| 51.85% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 2 | | adverbTags | | 0 | "Tomás glanced back [back]" | | 1 | "he said quietly [quietly]" |
| | dialogueSentences | 27 | | tagDensity | 0.37 | | leniency | 0.741 | | rawRatio | 0.2 | | effectiveRatio | 0.148 | |
| 92.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1400 | | 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) | |
| 64.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1400 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "tension" | | 1 | "loomed" | | 2 | "stomach" | | 3 | "constructed" | | 4 | "flickered" | | 5 | "scanned" | | 6 | "charged" | | 7 | "familiar" | | 8 | "footsteps" | | 9 | "echoing" |
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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 | 117 | | matches | (empty) | |
| 69.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 117 | | filterMatches | | | hedgeMatches | | 0 | "began to" | | 1 | "appeared to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1400 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1184 | | uniqueNames | 15 | | maxNameDensity | 1.27 | | worstName | "Tomás" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Tomás" | | discoveredNames | | Quinn | 14 | | Raven | 1 | | Nest | 2 | | Morris | 2 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 15 | | Seville | 1 | | London | 2 | | Tube | 1 | | Underground | 1 | | Latin | 1 | | One | 2 | | Spanish | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Morris" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" | | 7 | "One" |
| | places | | 0 | "Seville" | | 1 | "London" | | 2 | "Spanish" |
| | globalScore | 0.867 | | windowScore | 0.833 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 6 | | matches | | 0 | "looked like a makeshift turnstile made fr" | | 1 | "sounded like backwards Latin" | | 2 | "looked like liquid starlight" | | 3 | "looked like a curved blade made of black" | | 4 | "seemed heavier charged" | | 5 | "voice that seemed to come from everywhere at once" |
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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 | 1400 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 134 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 31.11 | | std | 21.44 | | cv | 0.689 | | sampleLengths | | 0 | 53 | | 1 | 15 | | 2 | 76 | | 3 | 57 | | 4 | 43 | | 5 | 13 | | 6 | 20 | | 7 | 26 | | 8 | 58 | | 9 | 57 | | 10 | 8 | | 11 | 45 | | 12 | 54 | | 13 | 7 | | 14 | 55 | | 15 | 93 | | 16 | 6 | | 17 | 52 | | 18 | 41 | | 19 | 12 | | 20 | 17 | | 21 | 32 | | 22 | 43 | | 23 | 17 | | 24 | 8 | | 25 | 45 | | 26 | 31 | | 27 | 38 | | 28 | 33 | | 29 | 38 | | 30 | 14 | | 31 | 9 | | 32 | 38 | | 33 | 58 | | 34 | 7 | | 35 | 45 | | 36 | 10 | | 37 | 44 | | 38 | 13 | | 39 | 15 | | 40 | 24 | | 41 | 3 | | 42 | 23 | | 43 | 1 | | 44 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 225 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 134 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1188 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.03535353535353535 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007575757575757576 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 10.45 | | std | 6.6 | | cv | 0.632 | | sampleLengths | | 0 | 8 | | 1 | 19 | | 2 | 11 | | 3 | 15 | | 4 | 3 | | 5 | 12 | | 6 | 4 | | 7 | 23 | | 8 | 13 | | 9 | 19 | | 10 | 10 | | 11 | 4 | | 12 | 3 | | 13 | 12 | | 14 | 11 | | 15 | 4 | | 16 | 30 | | 17 | 17 | | 18 | 21 | | 19 | 4 | | 20 | 1 | | 21 | 7 | | 22 | 6 | | 23 | 8 | | 24 | 12 | | 25 | 13 | | 26 | 6 | | 27 | 7 | | 28 | 10 | | 29 | 23 | | 30 | 25 | | 31 | 21 | | 32 | 2 | | 33 | 3 | | 34 | 11 | | 35 | 5 | | 36 | 15 | | 37 | 8 | | 38 | 6 | | 39 | 11 | | 40 | 17 | | 41 | 11 | | 42 | 17 | | 43 | 16 | | 44 | 14 | | 45 | 4 | | 46 | 3 | | 47 | 6 | | 48 | 1 | | 49 | 5 |
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| 67.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.417910447761194 | | totalSentences | 134 | | uniqueOpeners | 56 | |
| 30.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 109 | | matches | | 0 | "Instead he veered left down" |
| | ratio | 0.009 | |
| 91.56% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 109 | | matches | | 0 | "Her worn leather watch slapped" | | 1 | "She had chased men like" | | 2 | "He did not slow." | | 3 | "She cleared them a second" | | 4 | "She had watched him slip" | | 5 | "He burst from the alley" | | 6 | "His accent carried the soft" | | 7 | "He sounded more disappointed than" | | 8 | "She poured on speed, closing" | | 9 | "Her hand brushed the radio" | | 10 | "She took the stairs two" | | 11 | "She heard voices now, low" | | 12 | "He held something small between" | | 13 | "He stepped through." | | 14 | "She slammed her shoulder against" | | 15 | "Her stomach tightened, but she" | | 16 | "She had raided enough drug" | | 17 | "She spotted Tomás at a" | | 18 | "He spoke quickly with a" | | 19 | "His hands moved in short," |
| | ratio | 0.321 | |
| 19.63% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 109 | | matches | | 0 | "Harlow Quinn surged forward, elbows" | | 1 | "The suspect's curly head bobbed" | | 2 | "Her worn leather watch slapped" | | 3 | "She had chased men like" | | 4 | "He did not slow." | | 5 | "Quinn followed, boots splashing through" | | 6 | "The scar on his left" | | 7 | "She cleared them a second" | | 8 | "Pain flared, then dulled." | | 9 | "Adrenaline did that." | | 10 | "Quinn still saw his name" | | 11 | "Tomás Herrera knew things." | | 12 | "She had watched him slip" | | 13 | "He burst from the alley" | | 14 | "Quinn stayed close enough to" | | 15 | "The man was tiring." | | 16 | "Tomás glanced back, warm brown" | | 17 | "His accent carried the soft" | | 18 | "He sounded more disappointed than" | | 19 | "That annoyed her more than" |
| | ratio | 0.881 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 109 | | matches | (empty) | | ratio | 0 | |
| 88.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 4 | | matches | | 0 | "Quinn followed, boots splashing through puddles that had collected between cracked paving stones." | | 1 | "Camden loomed ahead, the streets narrowing, the crowds thinning into the sort of people who knew better than to stare at a pursuit." | | 2 | "A bell rang somewhere deeper in the chamber, three clear notes that cut through the murmuring." | | 3 | "The hooded figures kept coming, their footsteps echoing off the curved tunnel walls." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, voice steady" |
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| 75.93% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "Tomás whispered (whisper)" |
| | dialogueSentences | 27 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0.333 | | effectiveRatio | 0.148 | |