| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.591 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 570 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 56.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 570 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "scanned" | | 3 | "tracing" | | 4 | "crystal" |
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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 | 42 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 42 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 51 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 570 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 3.30% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 409 | | uniqueNames | 6 | | maxNameDensity | 2.93 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Aurora | 10 | | Silas | 12 | | Cardiff | 1 |
| | persons | | | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Cardiff" |
| | globalScore | 0.033 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | 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 | 570 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 24.78 | | std | 13.36 | | cv | 0.539 | | sampleLengths | | 0 | 61 | | 1 | 7 | | 2 | 33 | | 3 | 21 | | 4 | 10 | | 5 | 38 | | 6 | 10 | | 7 | 40 | | 8 | 30 | | 9 | 28 | | 10 | 25 | | 11 | 31 | | 12 | 43 | | 13 | 29 | | 14 | 11 | | 15 | 26 | | 16 | 35 | | 17 | 9 | | 18 | 14 | | 19 | 21 | | 20 | 21 | | 21 | 23 | | 22 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 42 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 75 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 51 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 413 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 5 | | adverbRatio | 0.012106537530266344 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.002421307506053269 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 51 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 51 | | mean | 11.18 | | std | 4.63 | | cv | 0.414 | | sampleLengths | | 0 | 13 | | 1 | 12 | | 2 | 19 | | 3 | 7 | | 4 | 10 | | 5 | 7 | | 6 | 12 | | 7 | 21 | | 8 | 3 | | 9 | 9 | | 10 | 9 | | 11 | 10 | | 12 | 4 | | 13 | 14 | | 14 | 20 | | 15 | 10 | | 16 | 20 | | 17 | 8 | | 18 | 12 | | 19 | 16 | | 20 | 14 | | 21 | 19 | | 22 | 9 | | 23 | 17 | | 24 | 8 | | 25 | 17 | | 26 | 5 | | 27 | 9 | | 28 | 14 | | 29 | 5 | | 30 | 9 | | 31 | 15 | | 32 | 3 | | 33 | 16 | | 34 | 10 | | 35 | 11 | | 36 | 17 | | 37 | 9 | | 38 | 12 | | 39 | 14 | | 40 | 9 | | 41 | 9 | | 42 | 6 | | 43 | 8 | | 44 | 15 | | 45 | 6 | | 46 | 13 | | 47 | 8 | | 48 | 14 | | 49 | 9 |
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| 80.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5294117647058824 | | totalSentences | 51 | | uniqueOpeners | 27 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 41 | | matches | | 0 | "She scanned the room with" | | 1 | "He stared past the bar," | | 2 | "He set the rag down" | | 3 | "She pulled off her damp" | | 4 | "He pushed the glass across" | | 5 | "He pushed it toward her." | | 6 | "She set the glass down" | | 7 | "His hand drifted to the" | | 8 | "She set the glass back" |
| | ratio | 0.22 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 41 | | matches | | 0 | "The green neon sign above" | | 1 | "Silas wiped down the mahogany" | | 2 | "Brass fixtures gleamed under low" | | 3 | "The brass bell above the" | | 4 | "Aurora pushed past the threshold," | | 5 | "She scanned the room with" | | 6 | "Silas stopped wiping." | | 7 | "He stared past the bar," | | 8 | "He set the rag down" | | 9 | "Silas said, resting his heavy" | | 10 | "Aurora crossed the floorboards." | | 11 | "She pulled off her damp" | | 12 | "A small crescent-shaped scar caught" | | 13 | "Aurora said, sliding onto the" | | 14 | "Silas said, pouring a finger" | | 15 | "He pushed the glass across" | | 16 | "Aurora said, her fingers curling" | | 17 | "Silas said, leaning his forearms" | | 18 | "Aurora said, the corner of" | | 19 | "Silas traded the water for" |
| | ratio | 0.927 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 41 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 1 | | matches | | 0 | "She scanned the room with bright blue eyes, her gaze lingering on the framed topographical charts before landing on the bartender." |
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| 48.08% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 2 | | matches | | 0 | "Aurora said, the corner of her mouth twitching upward without humor" | | 1 | "Silas asked, his voice dropping an octave" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 22 | | tagDensity | 0.591 | | leniency | 1 | | rawRatio | 0.077 | | effectiveRatio | 0.077 | |