| 18.18% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "she asked finally [finally]" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.25 | | effectiveRatio | 0.182 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 588 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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 | 588 | | totalAiIsms | 17 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | word | "down her spine" | | count | 1 |
| | 14 | | word | "skipped a beat" | | count | 1 |
|
| | highlights | | 0 | "practiced ease" | | 1 | "familiar" | | 2 | "tension" | | 3 | "unspoken" | | 4 | "silence" | | 5 | "palpable" | | 6 | "weight" | | 7 | "stark" | | 8 | "silk" | | 9 | "gleaming" | | 10 | "enigmatic" | | 11 | "flicked" | | 12 | "resolve" | | 13 | "down her spine" | | 14 | "skipped a beat" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "The air was heavy with" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 33 | | matches | (empty) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 33 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 40 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 590 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 49.80% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 499 | | uniqueNames | 5 | | maxNameDensity | 2 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 4 | | Rory | 10 | | Ptolemy | 2 | | Moreau | 1 | | Lucien | 8 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Ptolemy" | | 3 | "Moreau" | | 4 | "Lucien" |
| | places | (empty) | | globalScore | 0.498 | | windowScore | 0.667 | |
| 63.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 29 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 590 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 40 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 32.78 | | std | 19.24 | | cv | 0.587 | | sampleLengths | | 0 | 67 | | 1 | 2 | | 2 | 47 | | 3 | 44 | | 4 | 20 | | 5 | 47 | | 6 | 8 | | 7 | 41 | | 8 | 42 | | 9 | 16 | | 10 | 15 | | 11 | 20 | | 12 | 11 | | 13 | 61 | | 14 | 14 | | 15 | 52 | | 16 | 32 | | 17 | 51 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 33 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 81 | | matches | (empty) | |
| 71.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 40 | | ratio | 0.025 | | matches | | 0 | "As the silence between them stretched out, Rory became aware of the sounds around her – Ptolemy's soft purring from the living room, the distant hum of the curry house below, the creaks and groans of the old building settling into its foundation." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 498 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.030120481927710843 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.010040160642570281 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 40 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 40 | | mean | 14.75 | | std | 8.36 | | cv | 0.567 | | sampleLengths | | 0 | 19 | | 1 | 25 | | 2 | 23 | | 3 | 2 | | 4 | 20 | | 5 | 11 | | 6 | 16 | | 7 | 9 | | 8 | 15 | | 9 | 20 | | 10 | 20 | | 11 | 23 | | 12 | 16 | | 13 | 8 | | 14 | 3 | | 15 | 5 | | 16 | 13 | | 17 | 28 | | 18 | 17 | | 19 | 16 | | 20 | 9 | | 21 | 7 | | 22 | 9 | | 23 | 10 | | 24 | 5 | | 25 | 6 | | 26 | 14 | | 27 | 7 | | 28 | 4 | | 29 | 43 | | 30 | 18 | | 31 | 11 | | 32 | 3 | | 33 | 15 | | 34 | 14 | | 35 | 23 | | 36 | 17 | | 37 | 15 | | 38 | 23 | | 39 | 28 |
| |
| 87.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.525 | | totalSentences | 40 | | uniqueOpeners | 21 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 32 | | matches | | 0 | "Instead, her eyes landed on" |
| | ratio | 0.031 | |
| 95.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 32 | | matches | | 0 | "She pushed the door open," | | 1 | "she asked finally, her voice" | | 2 | "he replied, his voice low," | | 3 | "He took a step closer," | | 4 | "She pushed it down, reminding" | | 5 | "she said, her voice neutral" | | 6 | "He chuckled, a low, husky" | | 7 | "She did know him, all" | | 8 | "It was a sensation she'd" | | 9 | "he said, his voice low," |
| | ratio | 0.313 | |
| 38.13% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 27 | | totalSentences | 32 | | matches | | 0 | "The three deadbolts on Eva's" | | 1 | "She pushed the door open," | | 2 | "Rory's mind struggled to catch" | | 3 | "Time had a way of" | | 4 | "The hurt, the anger, and" | | 5 | "The air was heavy with" | | 6 | "Rory's grip on the door" | | 7 | "she asked finally, her voice" | | 8 | "Lucien pushed off the wall," | | 9 | "he replied, his voice low," | | 10 | "Rory's eyes narrowed." | | 11 | "He took a step closer," | | 12 | "A faint flush rose to" | | 13 | "She pushed it down, reminding" | | 14 | "she said, her voice neutral" | | 15 | "Lucien's smile was a thin," | | 16 | "Rory's gaze flicked to the" | | 17 | "He chuckled, a low, husky" | | 18 | "She did know him, all" | | 19 | "That was the problem." |
| | ratio | 0.844 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 32 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "Lucien's eyes locked onto hers, his gaze piercing, as if he could see right through her defenses." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "he replied, his voice low, smooth as silk" | | 1 | "she said, her voice neutral" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |