| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.291 | | leniency | 0.582 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1663 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "slightly" | | 3 | "sharply" |
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| 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) | |
| 66.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1663 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "shattered" | | 1 | "sanctuary" | | 2 | "lilt" | | 3 | "scanned" | | 4 | "familiar" | | 5 | "intensity" | | 6 | "electric" | | 7 | "weight" | | 8 | "searing" | | 9 | "rhythmic" | | 10 | "flickered" |
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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 | 97 | | matches | (empty) | |
| 98.67% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 137 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1651 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1130 | | uniqueNames | 15 | | maxNameDensity | 1.68 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Evan" | | discoveredNames | | Aurora | 19 | | Guinness | 1 | | Raven | 1 | | Nest | 3 | | Soho | 2 | | Friday | 1 | | Italian | 1 | | Atlantic | 1 | | Welsh | 1 | | London | 2 | | Cardiff | 2 | | Silas | 14 | | Prague | 1 | | Balkans | 1 | | Evan | 14 |
| | persons | | 0 | "Aurora" | | 1 | "Raven" | | 2 | "Silas" | | 3 | "Balkans" | | 4 | "Evan" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Prague" |
| | globalScore | 0.659 | | windowScore | 0.333 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 5 | | matches | | 0 | "tobacco that seemed to seep out of the old Soho brickwork" | | 1 | "sounded like soft edges and high-end scotc" | | 2 | "looked like a different man dressed in th" | | 3 | "felt like it was throbbing" | | 4 | "looked like he’d been waiting for a decad" |
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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 | 1651 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 137 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 22.31 | | std | 17.56 | | cv | 0.787 | | sampleLengths | | 0 | 13 | | 1 | 3 | | 2 | 60 | | 3 | 41 | | 4 | 18 | | 5 | 4 | | 6 | 40 | | 7 | 13 | | 8 | 48 | | 9 | 11 | | 10 | 1 | | 11 | 74 | | 12 | 10 | | 13 | 17 | | 14 | 70 | | 15 | 35 | | 16 | 5 | | 17 | 8 | | 18 | 5 | | 19 | 28 | | 20 | 27 | | 21 | 21 | | 22 | 10 | | 23 | 16 | | 24 | 22 | | 25 | 16 | | 26 | 24 | | 27 | 16 | | 28 | 65 | | 29 | 37 | | 30 | 21 | | 31 | 18 | | 32 | 7 | | 33 | 38 | | 34 | 38 | | 35 | 18 | | 36 | 28 | | 37 | 42 | | 38 | 12 | | 39 | 31 | | 40 | 7 | | 41 | 15 | | 42 | 24 | | 43 | 24 | | 44 | 34 | | 45 | 21 | | 46 | 25 | | 47 | 31 | | 48 | 36 | | 49 | 15 |
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| 94.41% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 97 | | matches | | 0 | "was lost" | | 1 | "been hammered" | | 2 | "was gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 183 | | matches | | 0 | "was monitoring" | | 1 | "was slipping" | | 2 | "was throbbing" | | 3 | "wasn't looking" | | 4 | "was looking" | | 5 | "wasn't hiding" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 137 | | ratio | 0.015 | | matches | | 0 | "Only the eyes were the same—that particular, restless grey that always seemed to be looking for a crack in the door." | | 1 | "The smell of his cologne—something citrusy and expensive—lingered in the air, a ghost in the room." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 767 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.02607561929595828 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002607561929595828 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 137 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 137 | | mean | 12.05 | | std | 7.24 | | cv | 0.601 | | sampleLengths | | 0 | 13 | | 1 | 3 | | 2 | 21 | | 3 | 6 | | 4 | 3 | | 5 | 30 | | 6 | 24 | | 7 | 17 | | 8 | 18 | | 9 | 4 | | 10 | 21 | | 11 | 5 | | 12 | 14 | | 13 | 13 | | 14 | 9 | | 15 | 25 | | 16 | 14 | | 17 | 3 | | 18 | 8 | | 19 | 1 | | 20 | 14 | | 21 | 13 | | 22 | 26 | | 23 | 21 | | 24 | 10 | | 25 | 17 | | 26 | 22 | | 27 | 6 | | 28 | 24 | | 29 | 18 | | 30 | 8 | | 31 | 20 | | 32 | 7 | | 33 | 5 | | 34 | 8 | | 35 | 5 | | 36 | 8 | | 37 | 20 | | 38 | 27 | | 39 | 15 | | 40 | 6 | | 41 | 10 | | 42 | 8 | | 43 | 8 | | 44 | 22 | | 45 | 7 | | 46 | 9 | | 47 | 9 | | 48 | 15 | | 49 | 16 |
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| 38.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.25547445255474455 | | totalSentences | 137 | | uniqueOpeners | 35 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 87 | | matches | | 0 | "Only the eyes were the" |
| | ratio | 0.011 | |
| 36.09% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 87 | | matches | | 0 | "He didn't stop pouring the" | | 1 | "He never did." | | 2 | "she muttered, though her voice" | | 3 | "They were out of place." | | 4 | "It was deeper than she" | | 5 | "She didn't let go of" | | 6 | "He looked like a different" | | 7 | "She dropped the glass into" | | 8 | "She felt Silas’s presence move" | | 9 | "He was leaning against the" | | 10 | "He wasn't looking at them," | | 11 | "He leaned against the mahogany" | | 12 | "He scanned the bar, his" | | 13 | "she said, her voice dropping" | | 14 | "He looked at Silas, then" | | 15 | "She looked past Evan, focusing" | | 16 | "He placed a clean coaster" | | 17 | "His voice was a low," | | 18 | "He sized Silas up, his" | | 19 | "He leaned forward, his hazel" |
| | ratio | 0.46 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 87 | | matches | | 0 | "The whiskey glass shattered against" | | 1 | "Silas barked the command from" | | 2 | "He didn't stop pouring the" | | 3 | "He never did." | | 4 | "The Raven's Nest was too" | | 5 | "Aurora ducked down, her black" | | 6 | "The crescent scar on her" | | 7 | "she muttered, though her voice" | | 8 | "A pair of polished, expensive" | | 9 | "They were out of place." | | 10 | "The Nest was a sanctuary" | | 11 | "The voice hit Aurora like" | | 12 | "It was deeper than she" | | 13 | "The Welsh lilt had been" | | 14 | "Aurora stood slowly." | | 15 | "She didn't let go of" | | 16 | "He looked like a different" | | 17 | "The boy who had chased" | | 18 | "She dropped the glass into" | | 19 | "She felt Silas’s presence move" |
| | ratio | 0.954 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 99.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 3 | | matches | | 0 | "The Raven's Nest was too crowded for apologies, the air thick with the smell of damp wool and stale tobacco that seemed to seep out of the old Soho brickwork." | | 1 | "In his place stood a man in a charcoal wool overcoat that cost more than her car, his hair groomed to a perfection that felt clinical." | | 2 | "He leaned against the mahogany bar, his posture projecting a casual ownership of the space that made Aurora’s skin crawl." |
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| 31.25% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 3 | | matches | | 0 | "she muttered, though her voice was lost to the roar of a Friday night crowd" | | 1 | "she said, her voice dropping an octave" | | 2 | "Silas said, his voice dropping to that dangerous, quiet register" |
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| 95.45% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she snapped (snap)" | | 2 | "Silas hissed (hiss)" |
| | dialogueSentences | 55 | | tagDensity | 0.236 | | leniency | 0.473 | | rawRatio | 0.231 | | effectiveRatio | 0.109 | |