| 51.85% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said softly [softly]" | | 1 | "she asked hoarsely [hoarsely]" |
| | dialogueSentences | 27 | | tagDensity | 0.481 | | leniency | 0.963 | | rawRatio | 0.154 | | effectiveRatio | 0.148 | |
| 77.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 674 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "reluctantly" | | count | 1 |
|
| | highlights | | 0 | "wickedly" | | 1 | "softly" | | 2 | "reluctantly" |
| |
| 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) | |
| 25.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 674 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "silence" | | 1 | "gleaming" | | 2 | "searing" | | 3 | "familiar" | | 4 | "footsteps" | | 5 | "jaw clenched" | | 6 | "chill" | | 7 | "raced" | | 8 | "flickered" | | 9 | "shattered" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 667 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 72.48% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 516 | | uniqueNames | 6 | | maxNameDensity | 1.55 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 8 | | Wednesday | 1 | | Moreau | 1 | | Remorse | 1 | | Relief | 1 | | Lucien | 3 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Remorse" | | 3 | "Relief" | | 4 | "Lucien" |
| | places | (empty) | | globalScore | 0.725 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | 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 | 667 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 59.25% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 31.76 | | std | 11.35 | | cv | 0.357 | | sampleLengths | | 0 | 49 | | 1 | 22 | | 2 | 46 | | 3 | 45 | | 4 | 23 | | 5 | 53 | | 6 | 11 | | 7 | 17 | | 8 | 24 | | 9 | 42 | | 10 | 29 | | 11 | 19 | | 12 | 25 | | 13 | 38 | | 14 | 26 | | 15 | 39 | | 16 | 33 | | 17 | 33 | | 18 | 21 | | 19 | 29 | | 20 | 43 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 96 | | matches | (empty) | |
| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 81 | | ratio | 0.037 | | matches | | 0 | "Sleek blond hair, chiseled features, heterochromatic eyes—one amber, one fathomless black." | | 1 | "An ivory-handled cane—she knew it concealed a wickedly sharp blade—was clenched in his fist." | | 2 | "Memories flooded back—late nights poring over ancient grimoires, the searing brush of his lips against hers, the wrenching agony of his betrayal." |
| |
| 99.87% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 523 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.040152963671128104 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.01338432122370937 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 8.23 | | std | 5 | | cv | 0.607 | | sampleLengths | | 0 | 8 | | 1 | 5 | | 2 | 2 | | 3 | 17 | | 4 | 17 | | 5 | 8 | | 6 | 14 | | 7 | 17 | | 8 | 6 | | 9 | 11 | | 10 | 2 | | 11 | 10 | | 12 | 10 | | 13 | 4 | | 14 | 17 | | 15 | 14 | | 16 | 9 | | 17 | 10 | | 18 | 4 | | 19 | 2 | | 20 | 22 | | 21 | 6 | | 22 | 4 | | 23 | 10 | | 24 | 9 | | 25 | 6 | | 26 | 5 | | 27 | 6 | | 28 | 7 | | 29 | 4 | | 30 | 4 | | 31 | 19 | | 32 | 1 | | 33 | 5 | | 34 | 11 | | 35 | 7 | | 36 | 14 | | 37 | 5 | | 38 | 11 | | 39 | 4 | | 40 | 12 | | 41 | 2 | | 42 | 4 | | 43 | 8 | | 44 | 7 | | 45 | 9 | | 46 | 16 | | 47 | 5 | | 48 | 3 | | 49 | 30 |
| |
| 90.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.5432098765432098 | | totalSentences | 81 | | uniqueOpeners | 44 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 57 | | matches | | 0 | "Then she kissed him, hard" |
| | ratio | 0.018 | |
| 44.56% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 57 | | matches | | 0 | "She nudged the sleeping potions" | | 1 | "She hadn't laid eyes on" | | 2 | "he said, his voice a" | | 3 | "Her heart stuttered at his" | | 4 | "He swept past her." | | 5 | "She shut the door and" | | 6 | "she demanded, crossing her arms" | | 7 | "He twirled the cane between" | | 8 | "She stalked into the tiny" | | 9 | "She busied herself filling the" | | 10 | "His footsteps whispered over the" | | 11 | "She tensed as he drew" | | 12 | "She whirled to face him" | | 13 | "He reached for her." | | 14 | "She flinched away, her shoulders" | | 15 | "He sighed and let his" | | 16 | "he said softly" | | 17 | "she asked hoarsely" | | 18 | "His forehead came to rest" | | 19 | "His fingers fisted in her" |
| | ratio | 0.439 | |
| 56.49% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 57 | | matches | | 0 | "The sharp rap at the" | | 1 | "Ptolemy, the flat's resident tabby," | | 2 | "She nudged the sleeping potions" | | 3 | "The breath caught in her" | | 4 | "She hadn't laid eyes on" | | 5 | "Rory shook herself and undid" | | 6 | "The door creaked open." | | 7 | "Lucien stood there in his" | | 8 | "An ivory-handled cane—she knew it" | | 9 | "he said, his voice a" | | 10 | "Her heart stuttered at his" | | 11 | "Memories flooded back—late nights poring" | | 12 | "He swept past her." | | 13 | "Sandalwood and spice tickled her" | | 14 | "She shut the door and" | | 15 | "she demanded, crossing her arms" | | 16 | "A muscle jumped in his" | | 17 | "He twirled the cane between" | | 18 | "Rory barked a laugh." | | 19 | "She stalked into the tiny" |
| | ratio | 0.807 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, his voice a low purr" | | 1 | "She stalked, desperate to put space between them" | | 2 | "Rory said, her voice shaking" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 5 | | fancyTags | | 0 | "she demanded (demand)" | | 1 | "she whispered (whisper)" | | 2 | "he agreed (agree)" | | 3 | "she whispered (whisper)" | | 4 | "he breathed (breathe)" |
| | dialogueSentences | 27 | | tagDensity | 0.37 | | leniency | 0.741 | | rawRatio | 0.5 | | effectiveRatio | 0.37 | |