| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 47 | | tagDensity | 0.128 | | leniency | 0.255 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.43% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 946 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 20.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 946 | | totalAiIsms | 15 | | found | | 0 | | word | "skipped a beat" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | word | "down her spine" | | count | 1 |
| | 12 | |
| | highlights | | 0 | "skipped a beat" | | 1 | "intensity" | | 2 | "tinged" | | 3 | "eyebrow" | | 4 | "unspoken" | | 5 | "weight" | | 6 | "resolve" | | 7 | "race" | | 8 | "tension" | | 9 | "familiar" | | 10 | "charged" | | 11 | "down her spine" | | 12 | "pounding" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
| | 2 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "sent a shiver down" | | 2 | "a glimmer of hope" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 56 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 56 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 97 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 947 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 32.46% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 553 | | uniqueNames | 4 | | maxNameDensity | 2.35 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 1 | | Aurora | 13 | | Lucien | 6 | | Moreau | 1 |
| | persons | | 0 | "Eva" | | 1 | "Aurora" | | 2 | "Lucien" | | 3 | "Moreau" |
| | places | (empty) | | globalScore | 0.325 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | 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 | 947 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 97 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 20.59 | | std | 12.57 | | cv | 0.611 | | sampleLengths | | 0 | 53 | | 1 | 16 | | 2 | 25 | | 3 | 44 | | 4 | 20 | | 5 | 21 | | 6 | 5 | | 7 | 15 | | 8 | 8 | | 9 | 10 | | 10 | 30 | | 11 | 23 | | 12 | 16 | | 13 | 13 | | 14 | 14 | | 15 | 2 | | 16 | 10 | | 17 | 24 | | 18 | 10 | | 19 | 7 | | 20 | 17 | | 21 | 17 | | 22 | 23 | | 23 | 15 | | 24 | 21 | | 25 | 34 | | 26 | 9 | | 27 | 34 | | 28 | 28 | | 29 | 15 | | 30 | 17 | | 31 | 28 | | 32 | 7 | | 33 | 25 | | 34 | 32 | | 35 | 37 | | 36 | 23 | | 37 | 11 | | 38 | 19 | | 39 | 10 | | 40 | 31 | | 41 | 26 | | 42 | 19 | | 43 | 15 | | 44 | 2 | | 45 | 66 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 56 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 103 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 97 | | ratio | 0.01 | | matches | | 0 | "His slicked-back platinum blond hair gleamed under the dim hallway light, and his heterochromatic eyes — one amber, one black — locked onto hers with an intensity that made her breath catch." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 553 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.02531645569620253 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0018083182640144665 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 97 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 97 | | mean | 9.76 | | std | 6.34 | | cv | 0.649 | | sampleLengths | | 0 | 13 | | 1 | 8 | | 2 | 32 | | 3 | 16 | | 4 | 13 | | 5 | 6 | | 6 | 6 | | 7 | 6 | | 8 | 15 | | 9 | 23 | | 10 | 10 | | 11 | 10 | | 12 | 11 | | 13 | 10 | | 14 | 3 | | 15 | 2 | | 16 | 15 | | 17 | 4 | | 18 | 4 | | 19 | 7 | | 20 | 3 | | 21 | 14 | | 22 | 8 | | 23 | 8 | | 24 | 15 | | 25 | 8 | | 26 | 13 | | 27 | 3 | | 28 | 10 | | 29 | 3 | | 30 | 12 | | 31 | 2 | | 32 | 2 | | 33 | 3 | | 34 | 7 | | 35 | 8 | | 36 | 16 | | 37 | 8 | | 38 | 2 | | 39 | 7 | | 40 | 9 | | 41 | 8 | | 42 | 8 | | 43 | 9 | | 44 | 23 | | 45 | 3 | | 46 | 12 | | 47 | 7 | | 48 | 14 | | 49 | 10 |
| |
| 64.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.3917525773195876 | | totalSentences | 97 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 5.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 56 | | matches | | 0 | "His slicked-back platinum blond hair" | | 1 | "she managed, her voice a" | | 2 | "he replied, his tone smooth" | | 3 | "He held up a small" | | 4 | "She stepped back, letting him" | | 5 | "She folded her arms, a" | | 6 | "She raised an eyebrow." | | 7 | "he said, his voice steady" | | 8 | "She needed a moment to" | | 9 | "She sipped her water, the" | | 10 | "He took a step closer," | | 11 | "She set the glass down," | | 12 | "He sighed, the sound heavy" | | 13 | "She turned away, her hands" | | 14 | "He held up a hand," | | 15 | "She laughed, a bitter, hollow" | | 16 | "He took another step closer," | | 17 | "He hesitated, then seemed to" | | 18 | "She bit her lip, a" | | 19 | "he said, his voice thick" |
| | ratio | 0.536 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 56 | | matches | | 0 | "The door to Eva's flat" | | 1 | "There, standing in the threshold," | | 2 | "His slicked-back platinum blond hair" | | 3 | "she managed, her voice a" | | 4 | "he replied, his tone smooth" | | 5 | "He held up a small" | | 6 | "She stepped back, letting him" | | 7 | "The flat was as cluttered" | | 8 | "Ptolemy, the tabby cat, meowed" | | 9 | "Aurora asked, closing the door" | | 10 | "She folded her arms, a" | | 11 | "Lucien glanced around the room," | | 12 | "Aurora's curiosity piqued." | | 13 | "She raised an eyebrow." | | 14 | "he said, his voice steady" | | 15 | "Aurora crossed the room to" | | 16 | "She needed a moment to" | | 17 | "Lucien leaned against the doorframe," | | 18 | "She sipped her water, the" | | 19 | "He took a step closer," |
| | ratio | 0.946 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 56 | | matches | (empty) | | ratio | 0 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 2 | | matches | | 0 | "His slicked-back platinum blond hair gleamed under the dim hallway light, and his heterochromatic eyes — one amber, one black — locked onto hers with an intensi…" | | 1 | "Lucien chuckled, a sound that sent a shiver down her spine." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 3 | | matches | | 0 | "he replied, his tone smooth but tinged with a note of caution" | | 1 | "he said, his voice steady" | | 2 | "he said, his voice thick with regret" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 47 | | tagDensity | 0.106 | | leniency | 0.213 | | rawRatio | 0.2 | | effectiveRatio | 0.043 | |