| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.448 | | leniency | 0.897 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 77.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1324 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "very" | | 1 | "gently" | | 2 | "softly" | | 3 | "lazily" | | 4 | "quickly" | | 5 | "really" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 39.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1324 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "oppressive" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "scanning" | | 4 | "perfect" | | 5 | "raced" | | 6 | "chill" | | 7 | "etched" | | 8 | "complex" | | 9 | "velvet" | | 10 | "intricate" | | 11 | "quivered" | | 12 | "unwavering" | | 13 | "throbbed" |
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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 | 93 | | matches | (empty) | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1312 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 90.86% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 930 | | uniqueNames | 8 | | maxNameDensity | 1.18 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Harlow | 1 | | Quinn | 11 | | Two | 1 | | Amir | 10 | | Chen | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Two" | | 3 | "Amir" | | 4 | "Chen" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.909 | | windowScore | 1 | |
| 77.54% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like yellowed bone" | | 1 | "pattern that seemed to swim in the torchlight if you stared too long" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.762 | | wordCount | 1312 | | matches | | 0 | "not with cardinal points, but with intricate, spiralling sigils" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 39.76 | | std | 25.08 | | cv | 0.631 | | sampleLengths | | 0 | 81 | | 1 | 30 | | 2 | 61 | | 3 | 55 | | 4 | 68 | | 5 | 10 | | 6 | 16 | | 7 | 35 | | 8 | 67 | | 9 | 7 | | 10 | 8 | | 11 | 59 | | 12 | 66 | | 13 | 17 | | 14 | 51 | | 15 | 31 | | 16 | 35 | | 17 | 11 | | 18 | 52 | | 19 | 12 | | 20 | 35 | | 21 | 104 | | 22 | 48 | | 23 | 11 | | 24 | 11 | | 25 | 13 | | 26 | 35 | | 27 | 34 | | 28 | 54 | | 29 | 45 | | 30 | 75 | | 31 | 10 | | 32 | 65 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 93 | | matches | | 0 | "was blistered" | | 1 | "was clenched" | | 2 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 154 | | matches | (empty) | |
| 11.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 4 | | flaggedSentences | 5 | | totalSentences | 109 | | ratio | 0.046 | | matches | | 0 | "Male, late twenties, dressed in expensive but practical dark clothing—technical trousers, a merino wool jumper." | | 1 | "The other, heavier, booted—likely the assailant." | | 2 | "The air there felt different—thicker, with a faint, ozone tang that made the hair on her arms stand up." | | 3 | "Inside, nestled in padded compartments, were items that made no sense for a mugger’s target or a casual urban explorer: several small vials of iridescent liquid stoppered with wax; a bundle of dried herbs tied with silver wire; a notebook filled with dense, handwritten script in a language she didn’t recognize; and, wrapped in velvet, a small brass compass." | | 4 | "“He was intercepted. He was coming here to meet someone, or to go somewhere. He had the token for entry. The backpack is a kit. Specialized. The burn isn’t from a taser; it’s a kill shot. Something that leaves minimal evidence. The assailant didn’t follow him in and didn’t leave on foot.”" |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 660 | | adjectiveStacks | 1 | | stackExamples | | 0 | "perfect, undisturbed archaeological layer" |
| | adverbCount | 16 | | adverbRatio | 0.024242424242424242 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004545454545454545 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 12.04 | | std | 9.95 | | cv | 0.827 | | sampleLengths | | 0 | 13 | | 1 | 20 | | 2 | 21 | | 3 | 15 | | 4 | 12 | | 5 | 19 | | 6 | 7 | | 7 | 4 | | 8 | 19 | | 9 | 5 | | 10 | 15 | | 11 | 9 | | 12 | 10 | | 13 | 3 | | 14 | 48 | | 15 | 7 | | 16 | 3 | | 17 | 9 | | 18 | 4 | | 19 | 10 | | 20 | 26 | | 21 | 7 | | 22 | 6 | | 23 | 3 | | 24 | 6 | | 25 | 4 | | 26 | 6 | | 27 | 10 | | 28 | 12 | | 29 | 9 | | 30 | 2 | | 31 | 12 | | 32 | 9 | | 33 | 20 | | 34 | 12 | | 35 | 16 | | 36 | 10 | | 37 | 7 | | 38 | 8 | | 39 | 6 | | 40 | 8 | | 41 | 19 | | 42 | 12 | | 43 | 3 | | 44 | 7 | | 45 | 4 | | 46 | 8 | | 47 | 9 | | 48 | 4 | | 49 | 5 |
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| 48.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.3211009174311927 | | totalSentences | 109 | | uniqueOpeners | 35 | |
| 37.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 88 | | matches | | 0 | "Just below the hairline, near" |
| | ratio | 0.011 | |
| 65.45% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 88 | | matches | | 0 | "Her colleague, DS Amir Chen," | | 1 | "He glanced up as her" | | 2 | "She took in the scene." | | 3 | "Her eyes tracked from the" | | 4 | "It was too neat." | | 5 | "She moved past Amir, her" | | 6 | "They converged here." | | 7 | "she said, her voice flat" | | 8 | "He stood, brushing dust from" | | 9 | "It was a perfect, undisturbed" | | 10 | "She returned to the body," | | 11 | "She leaned closer, ignoring the" | | 12 | "She tilted his head gently." | | 13 | "It was a clean, cauterized" | | 14 | "She’d seen marks like that" | | 15 | "Her light swept over the" | | 16 | "They were clean, no defensive" | | 17 | "It was etched with a" | | 18 | "She bagged the token, her" | | 19 | "Her gaze drifted past the" |
| | ratio | 0.386 | |
| 62.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 88 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn’s breath fogged" | | 2 | "The scene was at the" | | 3 | "The body lay face down," | | 4 | "Her colleague, DS Amir Chen," | | 5 | "He glanced up as her" | | 6 | "Quinn pulled on latex gloves," | | 7 | "She took in the scene." | | 8 | "A small, expensive-looking backpack lay" | | 9 | "Amir pointed with his pen" | | 10 | "Quinn didn’t answer." | | 11 | "Her eyes tracked from the" | | 12 | "It was too neat." | | 13 | "She moved past Amir, her" | | 14 | "The dust was thick, a" | | 15 | "The other, heavier, booted—likely the" | | 16 | "They converged here." | | 17 | "she said, her voice flat" | | 18 | "He stood, brushing dust from" | | 19 | "The boot prints came in," |
| | ratio | 0.795 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 56.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 4 | | matches | | 0 | "Two uniformed officers stood by a cordon tape that looked ridiculous in the vast emptiness." | | 1 | "It was etched with a complex, interlocking pattern that seemed to swim in the torchlight if you stared too long." | | 2 | "The air there felt different—thicker, with a faint, ozone tang that made the hair on her arms stand up." | | 3 | "Inside, nestled in padded compartments, were items that made no sense for a mugger’s target or a casual urban explorer: several small vials of iridescent liquid…" |
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| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, her voice flat" | | 1 | "she said, more to herself than to Amir" | | 2 | "she lifted, its needle still fixed on the tunnel," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.207 | | leniency | 0.414 | | rawRatio | 0 | | effectiveRatio | 0 | |