| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 474 | | 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) | |
| 36.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 474 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "comforting" | | 1 | "stark" | | 2 | "scanned" | | 3 | "etched" | | 4 | "fragmented" | | 5 | "sequenced" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was heavy with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 22 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 22 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 22 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 76 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 471 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 393 | | uniqueNames | 7 | | maxNameDensity | 0.76 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Silas | 3 | | Prague | 1 | | Rory | 2 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 30.95% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 21 | | glossingSentenceCount | 1 | | matches | | 0 | "As if responding to the both of them, the front door swung open, and a figure walked into this realm of gaslit nostalgia" |
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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 | 471 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 22 | | matches | (empty) | |
| 89.04% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 7 | | mean | 67.29 | | std | 31.06 | | cv | 0.462 | | sampleLengths | | |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 22 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 57 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 92 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.010869565217391304 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 22 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 22 | | mean | 21.36 | | std | 14.04 | | cv | 0.657 | | sampleLengths | | 0 | 18 | | 1 | 21 | | 2 | 13 | | 3 | 20 | | 4 | 11 | | 5 | 8 | | 6 | 21 | | 7 | 23 | | 8 | 22 | | 9 | 18 | | 10 | 24 | | 11 | 21 | | 12 | 13 | | 13 | 9 | | 14 | 26 | | 15 | 13 | | 16 | 17 | | 17 | 23 | | 18 | 17 | | 19 | 42 | | 20 | 13 | | 21 | 77 |
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| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.7727272727272727 | | totalSentences | 22 | | uniqueOpeners | 17 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 22 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 22 | | matches | | 0 | "Her bright blue eyes scanned" | | 1 | "She'd known this place," | | 2 | "She flagged down Silas, who" | | 3 | "He knew why she came" | | 4 | "his low, raspy voice asked," | | 5 | "She sipped, letting her gaze" | | 6 | "They reminded her of a" |
| | ratio | 0.318 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 18 | | totalSentences | 22 | | matches | | 0 | "The fog swirled outside, tendrils" | | 1 | "The air was heavy with" | | 2 | "Aurora Carter slid onto a" | | 3 | "Her bright blue eyes scanned" | | 4 | "She'd known this place," | | 5 | "Some nights she'd find herself" | | 6 | "Tonight, however, she'd come alone," | | 7 | "She flagged down Silas, who" | | 8 | "He knew why she came" | | 9 | "his low, raspy voice asked," | | 10 | "Rory said with a smile," | | 11 | "She sipped, letting her gaze" | | 12 | "Maps of far-off lands, faded" | | 13 | "These stories and the people" | | 14 | "They reminded her of a" | | 15 | "Rory's head snapped around, a" | | 16 | "The face in front of" | | 17 | "The man wasn't in the" |
| | ratio | 0.818 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 22 | | matches | | 0 | "As if responding to the" |
| | ratio | 0.045 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 15 | | technicalSentenceCount | 4 | | matches | | 0 | "Aurora Carter slid onto a stool, her black hair a stark contrast to the warm lighting that bathed her features." | | 1 | "She flagged down Silas, who approached with his customary quiet authority, his grey-streaked auburn hair and neatly trimmed beard a calming presence." | | 2 | "As if responding to the both of them, the front door swung open, and a figure walked into this realm of gaslit nostalgia." | | 3 | "Rory's head snapped around, a cold realization spreading across her skin as if the temperature had dropped." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |