| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 4 | | adverbTags | | 0 | "Davies glanced around [around]" | | 1 | "Harlow's hand tightened around [around]" | | 2 | "She glanced around [around]" | | 3 | "Eva's gaze darted around [around]" |
| | dialogueSentences | 37 | | tagDensity | 0.351 | | leniency | 0.703 | | rawRatio | 0.308 | | effectiveRatio | 0.216 | |
| 72.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 555 | | totalAiIsmAdverbs | 3 | | 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) | |
| 0.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 555 | | totalAiIsms | 11 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | word | "down her spine" | | count | 1 |
| | 8 | | | 9 | |
| | highlights | | 0 | "tension" | | 1 | "familiar" | | 2 | "weight" | | 3 | "etched" | | 4 | "measured" | | 5 | "whisper" | | 6 | "chill" | | 7 | "down her spine" | | 8 | "trembled" | | 9 | "jaw clenched" |
| |
| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 3 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" | | 2 | "jaw clenched" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 36 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 36 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 59 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 21 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 554 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 300 | | uniqueNames | 8 | | maxNameDensity | 4.67 | | worstName | "Harlow" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 14 | | Quinn | 1 | | Davies | 4 | | Reaching | 1 | | Weaving | 1 | | Eva | 7 | | Veil | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Davies" | | 3 | "Eva" | | 4 | "Compass" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 50.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 25 | | glossingSentenceCount | 1 | | matches | | 0 | "e spun wildly, seemingly drawn to the symbol" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 554 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 59 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 18.47 | | std | 9.62 | | cv | 0.521 | | sampleLengths | | 0 | 51 | | 1 | 15 | | 2 | 30 | | 3 | 8 | | 4 | 26 | | 5 | 5 | | 6 | 22 | | 7 | 9 | | 8 | 20 | | 9 | 25 | | 10 | 11 | | 11 | 20 | | 12 | 17 | | 13 | 32 | | 14 | 8 | | 15 | 13 | | 16 | 19 | | 17 | 17 | | 18 | 25 | | 19 | 26 | | 20 | 8 | | 21 | 15 | | 22 | 7 | | 23 | 13 | | 24 | 13 | | 25 | 27 | | 26 | 16 | | 27 | 30 | | 28 | 15 | | 29 | 11 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 36 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 59 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 59 | | ratio | 0 | | matches | (empty) | |
| 91.53% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 300 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.043333333333333335 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.02666666666666667 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 59 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 59 | | mean | 9.39 | | std | 4.68 | | cv | 0.498 | | sampleLengths | | 0 | 17 | | 1 | 15 | | 2 | 19 | | 3 | 15 | | 4 | 19 | | 5 | 11 | | 6 | 6 | | 7 | 2 | | 8 | 11 | | 9 | 15 | | 10 | 3 | | 11 | 2 | | 12 | 12 | | 13 | 10 | | 14 | 9 | | 15 | 16 | | 16 | 4 | | 17 | 16 | | 18 | 9 | | 19 | 6 | | 20 | 5 | | 21 | 9 | | 22 | 11 | | 23 | 8 | | 24 | 9 | | 25 | 14 | | 26 | 18 | | 27 | 8 | | 28 | 8 | | 29 | 5 | | 30 | 11 | | 31 | 8 | | 32 | 9 | | 33 | 8 | | 34 | 12 | | 35 | 13 | | 36 | 7 | | 37 | 9 | | 38 | 10 | | 39 | 4 | | 40 | 4 | | 41 | 12 | | 42 | 3 | | 43 | 3 | | 44 | 4 | | 45 | 5 | | 46 | 8 | | 47 | 6 | | 48 | 7 | | 49 | 16 |
| |
| 83.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5084745762711864 | | totalSentences | 59 | | uniqueOpeners | 30 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 5 | | totalSentences | 35 | | matches | | 0 | "She strode past the rows" | | 1 | "she barked, approaching the young" | | 2 | "She examined the body closer," | | 3 | "she murmured, rising to her" | | 4 | "She glanced around nervously" |
| | ratio | 0.143 | |
| 2.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 35 | | matches | | 0 | "Detective Harlow Quinn swept into" | | 1 | "The usual bustle had given" | | 2 | "She strode past the rows" | | 3 | "she barked, approaching the young" | | 4 | "Davies gestured to the victim," | | 5 | "Harlow nodded, kneeling beside the" | | 6 | "Davies glanced around, lowering his" | | 7 | "Harlow's eyes narrowed." | | 8 | "She examined the body closer," | | 9 | "Harlow's gaze drifted to the" | | 10 | "The needle spun wildly, seemingly" | | 11 | "Davies's eyes widened" | | 12 | "Harlow didn't answer, her attention" | | 13 | "she murmured, rising to her" | | 14 | "A young woman with curly" | | 15 | "Harlow's voice was low and" | | 16 | "The woman startled, her green" | | 17 | "Harlow leaned forward, her sharp" | | 18 | "Eva swallowed hard, her gaze" | | 19 | "Harlow's hand tightened around the" |
| | ratio | 0.914 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 35 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 8 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 95.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she barked (bark)" | | 1 | "she murmured (murmur)" |
| | dialogueSentences | 37 | | tagDensity | 0.081 | | leniency | 0.162 | | rawRatio | 0.667 | | effectiveRatio | 0.108 | |