| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.081 | | leniency | 0.162 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 629 | | 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) | |
| 20.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 629 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "pulse" | | 1 | "charged" | | 2 | "unspoken" | | 3 | "tension" | | 4 | "stomach" | | 5 | "tracing" | | 6 | "flicked" | | 7 | "weight" | | 8 | "unreadable" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "sent a shiver through" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 46 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 46 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 80 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 626 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 42.01% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 463 | | uniqueNames | 3 | | maxNameDensity | 2.16 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Lucien" | | discoveredNames | | | persons | | 0 | "Lucien" | | 1 | "Aurora" | | 2 | "Ptolemy" |
| | places | (empty) | | globalScore | 0.42 | | windowScore | 0.667 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 29 | | glossingSentenceCount | 1 | | matches | | 0 | "as if sensing the storm brewing" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 626 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 80 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 14.9 | | std | 15.52 | | cv | 1.042 | | sampleLengths | | 0 | 49 | | 1 | 5 | | 2 | 52 | | 3 | 8 | | 4 | 4 | | 5 | 36 | | 6 | 5 | | 7 | 46 | | 8 | 9 | | 9 | 7 | | 10 | 6 | | 11 | 23 | | 12 | 10 | | 13 | 3 | | 14 | 12 | | 15 | 8 | | 16 | 4 | | 17 | 53 | | 18 | 33 | | 19 | 8 | | 20 | 2 | | 21 | 2 | | 22 | 3 | | 23 | 15 | | 24 | 7 | | 25 | 10 | | 26 | 22 | | 27 | 7 | | 28 | 57 | | 29 | 9 | | 30 | 4 | | 31 | 6 | | 32 | 16 | | 33 | 6 | | 34 | 15 | | 35 | 7 | | 36 | 7 | | 37 | 3 | | 38 | 1 | | 39 | 8 | | 40 | 26 | | 41 | 12 |
| |
| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 46 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 81 | | matches | (empty) | |
| 35.71% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 80 | | ratio | 0.038 | | matches | | 0 | "The flat was too quiet—no cat to mewl, no distant hum of the kitchen." | | 1 | "The flat smelled of something faintly metallic—old wine, maybe, or the faintest trace of something darker." | | 2 | "Aurora took a seat at the small kitchen table, her fingers tracing the scar on her wrist—the one that should’ve been healed long ago." |
| |
| 95.57% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 466 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.045064377682403435 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.01072961373390558 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 80 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 80 | | mean | 7.83 | | std | 6.09 | | cv | 0.779 | | sampleLengths | | 0 | 13 | | 1 | 13 | | 2 | 14 | | 3 | 9 | | 4 | 5 | | 5 | 25 | | 6 | 27 | | 7 | 8 | | 8 | 3 | | 9 | 1 | | 10 | 16 | | 11 | 14 | | 12 | 6 | | 13 | 3 | | 14 | 2 | | 15 | 3 | | 16 | 11 | | 17 | 24 | | 18 | 8 | | 19 | 9 | | 20 | 4 | | 21 | 3 | | 22 | 6 | | 23 | 15 | | 24 | 8 | | 25 | 7 | | 26 | 3 | | 27 | 3 | | 28 | 8 | | 29 | 4 | | 30 | 3 | | 31 | 5 | | 32 | 4 | | 33 | 3 | | 34 | 19 | | 35 | 13 | | 36 | 18 | | 37 | 24 | | 38 | 9 | | 39 | 6 | | 40 | 2 | | 41 | 2 | | 42 | 2 | | 43 | 3 | | 44 | 8 | | 45 | 7 | | 46 | 7 | | 47 | 3 | | 48 | 7 | | 49 | 9 |
| |
| 47.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.275 | | totalSentences | 80 | | uniqueOpeners | 22 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 46 | | matches | | 0 | "Just the creak of the" | | 1 | "Then the door swung open." | | 2 | "Just turned, his back to" | | 3 | "Instead, he reached for the" |
| | ratio | 0.087 | |
| 98.26% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 46 | | matches | | 0 | "He stood there, his tailored" | | 1 | "His amber eyes locked onto" | | 2 | "she said, voice tight" | | 3 | "His fingers brushed the doorknob," | | 4 | "He didn’t answer." | | 5 | "She followed, her heels clicking" | | 6 | "she said, voice low" | | 7 | "He spun, his cane raised" | | 8 | "He didn’t answer." | | 9 | "He poured two cups, the" | | 10 | "He set his cup down" | | 11 | "His gaze darkened." | | 12 | "She stood abruptly, her chair" | | 13 | "She turned away, her fingers" |
| | ratio | 0.304 | |
| 3.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 46 | | matches | | 0 | "The lock clicked with a" | | 1 | "Aurora pressed her back against" | | 2 | "The flat was too quiet—no" | | 3 | "He stood there, his tailored" | | 4 | "His amber eyes locked onto" | | 5 | "she said, voice tight" | | 6 | "Lucien didn’t flinch." | | 7 | "The flat smelled of something" | | 8 | "His fingers brushed the doorknob," | | 9 | "Aurora exhaled sharply." | | 10 | "He didn’t answer." | | 11 | "The flat’s single window was" | | 12 | "She followed, her heels clicking" | | 13 | "she said, voice low" | | 14 | "Lucien didn’t look back." | | 15 | "He spun, his cane raised" | | 16 | "A cold knot settled in" | | 17 | "The words tasted bitter" | | 18 | "Lucien’s jaw tightened." | | 19 | "He didn’t answer." |
| | ratio | 0.913 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 18 | | technicalSentenceCount | 4 | | matches | | 0 | "He stood there, his tailored suit already rumpled from the journey, his cane tapping against the floor like a metronome counting down to something inevitable." | | 1 | "His amber eyes locked onto hers, and for a heartbeat, the air between them thickened, charged with the same unspoken tension that had always lingered between th…" | | 2 | "The flat’s single window was dark, the only light coming from the streetlamps outside, casting long shadows that stretched like fingers across the floor." | | 3 | "The cat, Ptolemy, padded in from the hallway, his tail flicking as he sniffed the air, as if sensing the storm brewing." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, voice tight" | | 1 | "she said, voice low" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 37 | | tagDensity | 0.054 | | leniency | 0.108 | | rawRatio | 0 | | effectiveRatio | 0 | |