| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 32 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.083 | | effectiveRatio | 0.063 | |
| 87.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 821 | | totalAiIsmAdverbs | 2 | | 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) | |
| 93.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 821 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 47 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 47 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 10 | | totalWords | 821 | | ratio | 0.012 | | matches | | 0 | "Come to London. Get out. I'll find you a room." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 32.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 554 | | uniqueNames | 9 | | maxNameDensity | 2.35 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 13 | | Nest | 1 | | Eva | 7 | | Morgan | 1 | | Silas | 4 | | Crwys | 1 | | Road | 1 | | Evan | 1 | | London | 1 |
| | persons | | 0 | "Rory" | | 1 | "Nest" | | 2 | "Eva" | | 3 | "Morgan" | | 4 | "Silas" | | 5 | "Evan" |
| | places | | | globalScore | 0.327 | | windowScore | 0.5 | |
| 76.47% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 821 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 25.66 | | std | 25.64 | | cv | 0.999 | | sampleLengths | | 0 | 64 | | 1 | 20 | | 2 | 82 | | 3 | 4 | | 4 | 2 | | 5 | 43 | | 6 | 5 | | 7 | 59 | | 8 | 5 | | 9 | 4 | | 10 | 18 | | 11 | 28 | | 12 | 5 | | 13 | 15 | | 14 | 43 | | 15 | 7 | | 16 | 26 | | 17 | 4 | | 18 | 24 | | 19 | 2 | | 20 | 11 | | 21 | 105 | | 22 | 8 | | 23 | 47 | | 24 | 1 | | 25 | 37 | | 26 | 6 | | 27 | 48 | | 28 | 52 | | 29 | 31 | | 30 | 4 | | 31 | 11 |
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| 97.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 47 | | matches | | |
| 74.21% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 106 | | matches | | 0 | "was coming" | | 1 | "was listening" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 556 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02697841726618705 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.007194244604316547 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 12.25 | | std | 8.56 | | cv | 0.698 | | sampleLengths | | 0 | 14 | | 1 | 16 | | 2 | 18 | | 3 | 16 | | 4 | 20 | | 5 | 5 | | 6 | 18 | | 7 | 22 | | 8 | 5 | | 9 | 12 | | 10 | 20 | | 11 | 3 | | 12 | 1 | | 13 | 2 | | 14 | 14 | | 15 | 13 | | 16 | 3 | | 17 | 13 | | 18 | 5 | | 19 | 24 | | 20 | 7 | | 21 | 28 | | 22 | 5 | | 23 | 4 | | 24 | 3 | | 25 | 12 | | 26 | 3 | | 27 | 19 | | 28 | 9 | | 29 | 5 | | 30 | 15 | | 31 | 15 | | 32 | 12 | | 33 | 16 | | 34 | 7 | | 35 | 9 | | 36 | 17 | | 37 | 4 | | 38 | 19 | | 39 | 5 | | 40 | 2 | | 41 | 11 | | 42 | 10 | | 43 | 35 | | 44 | 3 | | 45 | 2 | | 46 | 8 | | 47 | 25 | | 48 | 22 | | 49 | 7 |
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| 68.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4626865671641791 | | totalSentences | 67 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 40 | | matches | (empty) | | ratio | 0 | |
| 50.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 40 | | matches | | 0 | "She had come in for" | | 1 | "She'd barely settled onto her" | | 2 | "She knew the voice the" | | 3 | "His hazel eyes moved from" | | 4 | "He said nothing." | | 5 | "He rarely did when he" | | 6 | "Her knuckles were pale and" | | 7 | "She turned her glass a" | | 8 | "He stayed close enough to" | | 9 | "She could still see the" | | 10 | "I'll find you a room.*" | | 11 | "She had packed one bag" | | 12 | "She had never gone back" | | 13 | "She lifted her palm off" | | 14 | "She didn't wait for an" | | 15 | "She set a crumpled five-pound" | | 16 | "He picked it up, folded" |
| | ratio | 0.425 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 37 | | totalSentences | 40 | | matches | | 0 | "The green neon above the" | | 1 | "The Nest smelled the way" | | 2 | "She had come in for" | | 3 | "Silas lifted two fingers off" | | 4 | "She'd barely settled onto her" | | 5 | "Rory didn't turn straight away." | | 6 | "She knew the voice the" | | 7 | "The long braid was gone." | | 8 | "A wedding band sat on" | | 9 | "Silas set a glass down" | | 10 | "His hazel eyes moved from" | | 11 | "He said nothing." | | 12 | "He rarely did when he" | | 13 | "Eva took the stool beside" | | 14 | "Her knuckles were pale and" | | 15 | "That stopped Rory." | | 16 | "She turned her glass a" | | 17 | "Eva's mouth moved, not quite" | | 18 | "Silas drifted down the bar," | | 19 | "He stayed close enough to" |
| | ratio | 0.925 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 40 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva's mouth moved, not quite a smile" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 32 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.167 | | effectiveRatio | 0.063 | |