| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Her knuckles whitened around [around]" |
| | dialogueSentences | 66 | | tagDensity | 0.197 | | leniency | 0.394 | | rawRatio | 0.077 | | effectiveRatio | 0.03 | |
| 96.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1389 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 49.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1389 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "perfect" | | 1 | "chill" | | 2 | "weight" | | 3 | "echoes" | | 4 | "silence" | | 5 | "reminder" | | 6 | "flicker" | | 7 | "traced" | | 8 | "processed" | | 9 | "trembled" | | 10 | "echo" | | 11 | "crystal" |
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| 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 | 140 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 140 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 190 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 13 | | totalWords | 1376 | | ratio | 0.009 | | matches | | 0 | "Keep the space. Keep the past." | | 1 | "You’re not the hero. You’re the pattern." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 913 | | uniqueNames | 14 | | maxNameDensity | 0.22 | | worstName | "Raven" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Raven" | | discoveredNames | | Raven | 2 | | Nest | 2 | | November | 1 | | Guinness | 1 | | Carter | 2 | | Golden | 1 | | Empress | 1 | | Prague | 1 | | Blunt | 1 | | Bristol | 1 | | Graham | 1 | | Thames | 1 | | Rory | 1 | | Aurora | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Empress" | | 4 | "Graham" | | 5 | "Rory" | | 6 | "Aurora" |
| | places | | 0 | "Golden" | | 1 | "Prague" | | 2 | "Bristol" | | 3 | "Thames" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 54.65% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.453 | | wordCount | 1376 | | matches | | 0 | "Not the same kind of waiting, but waiting nonetheless" | | 1 | "Not proud of it, but the check cleared" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 190 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 16.78 | | std | 15.99 | | cv | 0.953 | | sampleLengths | | 0 | 64 | | 1 | 4 | | 2 | 66 | | 3 | 6 | | 4 | 22 | | 5 | 13 | | 6 | 15 | | 7 | 14 | | 8 | 5 | | 9 | 9 | | 10 | 18 | | 11 | 69 | | 12 | 17 | | 13 | 11 | | 14 | 1 | | 15 | 17 | | 16 | 30 | | 17 | 2 | | 18 | 25 | | 19 | 4 | | 20 | 50 | | 21 | 19 | | 22 | 1 | | 23 | 30 | | 24 | 13 | | 25 | 10 | | 26 | 16 | | 27 | 2 | | 28 | 28 | | 29 | 32 | | 30 | 6 | | 31 | 35 | | 32 | 1 | | 33 | 18 | | 34 | 4 | | 35 | 16 | | 36 | 15 | | 37 | 6 | | 38 | 10 | | 39 | 21 | | 40 | 29 | | 41 | 49 | | 42 | 3 | | 43 | 1 | | 44 | 9 | | 45 | 1 | | 46 | 24 | | 47 | 13 | | 48 | 11 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 140 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 165 | | matches | (empty) | |
| 7.52% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 190 | | ratio | 0.047 | | matches | | 0 | "The bartender—flat cap squinted against the dim—didn’t miss a beat; half-pull of Guinness, perfect creamy head, onto the waiting tray." | | 1 | "The insulated delivery bag still slung over her arm told me what I needed to know—late shift from Golden Empress, tucked away." | | 2 | "I watched the way her hips balanced—still light on her feet, but there was something new in the reserve of her shoulders, a weight she carried like a guard dog ready to snap at a shadow." | | 3 | "A flicker of something crossed her face—shame?" | | 4 | "Then she looked up—bright blue eyes locking onto mine, paler than I remembered, like the colour had leached out through exposure." | | 5 | "The Raven’s Nest hummed around us—the clink of glasses, the murmur of a bet settled, a laugh too loud from the dartboard corner." | | 6 | "I lifted my own wrist reflexively—the faint mark, childhood kitchen accident." | | 7 | "The wood groaned under my weight—old bar stool, repaired too many times, just like everything else in this place." | | 8 | "I thought of Rory Carter—not Aurora—25 years old, brilliant and reckless, skipping stones across the law school pond, thinking she already knew every answer." |
