| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1188 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 70.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1188 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "warmth" | | 1 | "echoed" | | 2 | "weight" | | 3 | "silence" | | 4 | "flickered" | | 5 | "measured" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 196 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 196 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 196 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 18 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1185 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1185 | | uniqueNames | 12 | | maxNameDensity | 1.1 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "You" | | discoveredNames | | Soho | 1 | | Carter | 1 | | Raven | 1 | | Nest | 1 | | Blackwood | 1 | | Cardiff | 2 | | London | 1 | | Evan | 1 | | Rory | 2 | | Aurora | 12 | | Silas | 13 | | You | 10 |
| | persons | | 0 | "Carter" | | 1 | "Raven" | | 2 | "Blackwood" | | 3 | "Evan" | | 4 | "Rory" | | 5 | "Aurora" | | 6 | "Silas" | | 7 | "You" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "London" |
| | globalScore | 0.951 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like ash in the dim light" |
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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 | 1185 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 196 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 14.45 | | std | 21.41 | | cv | 1.481 | | sampleLengths | | 0 | 80 | | 1 | 71 | | 2 | 23 | | 3 | 38 | | 4 | 29 | | 5 | 5 | | 6 | 10 | | 7 | 4 | | 8 | 30 | | 9 | 6 | | 10 | 26 | | 11 | 8 | | 12 | 2 | | 13 | 17 | | 14 | 3 | | 15 | 7 | | 16 | 22 | | 17 | 19 | | 18 | 8 | | 19 | 30 | | 20 | 3 | | 21 | 8 | | 22 | 18 | | 23 | 2 | | 24 | 4 | | 25 | 18 | | 26 | 2 | | 27 | 3 | | 28 | 3 | | 29 | 14 | | 30 | 11 | | 31 | 7 | | 32 | 8 | | 33 | 34 | | 34 | 12 | | 35 | 8 | | 36 | 3 | | 37 | 5 | | 38 | 18 | | 39 | 3 | | 40 | 5 | | 41 | 15 | | 42 | 5 | | 43 | 19 | | 44 | 6 | | 45 | 4 | | 46 | 6 | | 47 | 17 | | 48 | 12 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 196 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 227 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 196 | | 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 | 25 | | adverbRatio | 0.021043771043771045 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0016835016835016834 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 196 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 196 | | mean | 6.05 | | std | 3.04 | | cv | 0.503 | | sampleLengths | | 0 | 16 | | 1 | 18 | | 2 | 12 | | 3 | 12 | | 4 | 10 | | 5 | 12 | | 6 | 13 | | 7 | 14 | | 8 | 13 | | 9 | 7 | | 10 | 11 | | 11 | 8 | | 12 | 5 | | 13 | 7 | | 14 | 10 | | 15 | 6 | | 16 | 7 | | 17 | 7 | | 18 | 7 | | 19 | 6 | | 20 | 11 | | 21 | 5 | | 22 | 8 | | 23 | 10 | | 24 | 6 | | 25 | 5 | | 26 | 10 | | 27 | 4 | | 28 | 10 | | 29 | 9 | | 30 | 11 | | 31 | 6 | | 32 | 7 | | 33 | 7 | | 34 | 6 | | 35 | 6 | | 36 | 6 | | 37 | 2 | | 38 | 2 | | 39 | 7 | | 40 | 6 | | 41 | 4 | | 42 | 3 | | 43 | 7 | | 44 | 5 | | 45 | 7 | | 46 | 10 | | 47 | 8 | | 48 | 11 | | 49 | 8 |
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| 33.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 32 | | diversityRatio | 0.20918367346938777 | | totalSentences | 196 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 176 | | matches | (empty) | | ratio | 0 | |
| 1.82% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 96 | | totalSentences | 176 | | matches | | 0 | "She moved toward the bar," | | 1 | "He wore a white shirt" | | 2 | "He set the glass down" | | 3 | "He wore a silver signet" | | 4 | "She placed her hands on" | | 5 | "She turned her left wrist" | | 6 | "He stepped around the end" | | 7 | "He stopped in front of" | | 8 | "You look like your father." | | 9 | "His voice was low, rough" | | 10 | "They told me you were" | | 11 | "He poured two fingers into" | | 12 | "He slid it across the" | | 13 | "I heard you were in" | | 14 | "She wrapped her fingers around" | | 15 | "She did not drink." | | 16 | "You left everything." | | 17 | "I left what I needed" | | 18 | "He crossed his arms over" | | 19 | "She did not tell me" |
| | ratio | 0.545 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 164 | | totalSentences | 176 | | matches | | 0 | "The green neon sign buzzed" | | 1 | "Aurora Carter pushed open the" | | 2 | "Water dripped from the hem" | | 3 | "The air inside smelled of" | | 4 | "Maps covered the walls, their" | | 5 | "She moved toward the bar," | | 6 | "The place was empty save" | | 7 | "He wore a white shirt" | | 8 | "A neat beard framed a" | | 9 | "He set the glass down" | | 10 | "Hazel eyes met bright blue." | | 11 | "The man's hand paused on" | | 12 | "He wore a silver signet" | | 13 | "The metal caught the dim" | | 14 | "Aurora stopped three feet from" | | 15 | "She placed her hands on" | | 16 | "The wood felt cool under" | | 17 | "She turned her left wrist" | | 18 | "The crescent-shaped scar stood out" | | 19 | "Silas Blackwood straightened his spine." |
| | ratio | 0.932 | |
| 85.23% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 176 | | matches | | 0 | "Before he died." | | 1 | "Before you were born." | | 2 | "Because you will not ask" |
| | ratio | 0.017 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 1 | | matches | | 0 | "The photographs depicted men in suits standing outside buildings that had been bombed out during the war." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |