| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said finally [finally]" | | 1 | "she began again [again]" |
| | dialogueSentences | 24 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0.222 | | effectiveRatio | 0.167 | |
| 75.31% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 810 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | | 2 | | adverb | "barely above a whisper" | | count | 1 |
| | 3 | |
| | highlights | | 0 | "lightly" | | 1 | "really" | | 2 | "barely above a whisper" | | 3 | "gently" |
| |
| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 810 | | totalAiIsms | 23 | | found | | 0 | | word | "skipped a beat" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "down her spine" | | count | 1 |
| | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "skipped a beat" | | 1 | "familiar" | | 2 | "unspoken" | | 3 | "comforting" | | 4 | "chaotic" | | 5 | "testament" | | 6 | "weight" | | 7 | "down her spine" | | 8 | "silence" | | 9 | "tension" | | 10 | "encounter" | | 11 | "whisper" | | 12 | "charged" | | 13 | "electric" | | 14 | "intensity" | | 15 | "flicker" | | 16 | "warmth" | | 17 | "pounding" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "hung in the air" | | count | 1 |
| | 1 | | label | "sent a shiver through" | | count | 1 |
| | 2 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "hung in the air" | | 1 | "sent a shiver down" | | 2 | "a glimmer of hope" |
| |
| 87.96% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 45 | | matches | | 0 | "e with surprise" | | 1 | "a jolt of warmth" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 45 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 61 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 812 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 52.40% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 666 | | uniqueNames | 7 | | maxNameDensity | 1.95 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 2 | | Aurora | 13 | | Carter | 1 | | Moreau | 1 | | Lucien | 5 | | Books | 1 | | Ptolemy | 5 |
| | persons | | 0 | "Eva" | | 1 | "Aurora" | | 2 | "Carter" | | 3 | "Moreau" | | 4 | "Lucien" | | 5 | "Books" | | 6 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.524 | | windowScore | 0.833 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 1 | | matches | | 0 | "quite bring himself to say them" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 812 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 61 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 30.07 | | std | 15.22 | | cv | 0.506 | | sampleLengths | | 0 | 78 | | 1 | 23 | | 2 | 60 | | 3 | 15 | | 4 | 30 | | 5 | 50 | | 6 | 39 | | 7 | 17 | | 8 | 25 | | 9 | 17 | | 10 | 35 | | 11 | 15 | | 12 | 34 | | 13 | 37 | | 14 | 15 | | 15 | 16 | | 16 | 20 | | 17 | 49 | | 18 | 16 | | 19 | 32 | | 20 | 20 | | 21 | 19 | | 22 | 31 | | 23 | 28 | | 24 | 18 | | 25 | 43 | | 26 | 30 |
| |
| 97.47% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 45 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 108 | | matches | (empty) | |
| 96.02% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 61 | | ratio | 0.016 | | matches | | 0 | "Lucien Moreau leaned casually against the doorframe, his heterochromatic eyes — one amber, one black — studying her with an inscrutable expression." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 206 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.024271844660194174 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.009708737864077669 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 61 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 61 | | mean | 13.31 | | std | 6.57 | | cv | 0.493 | | sampleLengths | | 0 | 24 | | 1 | 12 | | 2 | 22 | | 3 | 20 | | 4 | 19 | | 5 | 4 | | 6 | 16 | | 7 | 20 | | 8 | 13 | | 9 | 11 | | 10 | 10 | | 11 | 5 | | 12 | 13 | | 13 | 17 | | 14 | 12 | | 15 | 23 | | 16 | 15 | | 17 | 14 | | 18 | 15 | | 19 | 10 | | 20 | 8 | | 21 | 9 | | 22 | 12 | | 23 | 8 | | 24 | 5 | | 25 | 13 | | 26 | 4 | | 27 | 19 | | 28 | 16 | | 29 | 15 | | 30 | 14 | | 31 | 20 | | 32 | 24 | | 33 | 8 | | 34 | 5 | | 35 | 12 | | 36 | 3 | | 37 | 13 | | 38 | 3 | | 39 | 18 | | 40 | 2 | | 41 | 17 | | 42 | 32 | | 43 | 15 | | 44 | 1 | | 45 | 18 | | 46 | 14 | | 47 | 12 | | 48 | 8 | | 49 | 13 |
| |
| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.4098360655737705 | | totalSentences | 61 | | uniqueOpeners | 25 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 45 | | matches | | 0 | "Instead, she reached out, her" | | 1 | "Perhaps, she thought, they could" |
| | ratio | 0.044 | |
| 68.89% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 45 | | matches | | 0 | "She hadn't expected to see" | | 1 | "he said, his voice smooth" | | 2 | "She hadn't seen Lucien since" | | 3 | "She had left in a" | | 4 | "she replied, her voice steady" | | 5 | "He straightened, the ivory-handled cane" | | 6 | "she said finally, meeting his" | | 7 | "He smiled, a slow, knowing" | | 8 | "she asked, her voice barely" | | 9 | "He took a step closer," | | 10 | "she said, her voice tight" | | 11 | "She shook her head, the" | | 12 | "He reached out, his fingers" | | 13 | "she began, her voice trembling" | | 14 | "They stood in silence for" | | 15 | "she began again, but the" | | 16 | "He squeezed her hand gently," |
| | ratio | 0.378 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 45 | | matches | | 0 | "The door to Eva's flat" | | 1 | "She hadn't expected to see" | | 2 | "Lucien Moreau leaned casually against" | | 3 | "The dim light from the" | | 4 | "he said, his voice smooth" | | 5 | "Aurora's heart skipped a beat," | | 6 | "She hadn't seen Lucien since" | | 7 | "She had left in a" | | 8 | "she replied, her voice steady" | | 9 | "He straightened, the ivory-handled cane" | | 10 | "Aurora stepped inside, closing the" | | 11 | "The familiar scent of curry" | | 12 | "Ptolemy, the tabby cat, lounged" | | 13 | "Aurora admitted, glancing around at" | | 14 | "Books and papers were strewn" | | 15 | "Lucien nodded, his gaze never" | | 16 | "Aurora hesitated, the weight of" | | 17 | "she said finally, meeting his" | | 18 | "He smiled, a slow, knowing" | | 19 | "Silence stretched between them, filled" |
| | ratio | 0.867 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 4 | | matches | | 0 | "Silence stretched between them, filled with the unspoken words and unresolved tension that had lingered since their last encounter." | | 1 | "Aurora crossed her arms, trying to shield herself from the memories that threatened to overwhelm her." | | 2 | "He reached out, his fingers brushing against her arm, the contact sending a jolt of warmth through her." | | 3 | "Instead, she reached out, her fingers brushing against his, a tentative connection that spoke of hope and possibility." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 3 | | matches | | 0 | "she replied, her voice steady despite the turmoil within" | | 1 | "she asked, her voice barely above a whisper" | | 2 | "she said, her voice tight" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora admitted (admit)" |
| | dialogueSentences | 24 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.167 | | effectiveRatio | 0.083 | |