| 94.74% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "he replied firmly [firmly]" | | 1 | "Lucien began softly [softly]" |
| | dialogueSentences | 38 | | tagDensity | 0.342 | | leniency | 0.684 | | rawRatio | 0.154 | | effectiveRatio | 0.105 | |
| 43.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1145 | | totalAiIsmAdverbs | 13 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | adverb | "passionately" | | count | 1 |
| | 8 | |
| | highlights | | 0 | "lazily" | | 1 | "slightly" | | 2 | "really" | | 3 | "slowly" | | 4 | "gently" | | 5 | "carefully" | | 6 | "softly" | | 7 | "passionately" | | 8 | "very" |
| |
| 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 | 1145 | | totalAiIsms | 26 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "unspoken" | | 3 | "warmth" | | 4 | "scanned" | | 5 | "familiar" | | 6 | "intriguing" | | 7 | "pulse" | | 8 | "quickened" | | 9 | "weight" | | 10 | "navigate" | | 11 | "complex" | | 12 | "tension" | | 13 | "firmly" | | 14 | "whisper" | | 15 | "intensity" | | 16 | "sense of" | | 17 | "perfect" | | 18 | "fascinating" | | 19 | "silence" | | 20 | "comfortable" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
|
| | highlights | | 0 | "heart pounded in her chest" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 62 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 62 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1140 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 65.15% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 825 | | uniqueNames | 7 | | maxNameDensity | 1.7 | | worstName | "Aurora" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 3 | | Brick | 2 | | Lane | 2 | | Aurora | 14 | | Despite | 1 | | Lucien | 8 | | Ptolemy | 3 |
| | persons | | | places | | | globalScore | 0.652 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1140 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 93.96% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 26.51 | | std | 12.7 | | cv | 0.479 | | sampleLengths | | 0 | 60 | | 1 | 48 | | 2 | 23 | | 3 | 18 | | 4 | 38 | | 5 | 24 | | 6 | 29 | | 7 | 40 | | 8 | 34 | | 9 | 24 | | 10 | 16 | | 11 | 16 | | 12 | 23 | | 13 | 29 | | 14 | 50 | | 15 | 19 | | 16 | 33 | | 17 | 27 | | 18 | 26 | | 19 | 40 | | 20 | 10 | | 21 | 26 | | 22 | 36 | | 23 | 12 | | 24 | 33 | | 25 | 15 | | 26 | 20 | | 27 | 14 | | 28 | 10 | | 29 | 30 | | 30 | 9 | | 31 | 14 | | 32 | 32 | | 33 | 33 | | 34 | 18 | | 35 | 30 | | 36 | 13 | | 37 | 23 | | 38 | 36 | | 39 | 33 | | 40 | 12 | | 41 | 58 | | 42 | 6 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 62 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 147 | | matches | | 0 | "was standing" | | 1 | "were making" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 86 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 828 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.035024154589371984 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.018115942028985508 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 13.26 | | std | 6.25 | | cv | 0.472 | | sampleLengths | | 0 | 22 | | 1 | 23 | | 2 | 15 | | 3 | 10 | | 4 | 22 | | 5 | 16 | | 6 | 12 | | 7 | 11 | | 8 | 13 | | 9 | 5 | | 10 | 20 | | 11 | 18 | | 12 | 21 | | 13 | 3 | | 14 | 15 | | 15 | 14 | | 16 | 26 | | 17 | 14 | | 18 | 26 | | 19 | 8 | | 20 | 6 | | 21 | 18 | | 22 | 13 | | 23 | 3 | | 24 | 10 | | 25 | 6 | | 26 | 12 | | 27 | 11 | | 28 | 9 | | 29 | 20 | | 30 | 13 | | 31 | 13 | | 32 | 10 | | 33 | 14 | | 34 | 11 | | 35 | 8 | | 36 | 17 | | 37 | 16 | | 38 | 20 | | 39 | 7 | | 40 | 16 | | 41 | 10 | | 42 | 20 | | 43 | 20 | | 44 | 10 | | 45 | 13 | | 46 | 13 | | 47 | 17 | | 48 | 19 | | 49 | 5 |
| |
| 77.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.47674418604651164 | | totalSentences | 86 | | uniqueOpeners | 41 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Still, seeing him now, she" |
| | ratio | 0.017 | |
| 46.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 60 | | matches | | 0 | "She didn't like showing up" | | 1 | "It had been months since" | | 2 | "she replied, attempting to keep" | | 3 | "His lips curled into a" | | 4 | "She scoffed, trying to ignore" | | 5 | "His smile faded slightly, replaced" | | 6 | "She looked away, unsure how" | | 7 | "They had once been close," | | 8 | "she said, her voice quieter" | | 9 | "He sighed and ran a" | | 10 | "he replied firmly, closing the" | | 11 | "She wanted to reach out," | | 12 | "Her voice was barely a" | | 13 | "he replied, gently but with" | | 14 | "She hesitated, then nodded, a" | | 15 | "He extended his hand, and" | | 16 | "His fingers were warm and" | | 17 | "he asked, leading her to" | | 18 | "she replied, feeling the tension" | | 19 | "He chuckled softly." |
| | ratio | 0.433 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 60 | | matches | | 0 | "Aurora's heart pounded in her" | | 1 | "The night had turned chilly," | | 2 | "The streets were quiet, the" | | 3 | "She didn't like showing up" | | 4 | "Moments later, the door opened" | | 5 | "A pair of heterochromatic eyes," | | 6 | "Lucien said, surprise flickering across" | | 7 | "It had been months since" | | 8 | "she replied, attempting to keep" | | 9 | "Lucien unhooked the chain and" | | 10 | "Aurora walked past him into" | | 11 | "Ptolemy, the tabby cat, meowed" | | 12 | "Aurora turned to face Lucien," | | 13 | "His lips curled into a" | | 14 | "She scoffed, trying to ignore" | | 15 | "His smile faded slightly, replaced" | | 16 | "Aurora exhaled slowly, the weight" | | 17 | "Lucien's gaze softened, and he" | | 18 | "She looked away, unsure how" | | 19 | "They had once been close," |
| | ratio | 0.867 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, her voice quieter" | | 1 | "Aurora crossed, her eyes searching his face" | | 2 | "she said, trying to steer the conversation to safer ground" |
| |
| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 2 | | fancyTags | | 0 | "she admitted (admit)" | | 1 | "she noted (note)" |
| | dialogueSentences | 38 | | tagDensity | 0.263 | | leniency | 0.526 | | rawRatio | 0.2 | | effectiveRatio | 0.105 | |