| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 34 | | tagDensity | 0.471 | | leniency | 0.941 | | rawRatio | 0.063 | | effectiveRatio | 0.059 | |
| 74.72% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 989 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "softly" | | 1 | "slightly" | | 2 | "gently" | | 3 | "really" |
| |
| 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) | |
| 44.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 989 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoing" | | 2 | "lilt" | | 3 | "unreadable" | | 4 | "whisper" | | 5 | "echoed" | | 6 | "silence" | | 7 | "glinting" | | 8 | "familiar" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 83.33% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 40 | | matches | | 0 | "g in surprise" | | 1 | "t with excitement" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 40 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 57 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 984 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.88% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 592 | | uniqueNames | 11 | | maxNameDensity | 1.18 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 2 | | Nest | 2 | | England | 1 | | Soho | 3 | | Haight | 1 | | Ashbury | 1 | | Silas | 7 | | Welsh | 1 | | Aurora | 6 | | Rory | 1 | | Carter | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Rory" | | 5 | "Carter" |
| | places | | | globalScore | 0.909 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 98.37% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.016 | | wordCount | 984 | | matches | | 0 | "not glamorous, but it suits me" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 99.95% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 39.36 | | std | 19.67 | | cv | 0.5 | | sampleLengths | | 0 | 73 | | 1 | 39 | | 2 | 12 | | 3 | 50 | | 4 | 22 | | 5 | 37 | | 6 | 16 | | 7 | 31 | | 8 | 70 | | 9 | 58 | | 10 | 27 | | 11 | 25 | | 12 | 54 | | 13 | 22 | | 14 | 44 | | 15 | 36 | | 16 | 52 | | 17 | 64 | | 18 | 41 | | 19 | 39 | | 20 | 17 | | 21 | 81 | | 22 | 20 | | 23 | 6 | | 24 | 48 |
| |
| 96.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 40 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 93 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 596 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.03523489932885906 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.010067114093959731 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 57 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 57 | | mean | 17.26 | | std | 8.91 | | cv | 0.516 | | sampleLengths | | 0 | 10 | | 1 | 14 | | 2 | 19 | | 3 | 14 | | 4 | 16 | | 5 | 12 | | 6 | 17 | | 7 | 10 | | 8 | 12 | | 9 | 9 | | 10 | 36 | | 11 | 5 | | 12 | 17 | | 13 | 5 | | 14 | 7 | | 15 | 30 | | 16 | 7 | | 17 | 9 | | 18 | 20 | | 19 | 11 | | 20 | 16 | | 21 | 30 | | 22 | 24 | | 23 | 39 | | 24 | 19 | | 25 | 14 | | 26 | 13 | | 27 | 11 | | 28 | 14 | | 29 | 14 | | 30 | 28 | | 31 | 12 | | 32 | 20 | | 33 | 2 | | 34 | 23 | | 35 | 21 | | 36 | 20 | | 37 | 16 | | 38 | 31 | | 39 | 21 | | 40 | 25 | | 41 | 39 | | 42 | 22 | | 43 | 19 | | 44 | 10 | | 45 | 29 | | 46 | 9 | | 47 | 8 | | 48 | 26 | | 49 | 11 |
| |
| 81.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.49122807017543857 | | totalSentences | 57 | | uniqueOpeners | 28 | |
| 83.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 40 | | matches | | 0 | "Just then, the door to" |
| | ratio | 0.025 | |
| 30.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 40 | | matches | | 0 | "She spotted Silas behind the" | | 1 | "Her voice was low, still" | | 2 | "He looked up, his eyes" | | 3 | "He closed the book, his" | | 4 | "she replied, her eyes flickering" | | 5 | "He trailed off, a ghost" | | 6 | "She sat, her eyes never" | | 7 | "He leaned in, his voice" | | 8 | "She shook her head, the" | | 9 | "He poured a generous measure" | | 10 | "She stared into the dark" | | 11 | "She sighed, brushing a stray" | | 12 | "She paused, taking a sip" | | 13 | "He leaned back, the slight" | | 14 | "she said, her voice shaking" | | 15 | "She studied his face, noting" | | 16 | "He reached across the table," | | 17 | "She cleared her throat, swallowing" | | 18 | "She turned and walked towards" |
| | ratio | 0.475 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 40 | | matches | | 0 | "Aurora took a deep breath" | | 1 | "The warm, inviting smells of" | | 2 | "The walls were lined with" | | 3 | "She spotted Silas behind the" | | 4 | "The bar was nearly empty," | | 5 | "Aurora approached, her footsteps echoing" | | 6 | "Her voice was low, still" | | 7 | "He looked up, his eyes" | | 8 | "He closed the book, his" | | 9 | "she replied, her eyes flickering" | | 10 | "Silas gestured to the empty" | | 11 | "He trailed off, a ghost" | | 12 | "She sat, her eyes never" | | 13 | "He leaned in, his voice" | | 14 | "Aurora laughed, a sound that" | | 15 | "She shook her head, the" | | 16 | "He poured a generous measure" | | 17 | "She stared into the dark" | | 18 | "Silas's voice dropped an octave," | | 19 | "She sighed, brushing a stray" |
| | ratio | 0.9 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 40 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 2 | | matches | | 0 | "Aurora laughed, a sound that echoed back to her from the half-finished crossword in yesterday's newspaper." | | 1 | "Silas watched her, his gaze following her as she weaved through the maze of tables, his mind reliving shared memories and wondering what brought Rory Carter bac…" |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 6 | | matches | | 0 | "He looked up, his eyes widening in surprise" | | 1 | "He trailed, a ghost of a smile playing on his lips" | | 2 | "He leaned in, his voice lowering to a conspiratorial whisper" | | 3 | "Silas's voice dropped, his eyes narrowing" | | 4 | "she said, her voice shaking despite her best efforts" | | 5 | "Silas steepled, his eyes glinting with a hint of their old mischief" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |