounded against wet" | | 1 | "Rain pelted her face, but" | | 2 | "The suspect darted down an" | | 3 | "Quinn followed, her breath coming" | | 4 | "Her quarry was quick, but" | | 5 | "A crash of metal as" | | 6 | "Quinn vaulted over them without" | | 7 | "The figure ahead wore dark" | | 8 | "They burst out onto Camden" | | 9 | "The suspect veered suddenly, disappearing" | | 10 | "Quinn's instincts screamed a warning." | | 11 | "This station had been abandoned" | | 12 | "She paused at the top" | | 13 | "The entrance gaped like a" | | 14 | "Her hand went to her" | | 15 | "Her voice echoed into the" | | 16 | "Quinn descended the stairs, using" | | 17 | "The beam caught crumbling tiles" | | 18 | "Her footsteps echoed in the" | | 19 | "This wasn't right." |
| | ratio | 0.875 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 48 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "Figures in hooded robes browsed merchandise that glowed and pulsed with impossible colors." | | 1 | "Quinn's military training warred with her instinct for self-preservation as the lights in the market flickered, casting strange shadows that moved independent o…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "she whispered, her grip tightening on her weapon" | | 1 | "he said, his Spanish accent thick with concern" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "Tomás continued (continue)" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.5 | | effectiveRatio | 0.364 | |