| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 46 | | tagDensity | 0.348 | | leniency | 0.696 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 75.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1028 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "carefully" | | 1 | "really" | | 2 | "sharply" | | 3 | "slowly" | | 4 | "suddenly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 7.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1028 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "skipped a beat" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | word | "down her spine" | | count | 1 |
| | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | |
| | highlights | | 0 | "unreadable" | | 1 | "charm" | | 2 | "flickered" | | 3 | "magnetic" | | 4 | "skipped a beat" | | 5 | "constructed" | | 6 | "shattered" | | 7 | "chaotic" | | 8 | "down her spine" | | 9 | "dance" | | 10 | "echoes" | | 11 | "familiar" | | 12 | "weight" | | 13 | "profound" | | 14 | "silence" | | 15 | "raced" |
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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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "managed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1015 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 11.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 756 | | uniqueNames | 9 | | maxNameDensity | 2.78 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 2 | | Lucien | 14 | | Moreau | 1 | | Frenchman | 1 | | Aurora | 21 | | Unbidden | 1 | | Ptolemy | 2 | | Evan | 3 | | Holding | 1 |
| | persons | | 0 | "Eva" | | 1 | "Lucien" | | 2 | "Moreau" | | 3 | "Aurora" | | 4 | "Ptolemy" | | 5 | "Evan" | | 6 | "Holding" |
| | places | (empty) | | globalScore | 0.111 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.985 | | wordCount | 1015 | | matches | | 0 | "neither could deny nor" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 19.52 | | std | 12.42 | | cv | 0.637 | | sampleLengths | | 0 | 31 | | 1 | 7 | | 2 | 1 | | 3 | 41 | | 4 | 21 | | 5 | 22 | | 6 | 11 | | 7 | 25 | | 8 | 28 | | 9 | 12 | | 10 | 30 | | 11 | 8 | | 12 | 26 | | 13 | 32 | | 14 | 31 | | 15 | 5 | | 16 | 7 | | 17 | 46 | | 18 | 6 | | 19 | 27 | | 20 | 36 | | 21 | 5 | | 22 | 28 | | 23 | 36 | | 24 | 6 | | 25 | 24 | | 26 | 17 | | 27 | 6 | | 28 | 33 | | 29 | 7 | | 30 | 6 | | 31 | 41 | | 32 | 5 | | 33 | 22 | | 34 | 32 | | 35 | 11 | | 36 | 16 | | 37 | 21 | | 38 | 39 | | 39 | 4 | | 40 | 1 | | 41 | 38 | | 42 | 8 | | 43 | 18 | | 44 | 33 | | 45 | 11 | | 46 | 2 | | 47 | 22 | | 48 | 10 | | 49 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 144 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 104 | | ratio | 0.058 | | matches | | 0 | "From the corner of her eye, Aurora caught a shadow moving behind him—a tabby cat." | | 1 | "Lost in his dual-coloured gaze, she saw echoes of the nights they shared—intense, passionate, heartbreakingly beautiful." | | 2 | "The touch—light and familiar—had Aurora blinking away the sudden moisture in her eyes." | | 3 | "A small laugh escaped Aurora's lips—Ptolemy always knew how to lighten tense situations." | | 4 | "The bottle of whiskey emerged next—a relic from more cheerful days." | | 5 | "Aurora's heart pounded faster as her mind raced—Evan?" |
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| 92.49% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 767 | | adjectiveStacks | 1 | | stackExamples | | 0 | "old crescent-shaped scar" |
| | adverbCount | 32 | | adverbRatio | 0.041720990873533245 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.01564537157757497 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 9.76 | | std | 5.55 | | cv | 0.569 | | sampleLengths | | 0 | 12 | | 1 | 8 | | 2 | 2 | | 3 | 9 | | 4 | 7 | | 5 | 1 | | 6 | 15 | | 7 | 1 | | 8 | 7 | | 9 | 18 | | 10 | 21 | | 11 | 14 | | 12 | 8 | | 13 | 6 | | 14 | 5 | | 15 | 18 | | 16 | 7 | | 17 | 3 | | 18 | 15 | | 19 | 10 | | 20 | 12 | | 21 | 21 | | 22 | 9 | | 23 | 8 | | 24 | 7 | | 25 | 19 | | 26 | 5 | | 27 | 1 | | 28 | 16 | | 29 | 10 | | 30 | 18 | | 31 | 13 | | 32 | 5 | | 33 | 7 | | 34 | 21 | | 35 | 11 | | 36 | 14 | | 37 | 6 | | 38 | 14 | | 39 | 13 | | 40 | 19 | | 41 | 7 | | 42 | 10 | | 43 | 5 | | 44 | 14 | | 45 | 14 | | 46 | 3 | | 47 | 21 | | 48 | 12 | | 49 | 6 |
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| 80.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5 | | totalSentences | 104 | | uniqueOpeners | 52 | |
| 49.75% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 67 | | matches | | 0 | "Instead, she found herself face-to-face" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 67 | | matches | | 0 | "Her grip tightened around the" | | 1 | "he murmured, his heterochromatic eyes" | | 2 | "He tilted his head, studying" | | 3 | "She crossed her arms, a" | | 4 | "His lean frame seemed to" | | 5 | "he continued, voice steady" | | 6 | "She turned sharply, pacing to" | | 7 | "She missed that chaotic simplicity" | | 8 | "He chuckled, a gravelly sound" | | 9 | "She looked at him, the" | | 10 | "His step closer had her" | | 11 | "She shook her head slowly." | | 12 | "He raised his hand, and" | | 13 | "She stepped back." | | 14 | "He pointed behind her, where" | | 15 | "He reached for one of" | | 16 | "She trailed off, renewing the" | | 17 | "Their history haunted every exchanged" | | 18 | "She couldn't trust him, yet" | | 19 | "She remembered the times he" |
| | ratio | 0.299 | |
| 42.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 67 | | matches | | 0 | "Aurora yanked the door open," | | 1 | "Her grip tightened around the" | | 2 | "he murmured, his heterochromatic eyes" | | 3 | "The door to Eva's flat" | | 4 | "The room was a research" | | 5 | "Aurora's voice was sharp, the" | | 6 | "He tilted his head, studying" | | 7 | "Aurora's skepticism was a fortress" | | 8 | "Lucien's cane clicked against the" | | 9 | "Aurora's lips thinned." | | 10 | "Memories flickered: heated arguments, promises" | | 11 | "She crossed her arms, a" | | 12 | "His lean frame seemed to" | | 13 | "The word tasted bitter on" | | 14 | "he continued, voice steady" | | 15 | "Aurora's heart skipped a beat." | | 16 | "Lucien's gaze flickered to her" | | 17 | "Aurora felt exposed, as if" | | 18 | "Aurora regretted speaking aloud as" | | 19 | "A mix that confused her," |
| | ratio | 0.836 | |
| 74.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 67 | | matches | | 0 | "Now beside the table, Lucien" |
| | ratio | 0.015 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 1 | | matches | | 0 | "Aurora regretted speaking aloud as soon as she saw a smirk curve on Lucien’s lips, resembling both mockery and deep understanding." |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "he murmured, his heterochromatic eyes unreadable" | | 1 | "he continued, voice steady" | | 2 | "Lucien offered, his glass clinking against hers" |
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| 41.30% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 5 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "he continued (continue)" | | 2 | "Aurora agreed (agree)" | | 3 | "Lucien asserted (assert)" | | 4 | "he agreed (agree)" |
| | dialogueSentences | 46 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0.833 | | effectiveRatio | 0.217 | |