| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 983 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "truly" | | 1 | "cautiously" | | 2 | "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) | |
| 28.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 983 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "complex" | | 1 | "flicker" | | 2 | "maw" | | 3 | "standard" | | 4 | "potential" | | 5 | "silence" | | 6 | "echoing" | | 7 | "gloom" | | 8 | "charged" | | 9 | "rhythmic" | | 10 | "glint" | | 11 | "normalcy" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 978 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 914 | | uniqueNames | 16 | | maxNameDensity | 0.77 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Harlow | 4 | | Soho | 1 | | Herrera | 7 | | Tomás | 1 | | Raven | 1 | | Nest | 1 | | Camden | 2 | | Tube | 1 | | Sig | 2 | | Sauer | 2 | | Morris | 2 | | Three | 3 | | Detective | 1 | | Quinn | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Herrera" | | 2 | "Tomás" | | 3 | "Nest" | | 4 | "Sauer" | | 5 | "Morris" | | 6 | "Quinn" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Camden" | | 3 | "Sig" | | 4 | "Veil" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | 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 | 978 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 108 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 33.72 | | std | 19.59 | | cv | 0.581 | | sampleLengths | | 0 | 59 | | 1 | 58 | | 2 | 67 | | 3 | 55 | | 4 | 82 | | 5 | 51 | | 6 | 38 | | 7 | 25 | | 8 | 25 | | 9 | 14 | | 10 | 11 | | 11 | 13 | | 12 | 47 | | 13 | 4 | | 14 | 48 | | 15 | 32 | | 16 | 21 | | 17 | 38 | | 18 | 38 | | 19 | 40 | | 20 | 40 | | 21 | 23 | | 22 | 20 | | 23 | 30 | | 24 | 19 | | 25 | 2 | | 26 | 49 | | 27 | 6 | | 28 | 23 |
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| 95.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 103 | | matches | | 0 | "was headed" | | 1 | "was lost" | | 2 | "been closed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 144 | | matches | | 0 | "was starting" | | 1 | "wasn't backing" |
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| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 108 | | ratio | 0.037 | | matches | | 0 | "He—Herrera, Tomás Herrera—was quick, surprisingly so for a man who spent his days patching up scrapes and broken bones." | | 1 | "A flicker of something—fear, perhaps?—crossed his face." | | 2 | "She remembered the report—surface level check, structurally unsound, no signs of forced entry." | | 3 | "A wave of sounds washed over her – muffled voices, the clinking of glass, and an undertone of something else, something primal and unnerving." |
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| 95.96% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 919 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.04461371055495103 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.017410228509249184 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 9.06 | | std | 5.71 | | cv | 0.631 | | sampleLengths | | 0 | 10 | | 1 | 16 | | 2 | 19 | | 3 | 11 | | 4 | 3 | | 5 | 16 | | 6 | 24 | | 7 | 2 | | 8 | 3 | | 9 | 5 | | 10 | 8 | | 11 | 12 | | 12 | 18 | | 13 | 4 | | 14 | 16 | | 15 | 5 | | 16 | 12 | | 17 | 16 | | 18 | 13 | | 19 | 14 | | 20 | 7 | | 21 | 1 | | 22 | 4 | | 23 | 22 | | 24 | 15 | | 25 | 16 | | 26 | 7 | | 27 | 5 | | 28 | 17 | | 29 | 5 | | 30 | 14 | | 31 | 9 | | 32 | 18 | | 33 | 5 | | 34 | 12 | | 35 | 2 | | 36 | 6 | | 37 | 12 | | 38 | 4 | | 39 | 2 | | 40 | 12 | | 41 | 13 | | 42 | 5 | | 43 | 20 | | 44 | 14 | | 45 | 11 | | 46 | 4 | | 47 | 3 | | 48 | 2 | | 49 | 4 |
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| 44.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3425925925925926 | | totalSentences | 108 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 92 | | matches | | 0 | "Then she saw it." | | 1 | "Then, a glint of metal" | | 2 | "Then, with her Sig Sauer" |
| | ratio | 0.033 | |
| 50.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 92 | | matches | | 0 | "She kept her stride long" | | 1 | "He—Herrera, Tomás Herrera—was quick, surprisingly" | | 2 | "She’d pegged him as soft," | | 3 | "She’d been wrong." | | 4 | "He’d bolted from The Raven’s" | | 5 | "They all knew." | | 6 | "They were a network, a" | | 7 | "She didn’t break stride." | | 8 | "He was headed toward Camden." | | 9 | "He glanced over his shoulder," | | 10 | "She pushed past a couple" | | 11 | "He disappeared into the grimy" | | 12 | "She slowed, reaching the entrance." | | 13 | "Her hand instinctively went to" | | 14 | "It wasn’t a mugging gone" | | 15 | "It was something else." | | 16 | "She pulled out her radio," | | 17 | "She clenched her jaw." | | 18 | "They wouldn’t understand." | | 19 | "She cut the connection, the" |
| | ratio | 0.424 | |
| 46.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 92 | | matches | | 0 | "Rain lashed at Harlow’s face," | | 1 | "She kept her stride long" | | 2 | "He—Herrera, Tomás Herrera—was quick, surprisingly" | | 3 | "She’d pegged him as soft," | | 4 | "She’d been wrong." | | 5 | "He’d bolted from The Raven’s" | | 6 | "Silas, the bar’s owner, hadn’t" | | 7 | "They all knew." | | 8 | "That was the frustrating part." | | 9 | "They were a network, a" | | 10 | "Harlow adjusted the collar of" | | 11 | "Herrera cut a hard left," | | 12 | "She didn’t break stride." | | 13 | "Years on the force had" | | 14 | "He was headed toward Camden." | | 15 | "The alley opened onto a" | | 16 | "Herrera was already weaving through" | | 17 | "He glanced over his shoulder," | | 18 | "A flicker of something—fear, perhaps?—crossed" | | 19 | "She pushed past a couple" |
| | ratio | 0.826 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 92 | | matches | | 0 | "Or, more accurately, incomplete." | | 1 | "To enter a world she" |
| | ratio | 0.022 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "He—Herrera, Tomás Herrera—was quick, surprisingly so for a man who spent his days patching up scrapes and broken bones." | | 1 | "Rain dripped from the decaying ceiling, forming puddles that reflected the faint streetlights filtering through the grates above." | | 2 | "The door creaked inward, revealing a dimly lit passageway that descended into the earth." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |