| 41.27% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 5 | | adverbTags | | 0 | "he interrupted smoothly [smoothly]" | | 1 | "he repeated quietly [quietly]" | | 2 | "Lucien said wryly [wryly]" | | 3 | "Lucien said simply [simply]" | | 4 | "he said softly [softly]" |
| | dialogueSentences | 63 | | tagDensity | 0.381 | | leniency | 0.762 | | rawRatio | 0.208 | | effectiveRatio | 0.159 | |
| 63.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1361 | | totalAiIsmAdverbs | 10 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "barely above a whisper" | | count | 1 |
|
| | highlights | | 0 | "sharply" | | 1 | "carefully" | | 2 | "softly" | | 3 | "quickly" | | 4 | "slightly" | | 5 | "barely above a whisper" |
| |
| 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) | |
| 11.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1361 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "rhythmic" | | 1 | "stomach" | | 2 | "aftermath" | | 3 | "unreadable" | | 4 | "calculating" | | 5 | "eyebrow" | | 6 | "predator" | | 7 | "familiar" | | 8 | "weight" | | 9 | "grave" | | 10 | "echoed" | | 11 | "tinged" | | 12 | "flicker" | | 13 | "intensity" | | 14 | "measured" | | 15 | "silence" | | 16 | "unspoken" | | 17 | "racing" | | 18 | "charm" | | 19 | "whisper" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "stomach dropped" | | 1 | "sent a jolt through" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 136 | | 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 | 1 | | markdownWords | 2 | | totalWords | 1371 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 31 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1002 | | uniqueNames | 7 | | maxNameDensity | 2 | | worstName | "Lucien" | | maxWindowNameDensity | 5 | | worstWindowName | "Lucien" | | discoveredNames | | Rory | 19 | | Eva | 4 | | Ptolemy | 4 | | Moreau | 1 | | Blackwell | 1 | | Lucien | 20 | | French | 1 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Moreau" | | 4 | "Lucien" |
| | places | (empty) | | globalScore | 0.502 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.729 | | wordCount | 1371 | | matches | | 0 | "Not unless Eva had forgotten her keys again, but her friend usually texted first" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 136 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 23.64 | | std | 15.68 | | cv | 0.663 | | sampleLengths | | 0 | 66 | | 1 | 51 | | 2 | 76 | | 3 | 56 | | 4 | 38 | | 5 | 26 | | 6 | 29 | | 7 | 8 | | 8 | 18 | | 9 | 49 | | 10 | 32 | | 11 | 20 | | 12 | 31 | | 13 | 7 | | 14 | 26 | | 15 | 6 | | 16 | 27 | | 17 | 29 | | 18 | 29 | | 19 | 7 | | 20 | 16 | | 21 | 19 | | 22 | 24 | | 23 | 36 | | 24 | 12 | | 25 | 8 | | 26 | 9 | | 27 | 41 | | 28 | 11 | | 29 | 38 | | 30 | 50 | | 31 | 42 | | 32 | 9 | | 33 | 34 | | 34 | 15 | | 35 | 35 | | 36 | 10 | | 37 | 17 | | 38 | 26 | | 39 | 9 | | 40 | 16 | | 41 | 17 | | 42 | 2 | | 43 | 11 | | 44 | 15 | | 45 | 11 | | 46 | 23 | | 47 | 16 | | 48 | 9 | | 49 | 21 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 97 | | matches | (empty) | |
| 96.91% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 194 | | matches | | 0 | "was settling" | | 1 | "wasn’t expecting" | | 2 | "was like reopening" |
| |
| 16.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 136 | | ratio | 0.044 | | matches | | 0 | "It was after ten — too late for a friendly visit, and she wasn’t expecting anyone." | | 1 | "Setting the mug down on the cluttered coffee table — next to a stack of Eva’s research notes — Rory padded to the door, her bare feet silent against the worn wood floor." | | 2 | "Even through the distorted fisheye lens of the peephole, his mismatched eyes — one amber, one black — seemed to pierce right through her." | | 3 | "It wasn’t like Lucien to make unannounced visits — he was meticulous, calculating." | | 4 | "There was none — only a quiet intensity that made her chest ache." | | 5 | "Avaros — Lucien’s father’s realm." |
| |
| 93.75% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 995 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.04321608040201005 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.024120603015075376 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 136 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 136 | | mean | 10.08 | | std | 6.28 | | cv | 0.623 | | sampleLengths | | 0 | 22 | | 1 | 14 | | 2 | 16 | | 3 | 14 | | 4 | 33 | | 5 | 9 | | 6 | 9 | | 7 | 16 | | 8 | 19 | | 9 | 17 | | 10 | 24 | | 11 | 3 | | 12 | 23 | | 13 | 23 | | 14 | 4 | | 15 | 3 | | 16 | 6 | | 17 | 6 | | 18 | 13 | | 19 | 9 | | 20 | 4 | | 21 | 7 | | 22 | 14 | | 23 | 5 | | 24 | 18 | | 25 | 7 | | 26 | 4 | | 27 | 4 | | 28 | 4 | | 29 | 17 | | 30 | 1 | | 31 | 18 | | 32 | 12 | | 33 | 19 | | 34 | 16 | | 35 | 16 | | 36 | 15 | | 37 | 5 | | 38 | 9 | | 39 | 18 | | 40 | 4 | | 41 | 2 | | 42 | 5 | | 43 | 13 | | 44 | 13 | | 45 | 3 | | 46 | 3 | | 47 | 9 | | 48 | 18 | | 49 | 3 |
| |
| 63.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3897058823529412 | | totalSentences | 136 | | uniqueOpeners | 53 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 57.36% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 37 | | totalSentences | 91 | | matches | | 0 | "She froze, mug of tea" | | 1 | "It was after ten —" | | 2 | "She peered through the peephole" | | 3 | "He looked as impeccable as" | | 4 | "It had been six months" | | 5 | "She still remembered the way" | | 6 | "She hadn’t reached out." | | 7 | "Her fingers hovered over the" | | 8 | "She could pretend she wasn’t" | | 9 | "It wasn’t like Lucien to" | | 10 | "he called, his voice smooth" | | 11 | "She exhaled sharply and unlocked" | | 12 | "she said, her tone carefully" | | 13 | "He raised an eyebrow." | | 14 | "She hesitated, her gaze darting" | | 15 | "He crossed the threshold with" | | 16 | "he remarked, his gaze lingering" | | 17 | "he interrupted smoothly, turning to" | | 18 | "His lips quirked in a" | | 19 | "she asked, already dreading the" |
| | ratio | 0.407 | |
| 20.44% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 91 | | matches | | 0 | "The knock came just as" | | 1 | "She froze, mug of tea" | | 2 | "It was after ten —" | | 3 | "The cat, Ptolemy, lounged on" | | 4 | "She peered through the peephole" | | 5 | "Lucien Moreau stood on the" | | 6 | "He looked as impeccable as" | | 7 | "Rory’s stomach twisted." | | 8 | "It had been six months" | | 9 | "She still remembered the way" | | 10 | "She hadn’t reached out." | | 11 | "Neither had he." | | 12 | "Her fingers hovered over the" | | 13 | "She could pretend she wasn’t" | | 14 | "It wasn’t like Lucien to" | | 15 | "The knock came again, sharper" | | 16 | "he called, his voice smooth" | | 17 | "She exhaled sharply and unlocked" | | 18 | "she said, her tone carefully" | | 19 | "He raised an eyebrow." |
| | ratio | 0.879 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 91 | | matches | | 0 | "Even through the distorted fisheye" | | 1 | "If he was here, it" |
| | ratio | 0.022 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 7 | | matches | | 0 | "she said, her tone carefully neutral" | | 1 | "Rory crossed, her tone sharper than she intended" | | 2 | "he interrupted smoothly, turning to face her" | | 3 | "Lucien said, his voice low" | | 4 | "she said, her voice steadier than she felt" | | 5 | "he asked, his voice barely above a whisper" | | 6 | "she said, her voice strained" |
| |
| 54.76% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 20 | | fancyCount | 6 | | fancyTags | | 0 | "he interrupted smoothly (interrupt)" | | 1 | "Lucien assured (assure)" | | 2 | "he repeated quietly (repeat)" | | 3 | "he murmured (murmur)" | | 4 | "Lucien explained (explain)" | | 5 | "he admitted (admit)" |
| | dialogueSentences | 63 | | tagDensity | 0.317 | | leniency | 0.635 | | rawRatio | 0.3 | | effectiveRatio | 0.19 | |