| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 73 | | tagDensity | 0.082 | | leniency | 0.164 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1207 | | 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) | |
| 50.29% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1207 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "scanned" | | 1 | "weight" | | 2 | "warmth" | | 3 | "familiar" | | 4 | "echoed" | | 5 | "traced" | | 6 | "unreadable" | | 7 | "silence" |
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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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 183 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1207 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 924 | | uniqueNames | 5 | | maxNameDensity | 2.16 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Soho | 1 | | Silas | 20 | | Aurora | 9 | | Eastern | 1 | | Europe | 1 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Eastern" | | 2 | "Europe" |
| | globalScore | 0.418 | | windowScore | 0.333 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 5 | | matches | | 0 | "quite a laugh" | | 1 | "seemed deeper than she remembered" | | 2 | "looked like cages" | | 3 | "looked like frost" | | 4 | "looked like a weight he carried every day" |
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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 | 1207 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 183 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 100 | | mean | 12.07 | | std | 15.97 | | cv | 1.323 | | sampleLengths | | 0 | 69 | | 1 | 54 | | 2 | 14 | | 3 | 39 | | 4 | 9 | | 5 | 1 | | 6 | 51 | | 7 | 3 | | 8 | 28 | | 9 | 5 | | 10 | 32 | | 11 | 8 | | 12 | 6 | | 13 | 28 | | 14 | 3 | | 15 | 5 | | 16 | 2 | | 17 | 3 | | 18 | 45 | | 19 | 4 | | 20 | 3 | | 21 | 4 | | 22 | 6 | | 23 | 42 | | 24 | 11 | | 25 | 3 | | 26 | 1 | | 27 | 3 | | 28 | 57 | | 29 | 5 | | 30 | 10 | | 31 | 4 | | 32 | 17 | | 33 | 4 | | 34 | 4 | | 35 | 2 | | 36 | 30 | | 37 | 7 | | 38 | 5 | | 39 | 6 | | 40 | 4 | | 41 | 3 | | 42 | 19 | | 43 | 3 | | 44 | 5 | | 45 | 10 | | 46 | 18 | | 47 | 5 | | 48 | 2 | | 49 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 172 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 183 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 928 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavy leather-bound atlas" |
| | adverbCount | 20 | | adverbRatio | 0.021551724137931036 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003232758620689655 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 183 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 183 | | mean | 6.6 | | std | 4.65 | | cv | 0.704 | | sampleLengths | | 0 | 17 | | 1 | 16 | | 2 | 5 | | 3 | 16 | | 4 | 15 | | 5 | 16 | | 6 | 20 | | 7 | 2 | | 8 | 4 | | 9 | 12 | | 10 | 9 | | 11 | 5 | | 12 | 10 | | 13 | 4 | | 14 | 17 | | 15 | 8 | | 16 | 3 | | 17 | 6 | | 18 | 1 | | 19 | 9 | | 20 | 9 | | 21 | 13 | | 22 | 13 | | 23 | 7 | | 24 | 3 | | 25 | 8 | | 26 | 15 | | 27 | 5 | | 28 | 5 | | 29 | 11 | | 30 | 15 | | 31 | 6 | | 32 | 8 | | 33 | 6 | | 34 | 7 | | 35 | 6 | | 36 | 4 | | 37 | 11 | | 38 | 3 | | 39 | 5 | | 40 | 2 | | 41 | 3 | | 42 | 6 | | 43 | 17 | | 44 | 5 | | 45 | 17 | | 46 | 4 | | 47 | 3 | | 48 | 4 | | 49 | 6 |
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| 37.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.23497267759562843 | | totalSentences | 183 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 58 | | totalSentences | 104 | | matches | | 0 | "She shook the water from" | | 1 | "His grey-streaked auburn hair caught" | | 2 | "His hazel eyes locked onto" | | 3 | "He set the glass down" | | 4 | "She scanned the room." | | 5 | "His voice held a gravelly" | | 6 | "He leaned forward, resting his" | | 7 | "He pushed off the counter" | | 8 | "His left leg dragged slightly," | | 9 | "He stopped a few feet" | | 10 | "She pulled the sleeve down." | | 11 | "He reached for a bottle" | | 12 | "He slid it across the" | | 13 | "She wrapped her hands around" | | 14 | "She took a sip." | | 15 | "He picked up another rag" | | 16 | "His movements were precise, economical." | | 17 | "She remembered the first time" | | 18 | "She remembered the feeling of" | | 19 | "He didn't turn around." |
| | ratio | 0.558 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 104 | | matches | | 0 | "Rain slicked the cobblestones of" | | 1 | "The green neon sign above" | | 2 | "Aurora pushed the door open." | | 3 | "A brass bell chimed, cutting" | | 4 | "She shook the water from" | | 5 | "Silas stood behind the bar," | | 6 | "His grey-streaked auburn hair caught" | | 7 | "The rag stopped moving." | | 8 | "His hazel eyes locked onto" | | 9 | "He set the glass down" | | 10 | "The wood absorbed the sound." | | 11 | "Aurora kept her hands in" | | 12 | "She scanned the room." | | 13 | "The air smelled of stale" | | 14 | "His voice held a gravelly" | | 15 | "He leaned forward, resting his" | | 16 | "A silver signet ring glinted" | | 17 | "He pushed off the counter" | | 18 | "His left leg dragged slightly," | | 19 | "He stopped a few feet" |
| | ratio | 0.99 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "Silas stood behind the bar, polishing a tumbler with a rag that had seen better days." | | 1 | "He picked up another rag and started wiping a spot on the counter that was already clean." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 73 | | tagDensity | 0.082 | | leniency | 0.164 | | rawRatio | 0 | | effectiveRatio | 0 | |