| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 3 | | adverbTags | | 0 | "Meredith's voice broke just [just]" | | 1 | "Meredith's mask slipped again [again]" | | 2 | "The mask snapped back [back]" |
| | dialogueSentences | 83 | | tagDensity | 0.205 | | leniency | 0.41 | | rawRatio | 0.176 | | effectiveRatio | 0.072 | |
| 68.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1737 | | totalAiIsmAdverbs | 11 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 2 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | |
| | highlights | | 0 | "carefully" | | 1 | "deliberately" | | 2 | "perfectly" | | 3 | "really" | | 4 | "suddenly" | | 5 | "very" | | 6 | "slowly" |
| |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 62.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1737 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "eyebrow" | | 1 | "warmth" | | 2 | "flickered" | | 3 | "effortless" | | 4 | "could feel" | | 5 | "tension" | | 6 | "weight" | | 7 | "silence" | | 8 | "traced" | | 9 | "familiar" | | 10 | "trembled" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 109 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 173 | | 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 | 1730 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 34.65% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 66 | | wordCount | 1127 | | uniqueNames | 13 | | maxNameDensity | 2.31 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 26 | | Raven | 1 | | Nest | 1 | | Meredith | 17 | | Powell | 2 | | Cardiff | 1 | | Golden | 1 | | Empress | 1 | | Merry | 9 | | Thursday-night | 1 | | Silas | 4 | | Didn | 1 | | Smooth | 1 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Meredith" | | 3 | "Powell" | | 4 | "Merry" | | 5 | "Silas" |
| | places | | | globalScore | 0.346 | | windowScore | 0.5 | |
| 82.43% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a trap" | | 1 | "seemed distant suddenly, the clinking glasses and murmured conversations fading to static" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1730 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 100 | | mean | 17.3 | | std | 18.89 | | cv | 1.092 | | sampleLengths | | 0 | 11 | | 1 | 32 | | 2 | 6 | | 3 | 28 | | 4 | 44 | | 5 | 100 | | 6 | 10 | | 7 | 60 | | 8 | 1 | | 9 | 18 | | 10 | 17 | | 11 | 4 | | 12 | 1 | | 13 | 31 | | 14 | 5 | | 15 | 3 | | 16 | 5 | | 17 | 11 | | 18 | 42 | | 19 | 6 | | 20 | 3 | | 21 | 4 | | 22 | 28 | | 23 | 3 | | 24 | 3 | | 25 | 40 | | 26 | 3 | | 27 | 3 | | 28 | 31 | | 29 | 3 | | 30 | 46 | | 31 | 7 | | 32 | 3 | | 33 | 3 | | 34 | 5 | | 35 | 35 | | 36 | 47 | | 37 | 4 | | 38 | 84 | | 39 | 3 | | 40 | 2 | | 41 | 18 | | 42 | 5 | | 43 | 53 | | 44 | 7 | | 45 | 5 | | 46 | 23 | | 47 | 5 | | 48 | 1 | | 49 | 39 |
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| 95.61% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 109 | | matches | | 0 | "been straightened" | | 1 | "were painted" | | 2 | "being asked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 208 | | matches | | 0 | "was polishing" | | 1 | "was saying" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 173 | | ratio | 0 | | matches | (empty) | |
| 92.49% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1132 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 55 | | adverbRatio | 0.04858657243816254 | | lyAdverbCount | 22 | | lyAdverbRatio | 0.019434628975265017 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 173 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 173 | | mean | 10 | | std | 8.86 | | cv | 0.886 | | sampleLengths | | 0 | 11 | | 1 | 13 | | 2 | 19 | | 3 | 6 | | 4 | 28 | | 5 | 2 | | 6 | 12 | | 7 | 14 | | 8 | 16 | | 9 | 22 | | 10 | 22 | | 11 | 26 | | 12 | 30 | | 13 | 4 | | 14 | 1 | | 15 | 5 | | 16 | 3 | | 17 | 17 | | 18 | 28 | | 19 | 2 | | 20 | 4 | | 21 | 6 | | 22 | 1 | | 23 | 4 | | 24 | 14 | | 25 | 3 | | 26 | 8 | | 27 | 6 | | 28 | 4 | | 29 | 1 | | 30 | 5 | | 31 | 6 | | 32 | 20 | | 33 | 5 | | 34 | 3 | | 35 | 5 | | 36 | 8 | | 37 | 3 | | 38 | 6 | | 39 | 26 | | 40 | 6 | | 41 | 4 | | 42 | 6 | | 43 | 3 | | 44 | 4 | | 45 | 8 | | 46 | 17 | | 47 | 3 | | 48 | 3 | | 49 | 3 |
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| 54.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.37572254335260113 | | totalSentences | 173 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 94 | | matches | | 0 | "Then carefully, deliberately, looked away." | | 1 | "Instead, she sat very still." | | 2 | "Then the door opened, and" | | 3 | "More than the drink was" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 94 | | matches | | 0 | "He set the pint back" | | 1 | "She stared at the woman" | | 2 | "She pushed off from her" | | 3 | "She took a slow sip" | | 4 | "She'd meant it as a" | | 5 | "Her nails were painted a" | | 6 | "She could feel him cataloguing" | | 7 | "Her voice dropped, losing some" | | 8 | "She remembered too well." | | 9 | "She said it deliberately, watching" | | 10 | "Her eyes glistened, but she" | | 11 | "Her perfectly manicured fingers trembled" | | 12 | "He had the kind of" | | 13 | "She paused beside Rory, close" | | 14 | "Her voice was very soft," | | 15 | "She walked away without looking" | | 16 | "He nodded slowly, his silver" |
| | ratio | 0.181 | |
| 66.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 94 | | matches | | 0 | "The glass slipped from Rory's" | | 1 | "Silas caught it mid-fall, the" | | 2 | "He set the pint back" | | 3 | "She stared at the woman" | | 4 | "The woman ordering a gin" | | 5 | "The wild ginger curls Rory" | | 6 | "The vintage band tees and" | | 7 | "Those eyes found Rory." | | 8 | "Rory's chest tightened." | | 9 | "She pushed off from her" | | 10 | "The green neon sign above" | | 11 | "Hair escaping its ponytail." | | 12 | "The same mess she'd always" | | 13 | "The woman's shoulders stiffened." | | 14 | "She took a slow sip" | | 15 | "The full name, delivered like" | | 16 | "The number hung between them." | | 17 | "Meredith's gaze flickered over her," | | 18 | "Something cold slithered through Rory's" | | 19 | "She'd meant it as a" |
| | ratio | 0.787 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 94 | | matches | (empty) | | ratio | 0 | |
| 59.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 5 | | matches | | 0 | "Merry Powell, who'd shared her dorm room at Cardiff for two years." | | 1 | "The wild ginger curls Rory remembered had been straightened and dyed a severe blonde, pulled back in a style that screamed boardroom." | | 2 | "And her eyes, when they finally lifted from her phone and swept the room, held none of the warmth that had once made Merry everyone's favourite person at a part…" | | 3 | "Her nails were painted a muted nude, the kind of colour that took effort to look effortless." | | 4 | "But the door stayed closed, and the whiskey sat untouched, and somewhere out there, a woman she'd loved like a sister climbed into a cab with a man who'd never …" |
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| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory slid, not waiting for permission" | | 1 | "Meredith took, but her hand wasn't steady" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | 0 | "The mask snapped back (snap)" |
| | dialogueSentences | 83 | | tagDensity | 0.06 | | leniency | 0.12 | | rawRatio | 0.2 | | effectiveRatio | 0.024 | |