| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "The voice rasped like [like]" | | 1 | "she said quietly [quietly]" |
| | dialogueSentences | 45 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.1 | | effectiveRatio | 0.089 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1050 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 57.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1050 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "traced" | | 1 | "weight" | | 2 | "flicked" | | 3 | "glinting" | | 4 | "etched" | | 5 | "shattered" | | 6 | "trembled" | | 7 | "whisper" | | 8 | "flickered" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1050 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 600 | | uniqueNames | 4 | | maxNameDensity | 3 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 18 | | Cardiff | 1 | | Eva | 12 | | Silas | 3 |
| | persons | | | places | | | globalScore | 0 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | 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 | 1050 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 31.82 | | std | 23.36 | | cv | 0.734 | | sampleLengths | | 0 | 68 | | 1 | 3 | | 2 | 7 | | 3 | 21 | | 4 | 28 | | 5 | 1 | | 6 | 37 | | 7 | 28 | | 8 | 43 | | 9 | 3 | | 10 | 63 | | 11 | 16 | | 12 | 88 | | 13 | 15 | | 14 | 60 | | 15 | 18 | | 16 | 31 | | 17 | 38 | | 18 | 77 | | 19 | 47 | | 20 | 58 | | 21 | 26 | | 22 | 23 | | 23 | 9 | | 24 | 71 | | 25 | 12 | | 26 | 52 | | 27 | 30 | | 28 | 16 | | 29 | 3 | | 30 | 22 | | 31 | 18 | | 32 | 18 |
| |
| 99.51% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 61 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 112 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 85 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 606 | | adjectiveStacks | 1 | | stackExamples | | 0 | "swollen shut, dried blood" |
| | adverbCount | 17 | | adverbRatio | 0.028052805280528052 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.01155115511551155 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 12.35 | | std | 8.98 | | cv | 0.727 | | sampleLengths | | 0 | 24 | | 1 | 24 | | 2 | 20 | | 3 | 3 | | 4 | 4 | | 5 | 3 | | 6 | 15 | | 7 | 6 | | 8 | 5 | | 9 | 12 | | 10 | 11 | | 11 | 1 | | 12 | 17 | | 13 | 15 | | 14 | 5 | | 15 | 20 | | 16 | 8 | | 17 | 5 | | 18 | 14 | | 19 | 7 | | 20 | 17 | | 21 | 3 | | 22 | 21 | | 23 | 10 | | 24 | 24 | | 25 | 8 | | 26 | 9 | | 27 | 4 | | 28 | 3 | | 29 | 13 | | 30 | 13 | | 31 | 45 | | 32 | 17 | | 33 | 8 | | 34 | 7 | | 35 | 5 | | 36 | 37 | | 37 | 18 | | 38 | 9 | | 39 | 9 | | 40 | 6 | | 41 | 25 | | 42 | 11 | | 43 | 13 | | 44 | 14 | | 45 | 21 | | 46 | 9 | | 47 | 39 | | 48 | 8 | | 49 | 9 |
| |
| 61.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4235294117647059 | | totalSentences | 85 | | uniqueOpeners | 36 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 57 | | matches | | 0 | "Somewhere in the dark, a" |
| | ratio | 0.018 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 57 | | matches | | 0 | "She counted the scratches in" | | 1 | "She didn't look up." | | 2 | "Her bright blue eyes lifted," | | 3 | "She clicked across the floorboards" | | 4 | "She slid onto the stool" | | 5 | "He poured two whiskies without" | | 6 | "She set it down." | | 7 | "She leaned forward, her perfume" | | 8 | "She reached across, her fingers" | | 9 | "He studied Aurora, his gaze" | | 10 | "She stared into the whiskey," | | 11 | "She laughed, but it sounded" | | 12 | "she said quietly" | | 13 | "She slid it across the" | | 14 | "Her hand closed over Aurora's," | | 15 | "She glanced at the screen," | | 16 | "It was already cracked." |
| | ratio | 0.298 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 55 | | totalSentences | 57 | | matches | | 0 | "Aurora's thumb traced the crescent" | | 1 | "The green neon from the" | | 2 | "She counted the scratches in" | | 3 | "The door chimed." | | 4 | "She didn't look up." | | 5 | "The voice rasped like gravel" | | 6 | "Aurora set down the cloth." | | 7 | "Her bright blue eyes lifted," | | 8 | "Recognition hit her like a" | | 9 | "Eva stepped inside, shaking rain" | | 10 | "She clicked across the floorboards" | | 11 | "Aurora's voice didn't waver, though" | | 12 | "Eva's laugh cracked like ice." | | 13 | "She slid onto the stool" | | 14 | "The leather seat creaked under" | | 15 | "Eva signalled to Silas, who" | | 16 | "The retired spy's hazel eyes" | | 17 | "He poured two whiskies without" | | 18 | "Aurora felt the glass in" | | 19 | "She set it down." |
| | ratio | 0.965 | |
| 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 | 21 | | technicalSentenceCount | 1 | | matches | | 0 | "The green neon from the street bled through the rain-streaked window, turning dust motes into drifting ash that settled on the bottles behind her." |
| |
| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "Aurora's voice didn't, though her fingers curled around the bar's edge, nails digging into the varnish" | | 1 | "Eva's voice dropped, but every word landed like a hammer" | | 2 | "Eva looked up, her eyes wide" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Eva repeated (repeat)" | | 1 | "She laughed (laugh)" |
| | dialogueSentences | 45 | | tagDensity | 0.111 | | leniency | 0.222 | | rawRatio | 0.4 | | effectiveRatio | 0.089 | |