| 53.66% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said quietly [quietly]" | | 1 | "she said quietly [quietly]" | | 2 | "She pushed back [back]" |
| | dialogueSentences | 41 | | tagDensity | 0.463 | | leniency | 0.927 | | rawRatio | 0.158 | | effectiveRatio | 0.146 | |
| 81.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1642 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slowly" | | 1 | "precisely" | | 2 | "quickly" | | 3 | "really" |
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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) | |
| 48.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1642 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "familiar" | | 1 | "chaotic" | | 2 | "tapestry" | | 3 | "measured" | | 4 | "calibrated" | | 5 | "unspoken" | | 6 | "silence" | | 7 | "tracing" | | 8 | "fractured" | | 9 | "weight" | | 10 | "calculated" | | 11 | "tension" | | 12 | "pulse" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1640 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1268 | | uniqueNames | 13 | | maxNameDensity | 0.47 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Thomas" | | discoveredNames | | London | 3 | | Raven | 1 | | Nest | 1 | | Coleridge | 1 | | Silas | 4 | | Thomas | 5 | | Cardiff | 2 | | Berlin | 1 | | Rory | 6 | | Old | 1 | | Bailey | 1 | | Yu-Fei | 1 | | Tuesday | 1 |
| | persons | | 0 | "Raven" | | 1 | "Coleridge" | | 2 | "Silas" | | 3 | "Thomas" | | 4 | "Rory" | | 5 | "Old" | | 6 | "Bailey" | | 7 | "Yu-Fei" |
| | places | | 0 | "London" | | 1 | "Cardiff" | | 2 | "Berlin" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like armor now, necessary and cold" |
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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 | 1640 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 54.67 | | std | 47.07 | | cv | 0.861 | | sampleLengths | | 0 | 177 | | 1 | 166 | | 2 | 160 | | 3 | 73 | | 4 | 47 | | 5 | 84 | | 6 | 63 | | 7 | 58 | | 8 | 30 | | 9 | 53 | | 10 | 49 | | 11 | 5 | | 12 | 75 | | 13 | 129 | | 14 | 15 | | 15 | 29 | | 16 | 16 | | 17 | 83 | | 18 | 15 | | 19 | 32 | | 20 | 67 | | 21 | 17 | | 22 | 35 | | 23 | 13 | | 24 | 39 | | 25 | 4 | | 26 | 15 | | 27 | 17 | | 28 | 16 | | 29 | 58 |
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| 83.14% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 111 | | matches | | 0 | "being drawn" | | 1 | "was swept" | | 2 | "was cropped" | | 3 | "was tucked" | | 4 | "was calibrated" | | 5 | "were calloused" | | 6 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 220 | | matches | | |
| 99.57% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 132 | | ratio | 0.015 | | matches | | 0 | "Maps papered the walls in a chaotic tapestry—faded topography of places she’d only read about, black-and-white photographs of strangers caught in moments she couldn’t place." | | 1 | "As he reached for a bottle of gin, his left leg gave a slight, almost imperceptible hitch—the old knee injury that had ended a career in MI6 and birthed this place." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1281 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.03044496487119438 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.01327088212334114 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 12.42 | | std | 9.35 | | cv | 0.753 | | sampleLengths | | 0 | 25 | | 1 | 25 | | 2 | 19 | | 3 | 20 | | 4 | 25 | | 5 | 13 | | 6 | 7 | | 7 | 31 | | 8 | 7 | | 9 | 5 | | 10 | 26 | | 11 | 24 | | 12 | 11 | | 13 | 31 | | 14 | 4 | | 15 | 26 | | 16 | 7 | | 17 | 12 | | 18 | 7 | | 19 | 7 | | 20 | 11 | | 21 | 6 | | 22 | 21 | | 23 | 12 | | 24 | 15 | | 25 | 5 | | 26 | 18 | | 27 | 1 | | 28 | 10 | | 29 | 21 | | 30 | 4 | | 31 | 10 | | 32 | 21 | | 33 | 16 | | 34 | 4 | | 35 | 18 | | 36 | 17 | | 37 | 8 | | 38 | 14 | | 39 | 6 | | 40 | 6 | | 41 | 9 | | 42 | 35 | | 43 | 3 | | 44 | 5 | | 45 | 7 | | 46 | 3 | | 47 | 10 | | 48 | 9 | | 49 | 9 |
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| 40.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.3181818181818182 | | totalSentences | 132 | | uniqueOpeners | 42 | |
| 33.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 101 | | matches | | 0 | "Instead, he was here, vibrating" |
| | ratio | 0.01 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 56 | | totalSentences | 101 | | matches | | 0 | "She shook her umbrella, water" | | 1 | "She knew, too, that the" | | 2 | "She kept her hands in" | | 3 | "His grey-streaked auburn hair was" | | 4 | "He carried himself with a" | | 5 | "He never mentioned it." | | 6 | "He just worked around it," | | 7 | "He didn’t look up when" | | 8 | "He never did when she" | | 9 | "He knew her steps on" | | 10 | "He knew the rhythm of" | | 11 | "He only watched when he" | | 12 | "He turned as the door" | | 13 | "She hadn’t heard the name" | | 14 | "He looked hollowed out." | | 15 | "His hair, once a careless" | | 16 | "His eyes, the same warm" | | 17 | "She didn’t move immediately." | | 18 | "Her straight, shoulder-length black hair" | | 19 | "She kept her bright blue" |
| | ratio | 0.554 | |
| 9.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 91 | | totalSentences | 101 | | matches | | 0 | "The green neon sign above" | | 1 | "Rory pulled her collar against" | | 2 | "The air inside smelled of" | | 3 | "She shook her umbrella, water" | | 4 | "Maps papered the walls in" | | 5 | "A floor-to-ceiling bookshelf dominated the" | | 6 | "Rory knew better than to" | | 7 | "She knew, too, that the" | | 8 | "She kept her hands in" | | 9 | "Silas had taught her that." | | 10 | "His grey-streaked auburn hair was" | | 11 | "He carried himself with a" | | 12 | "He never mentioned it." | | 13 | "He just worked around it," | | 14 | "He didn’t look up when" | | 15 | "He never did when she" | | 16 | "He knew her steps on" | | 17 | "He knew the rhythm of" | | 18 | "He only watched when he" | | 19 | "That was when she saw" |
| | ratio | 0.901 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 101 | | matches | (empty) | | ratio | 0 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 6 | | matches | | 0 | "As he reached for a bottle of gin, his left leg gave a slight, almost imperceptible hitch—the old knee injury that had ended a career in MI6 and birthed this pl…" | | 1 | "His eyes, the same warm brown, held a frantic, guarded energy that made her chest tighten." | | 2 | "She thought of her own life: the damp that seeped through her ceiling, the endless shift of carrying takeout through London traffic for Yu-Fei’s restaurant, the…" | | 3 | "The girl who’d read law journals aloud in a drafty dorm room was gone." | | 4 | "In her place was a woman who calculated exits, who kept her scars hidden until they were necessary, who had learned that quiet often spoke louder than convictio…" | | 5 | "It was the quiet, suffocating weight of two paths that had diverged on a Tuesday afternoon four years ago, neither knowing it was the last time they’d stand on …" |
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| 98.68% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 1 | | matches | | 0 | "He ran, the gesture so painfully familiar it made her ribs ache" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 41 | | tagDensity | 0.293 | | leniency | 0.585 | | rawRatio | 0.083 | | effectiveRatio | 0.049 | |