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| 94.41% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 927 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.04638619201725998 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006472491909385114 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 190 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 190 | | mean | 7.24 | | std | 6.83 | | cv | 0.943 | | sampleLengths | | 0 | 8 | | 1 | 13 | | 2 | 15 | | 3 | 8 | | 4 | 20 | | 5 | 4 | | 6 | 25 | | 7 | 7 | | 8 | 22 | | 9 | 12 | | 10 | 6 | | 11 | 11 | | 12 | 6 | | 13 | 3 | | 14 | 2 | | 15 | 12 | | 16 | 1 | | 17 | 5 | | 18 | 4 | | 19 | 6 | | 20 | 9 | | 21 | 2 | | 22 | 1 | | 23 | 2 | | 24 | 5 | | 25 | 9 | | 26 | 2 | | 27 | 13 | | 28 | 3 | | 29 | 11 | | 30 | 36 | | 31 | 11 | | 32 | 8 | | 33 | 3 | | 34 | 9 | | 35 | 4 | | 36 | 1 | | 37 | 3 | | 38 | 9 | | 39 | 2 | | 40 | 1 | | 41 | 5 | | 42 | 2 | | 43 | 2 | | 44 | 2 | | 45 | 2 | | 46 | 4 | | 47 | 9 | | 48 | 12 | | 49 | 9 |
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| 68.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4421052631578947 | | totalSentences | 190 | | uniqueOpeners | 84 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 105 | | matches | | 0 | "Then he saw her." | | 1 | "Of course she would." | | 2 | "Then the stubborn tilt of" | | 3 | "Then she looked up—bright blue" | | 4 | "Then lifted the glass." | | 5 | "Then back at me." | | 6 | "Just knocked the rest back." |
| | ratio | 0.067 | |
| 33.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 105 | | matches | | 0 | "She wasn’t there for a" | | 1 | "She didn’t move." | | 2 | "I dried my hands on" | | 3 | "She flinched at the name." | | 4 | "My voice steady" | | 5 | "Her boots clicked against the" | | 6 | "I watched the way her" | | 7 | "She chose the stool farthest" | | 8 | "I poured her a gin" | | 9 | "She stared at the glass" | | 10 | "I wiped the bar top" | | 11 | "I let the silence sit." | | 12 | "We’d mastered silence in Prague." | | 13 | "She’d fill it eventually." | | 14 | "She took a slow sip." | | 15 | "I leaned on the bar" | | 16 | "My signet caught the light." | | 17 | "She set the drink down" | | 18 | "Her finger traced the rim." | | 19 | "She lowered her voice" |
| | ratio | 0.467 | |
| 93.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 105 | | matches | | 0 | "The door to the Raven's" | | 1 | "A gust rattled the green" | | 2 | "The bartender—flat cap squinted against" | | 3 | "Aurora Carter stood frozen just" | | 4 | "She wasn’t there for a" | | 5 | "The insulated delivery bag still" | | 6 | "The bag slipped from her" | | 7 | "A red thermal cup tumbled" | | 8 | "Coffee pooled dark against the" | | 9 | "She didn’t move." | | 10 | "I dried my hands on" | | 11 | "She flinched at the name." | | 12 | "My voice steady" | | 13 | "Her boots clicked against the" | | 14 | "I watched the way her" | | 15 | "She chose the stool farthest" | | 16 | "I poured her a gin" | | 17 | "Lime wedge already squeezed." | | 18 | "She stared at the glass" | | 19 | "A dry chuckle escaped her." |
| | ratio | 0.733 | |
| 95.24% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 105 | | matches | | 0 | "Now, standing in my bar" | | 1 | "Either way, I’d be here." |
| | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 66 | | tagDensity | 0.015 | | leniency | 0.03 | | rawRatio | 0 | | effectiveRatio | 0 | |