| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 2 | | adverbTags | | 0 | "Rory said warily [warily]" | | 1 | "Rory asked finally [finally]" |
| | dialogueSentences | 5 | | tagDensity | 0.8 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 61.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 262 | | 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) | |
| 4.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 262 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "streaming" | | 1 | "measured" | | 2 | "dancing" | | 3 | "gleaming" | | 4 | "eyebrow" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 20 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 20 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 21 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 262 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 28.05% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 246 | | uniqueNames | 6 | | maxNameDensity | 2.44 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 1 | | Flat | 1 | | Moreau | 1 | | Ptolemy | 4 | | Lucien | 5 | | Rory | 6 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Ptolemy" | | 3 | "Lucien" | | 4 | "Rory" |
| | places | | | globalScore | 0.28 | | windowScore | 0.833 | |
| 11.11% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 18 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed tailored yesterday, today, and the day before, with an air of precision" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 262 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 21 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 7 | | mean | 37.43 | | std | 22.21 | | cv | 0.593 | | sampleLengths | | |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 20 | | matches | (empty) | |
| 19.82% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 37 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 21 | | ratio | 0 | | matches | (empty) | |
| 99.73% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 246 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.028455284552845527 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.02032520325203252 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 21 | | echoCount | 0 | | echoWords | (empty) | |
| 97.26% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 21 | | mean | 12.48 | | std | 4.9 | | cv | 0.393 | | sampleLengths | | 0 | 15 | | 1 | 22 | | 2 | 17 | | 3 | 16 | | 4 | 4 | | 5 | 7 | | 6 | 3 | | 7 | 15 | | 8 | 15 | | 9 | 19 | | 10 | 8 | | 11 | 15 | | 12 | 9 | | 13 | 17 | | 14 | 12 | | 15 | 11 | | 16 | 12 | | 17 | 5 | | 18 | 14 | | 19 | 11 | | 20 | 15 |
| |
| 74.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.47619047619047616 | | totalSentences | 21 | | uniqueOpeners | 10 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 20 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 4 | | totalSentences | 20 | | matches | | 0 | "He wore a charcoal suit" | | 1 | "Her hands instinctively tightened around" | | 2 | "Their eyes locked, fixed on" | | 3 | "He grained his pants, precisely" |
| | ratio | 0.2 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 20 | | totalSentences | 20 | | matches | | 0 | "Rory's eyes narrowed as she" | | 1 | "Ptolemy, her tabby cat, was" | | 2 | "The air in Eva's Flat" | | 3 | "Rory worked the sandpaper with" | | 4 | "Ptolemy swiveled, tail twitching." | | 5 | "Rory followed his gaze through" | | 6 | "Lucien Moreau filled the space" | | 7 | "The angular planes of his" | | 8 | "He wore a charcoal suit" | | 9 | "Rory said warily, the sandpaper" | | 10 | "Her hands instinctively tightened around" | | 11 | "Their eyes locked, fixed on" | | 12 | "Rory asked finally, the sandpaper" | | 13 | "Ptolemy slid between them, weaving" | | 14 | "Lucien dropped to a crouch," | | 15 | "The tabby sprawled across his" | | 16 | "Ptolemy pawed at a buttonhole." | | 17 | "Rory raised an eyebrow as" | | 18 | "He grained his pants, precisely" | | 19 | "Lucien's voice punctuated the space," |
| | ratio | 1 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 20 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 12 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory said warily, the sandpaper falling still" | | 1 | "Lucien's voice punctuated, syphon drawscoming into the quiet room" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |