| 69.57% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said again [again]" | | 1 | "she said flatly [flatly]" | | 2 | "he said quietly [quietly]" |
| | dialogueSentences | 41 | | tagDensity | 0.561 | | leniency | 1 | | rawRatio | 0.13 | | effectiveRatio | 0.13 | |
| 90.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1579 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "completely" |
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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) | |
| 62.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1579 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "measured" | | 1 | "glinting" | | 2 | "traced" | | 3 | "flicked" | | 4 | "pulse" | | 5 | "fractured" | | 6 | "flicker" | | 7 | "calculating" | | 8 | "pristine" | | 9 | "resolved" | | 10 | "silence" | | 11 | "warmth" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 5 | | totalWords | 1568 | | ratio | 0.003 | | matches | | 0 | "clack" | | 1 | "Evan Vaughan. Senior Associate." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1192 | | uniqueNames | 14 | | maxNameDensity | 1.01 | | worstName | "Evan" | | maxWindowNameDensity | 3 | | worstWindowName | "Evan" | | discoveredNames | | Soho | 1 | | Tuesday | 1 | | Raven | 1 | | Nest | 1 | | Silas | 9 | | Edison | 1 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 | | Cardiff | 1 | | Rory | 11 | | Evan | 12 | | Roath | 1 | | Vaughan | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Edison" | | 4 | "Rory" | | 5 | "Evan" | | 6 | "Vaughan" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "Roath" |
| | globalScore | 0.997 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | 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 | 1568 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 105 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 34.84 | | std | 21.86 | | cv | 0.627 | | sampleLengths | | 0 | 68 | | 1 | 96 | | 2 | 47 | | 3 | 33 | | 4 | 12 | | 5 | 25 | | 6 | 15 | | 7 | 79 | | 8 | 25 | | 9 | 4 | | 10 | 10 | | 11 | 36 | | 12 | 40 | | 13 | 72 | | 14 | 10 | | 15 | 15 | | 16 | 43 | | 17 | 38 | | 18 | 13 | | 19 | 23 | | 20 | 2 | | 21 | 47 | | 22 | 26 | | 23 | 7 | | 24 | 34 | | 25 | 71 | | 26 | 35 | | 27 | 27 | | 28 | 39 | | 29 | 12 | | 30 | 43 | | 31 | 59 | | 32 | 25 | | 33 | 22 | | 34 | 57 | | 35 | 33 | | 36 | 22 | | 37 | 42 | | 38 | 16 | | 39 | 58 | | 40 | 41 | | 41 | 4 | | 42 | 31 | | 43 | 41 | | 44 | 70 |
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| 84.86% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 86 | | matches | | 0 | "was trimmed" | | 1 | "was cropped" | | 2 | "been slouched" | | 3 | "was gone" | | 4 | "being pulled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 185 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 105 | | ratio | 0.076 | | matches | | 0 | "The Raven’s Nest smelled off tonight—less like the usual stale gin and old floorboards, and more like damp wool and ozone from the storm outside." | | 1 | "Her wrist twitched under her sleeve—a habit whenever the weather turned sharp—and her thumb automatically traced the tiny, crescent-shaped scar on her left arm." | | 2 | "His hands, rested flat on the polished mahogany, were still—no nervous drumming, no trembling knuckles." | | 3 | "She kept her feet planted, her height—five-foot-six—feeling entirely inadequate against the height of the room, though she knew she could run if she needed to." | | 4 | "He looked at his drink—a single measure of clear liquor over a square cube of ice." | | 5 | "Evan winced, a tiny, fractured movement around his eyes—the only sign that the man who used to scream at her in a cramped kitchen in Roath was still somewhere beneath the expensive cloth." | | 6 | "He looked at Silas, then back at Rory, noticing for the first time the way she stood—balanced on the balls of her feet, her elbows loose, her eyes constantly calculating the distance between him, the door, and the heavy brass candlestick on the end of the bar." | | 7 | "For a second, Evan’s eyes brightened with a terrible, desperate hope—the hope that time could be smoothed over, that a bad decade could be resolved with an offer of help from a man who had made himself respectable." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1107 | | adjectiveStacks | 2 | | stackExamples | | 0 | "usual measured, heavy rhythm." | | 1 | "tiny, crescent-shaped scar" |
| | adverbCount | 37 | | adverbRatio | 0.03342366757000903 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.015356820234869015 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 14.93 | | std | 10.18 | | cv | 0.682 | | sampleLengths | | 0 | 21 | | 1 | 22 | | 2 | 25 | | 3 | 13 | | 4 | 31 | | 5 | 19 | | 6 | 33 | | 7 | 23 | | 8 | 24 | | 9 | 5 | | 10 | 28 | | 11 | 12 | | 12 | 3 | | 13 | 22 | | 14 | 12 | | 15 | 3 | | 16 | 19 | | 17 | 21 | | 18 | 5 | | 19 | 34 | | 20 | 6 | | 21 | 4 | | 22 | 15 | | 23 | 4 | | 24 | 10 | | 25 | 14 | | 26 | 22 | | 27 | 11 | | 28 | 4 | | 29 | 25 | | 30 | 5 | | 31 | 16 | | 32 | 48 | | 33 | 3 | | 34 | 6 | | 35 | 4 | | 36 | 12 | | 37 | 3 | | 38 | 11 | | 39 | 1 | | 40 | 12 | | 41 | 4 | | 42 | 7 | | 43 | 8 | | 44 | 33 | | 45 | 5 | | 46 | 13 | | 47 | 8 | | 48 | 15 | | 49 | 2 |
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| 44.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.34285714285714286 | | totalSentences | 105 | | uniqueOpeners | 36 | |
| 43.29% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 77 | | matches | | 0 | "Instead, he just took a" |
| | ratio | 0.013 | |
| 38.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 77 | | matches | | 0 | "His left leg hitched slightly" | | 1 | "His grey-streaked auburn beard was" | | 2 | "He caught her eye, gave" | | 3 | "Her wrist twitched under her" | | 4 | "She hadn't intended to stay." | | 5 | "She had a morning shift" | | 6 | "It wasn't Silas." | | 7 | "She turned slowly." | | 8 | "His hair was cropped close," | | 9 | "His fingernails were clean." | | 10 | "His hands, rested flat on" | | 11 | "he said again" | | 12 | "She didn't sit down." | | 13 | "She kept her feet planted," | | 14 | "He looked at his drink—a" | | 15 | "He looked at her then," | | 16 | "she said flatly" | | 17 | "He paused, searching for a" | | 18 | "He took a slow sip" | | 19 | "she said, her voice dropping" |
| | ratio | 0.455 | |
| 24.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 77 | | matches | | 0 | "The green neon sign above" | | 1 | "Rory pushed the heavy oak" | | 2 | "The Raven’s Nest smelled off" | | 3 | "His left leg hitched slightly" | | 4 | "His grey-streaked auburn beard was" | | 5 | "He caught her eye, gave" | | 6 | "Rory shook the rain from" | | 7 | "Her wrist twitched under her" | | 8 | "She hadn't intended to stay." | | 9 | "She had a morning shift" | | 10 | "a voice said from the" | | 11 | "It wasn't Silas." | | 12 | "The voice was smooth, stripped" | | 13 | "Rory froze, her hand hovering" | | 14 | "She turned slowly." | | 15 | "His hair was cropped close," | | 16 | "The Evan she remembered had" | | 17 | "This man sat like a" | | 18 | "His fingernails were clean." | | 19 | "His hands, rested flat on" |
| | ratio | 0.87 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 77 | | matches | (empty) | | ratio | 0 | |
| 94.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 3 | | matches | | 0 | "She had a morning shift at Golden Empress, and Yu-Fei was relentless about punctuality, but the flat upstairs was quiet in a way that made her teeth ache." | | 1 | "Evan winced, a tiny, fractured movement around his eyes—the only sign that the man who used to scream at her in a cramped kitchen in Roath was still somewhere b…" | | 2 | "For a second, Evan’s eyes brightened with a terrible, desperate hope—the hope that time could be smoothed over, that a bad decade could be resolved with an offe…" |
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| 81.52% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory said, her voice smooth and entirely devoid of malice" | | 1 | "Silas said, his voice a low rumble" |
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| 76.83% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 3 | | fancyTags | | 0 | "he murmured (murmur)" | | 1 | "Evan repeated (repeat)" | | 2 | "he whispered (whisper)" |
| | dialogueSentences | 41 | | tagDensity | 0.415 | | leniency | 0.829 | | rawRatio | 0.176 | | effectiveRatio | 0.146 | |