| 50.75% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 29 | | adverbTagCount | 5 | | adverbTags | | 0 | "Rory gestured vaguely [vaguely]" | | 1 | "Lila's voice hardened slightly [slightly]" | | 2 | "Lila gestured around [around]" | | 3 | "she corrected automatically [automatically]" | | 4 | "Silas asked softly [softly]" |
| | dialogueSentences | 67 | | tagDensity | 0.433 | | leniency | 0.866 | | rawRatio | 0.172 | | effectiveRatio | 0.149 | |
| 50.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1016 | | totalAiIsmAdverbs | 10 | | found | | | highlights | | 0 | "slowly" | | 1 | "slightly" | | 2 | "perfectly" | | 3 | "suddenly" | | 4 | "completely" | | 5 | "carefully" | | 6 | "softly" |
| |
| 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) | |
| 45.87% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1016 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "weight" | | 2 | "warmth" | | 3 | "pristine" | | 4 | "flicker" | | 5 | "unreadable" | | 6 | "tracing" | | 7 | "charm" | | 8 | "constructed" | | 9 | "perfect" | | 10 | "silence" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 63 | | matches | (empty) | |
| 97.51% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1013 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 644 | | uniqueNames | 8 | | maxNameDensity | 2.64 | | worstName | "Lila" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Lila" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Rory | 14 | | Lila | 17 | | Silas | 8 | | Evan | 1 | | London | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Rory" | | 4 | "Lila" | | 5 | "Silas" | | 6 | "Evan" |
| | places | | | globalScore | 0.18 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1013 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 18.09 | | std | 10.81 | | cv | 0.598 | | sampleLengths | | 0 | 53 | | 1 | 2 | | 2 | 27 | | 3 | 12 | | 4 | 28 | | 5 | 10 | | 6 | 1 | | 7 | 24 | | 8 | 4 | | 9 | 27 | | 10 | 26 | | 11 | 22 | | 12 | 43 | | 13 | 11 | | 14 | 18 | | 15 | 18 | | 16 | 19 | | 17 | 14 | | 18 | 17 | | 19 | 13 | | 20 | 13 | | 21 | 7 | | 22 | 12 | | 23 | 21 | | 24 | 12 | | 25 | 19 | | 26 | 4 | | 27 | 16 | | 28 | 19 | | 29 | 30 | | 30 | 12 | | 31 | 24 | | 32 | 25 | | 33 | 31 | | 34 | 8 | | 35 | 34 | | 36 | 7 | | 37 | 22 | | 38 | 26 | | 39 | 11 | | 40 | 7 | | 41 | 18 | | 42 | 20 | | 43 | 16 | | 44 | 10 | | 45 | 14 | | 46 | 3 | | 47 | 26 | | 48 | 8 | | 49 | 20 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 95.83% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 128 | | matches | | 0 | "was pretending" | | 1 | "was sliding" |
| |
| 85.14% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 99 | | ratio | 0.02 | | matches | | 0 | "The memory of Evan's hand on her throat, the way he'd smile and apologize afterward, the carefully constructed lies she'd told everyone—including Lila—about their 'perfect' relationship." | | 1 | "As she climbed the stairs to her flat above the bar, Rory wondered if Lila ever thought about the girl she'd been—the one who'd wanted to change the world, who'd believed words could make a difference." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 519 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.038535645472061654 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.019267822736030827 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 10.23 | | std | 5.81 | | cv | 0.568 | | sampleLengths | | 0 | 17 | | 1 | 15 | | 2 | 21 | | 3 | 2 | | 4 | 17 | | 5 | 10 | | 6 | 9 | | 7 | 3 | | 8 | 26 | | 9 | 2 | | 10 | 10 | | 11 | 1 | | 12 | 15 | | 13 | 9 | | 14 | 4 | | 15 | 20 | | 16 | 7 | | 17 | 12 | | 18 | 14 | | 19 | 14 | | 20 | 8 | | 21 | 7 | | 22 | 16 | | 23 | 9 | | 24 | 11 | | 25 | 11 | | 26 | 11 | | 27 | 7 | | 28 | 15 | | 29 | 3 | | 30 | 9 | | 31 | 4 | | 32 | 6 | | 33 | 14 | | 34 | 17 | | 35 | 12 | | 36 | 1 | | 37 | 7 | | 38 | 6 | | 39 | 7 | | 40 | 11 | | 41 | 1 | | 42 | 15 | | 43 | 6 | | 44 | 12 | | 45 | 13 | | 46 | 6 | | 47 | 4 | | 48 | 8 | | 49 | 8 |
| |
| 89.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.5555555555555556 | | totalSentences | 99 | | uniqueOpeners | 55 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 61 | | matches | | 0 | "His hazel eyes narrowed slightly" | | 1 | "She slid onto a stool," | | 2 | "He reached for a bottle" | | 3 | "His silver signet ring glinted" | | 4 | "He leaned against the bar," | | 5 | "She took a sip, the" | | 6 | "His gaze drifted to the" | | 7 | "Her designer coat was pristine," | | 8 | "She glanced at Silas." | | 9 | "She stood, pulling her coat" | | 10 | "she corrected automatically" | | 11 | "They'd both changed, but only" | | 12 | "she said, standing" |
| | ratio | 0.213 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 61 | | matches | | 0 | "The green neon sign of" | | 1 | "Aurora Carter straightened her delivery" | | 2 | "The man behind the bar" | | 3 | "His hazel eyes narrowed slightly" | | 4 | "Silas placed a glass down" | | 5 | "She slid onto a stool," | | 6 | "He reached for a bottle" | | 7 | "The glass clinked as he" | | 8 | "His silver signet ring glinted" | | 9 | "He leaned against the bar," | | 10 | "She took a sip, the" | | 11 | "His gaze drifted to the" | | 12 | "Rory turned, following his line" | | 13 | "The woman who entered moved" | | 14 | "Her designer coat was pristine," | | 15 | "The name escaped her lips" | | 16 | "The woman paused, a flicker" | | 17 | "Rory stood, the distance between" | | 18 | "Lila's smile didn't reach her" | | 19 | "She glanced at Silas." |
| | ratio | 0.934 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 56.03% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 29 | | uselessAdditionCount | 4 | | matches | | 0 | "She slid, her fingers brushing the crescent scar on her left wrist" | | 1 | "She took, the warmth spreading through her chest" | | 2 | "His gaze drifted, his expression shifting" | | 3 | "Lila shot back, her composure finally cracking" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "she corrected automatically (correct)" |
| | dialogueSentences | 67 | | tagDensity | 0.075 | | leniency | 0.149 | | rawRatio | 0.2 | | effectiveRatio | 0.03 | |