| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 45 | | tagDensity | 0.289 | | leniency | 0.578 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1336 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 73.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1336 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "scanning" | | 1 | "etched" | | 2 | "facade" | | 3 | "footsteps" | | 4 | "marble" | | 5 | "pulsed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 84 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 26 | | totalWords | 1336 | | ratio | 0.019 | | matches | | 0 | "He opened the door, Detective. He won't be the last. Come to the Market before it moves, or the next body will be someone you know." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 830 | | uniqueNames | 11 | | maxNameDensity | 1.45 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | British | 1 | | Museum | 1 | | Reeves | 7 | | Quinn | 12 | | Morris | 2 | | Egyptian | 1 | | Kowalski | 2 | | Eva | 10 | | Tube | 1 | | Detective | 1 | | Market | 1 |
| | persons | | 0 | "Museum" | | 1 | "Reeves" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" |
| | places | | | globalScore | 0.777 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like charcoal but had an odd iride" |
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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 | 1336 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 25.21 | | std | 20.87 | | cv | 0.828 | | sampleLengths | | 0 | 4 | | 1 | 86 | | 2 | 36 | | 3 | 2 | | 4 | 21 | | 5 | 47 | | 6 | 3 | | 7 | 28 | | 8 | 62 | | 9 | 52 | | 10 | 40 | | 11 | 8 | | 12 | 2 | | 13 | 4 | | 14 | 29 | | 15 | 13 | | 16 | 25 | | 17 | 6 | | 18 | 40 | | 19 | 6 | | 20 | 25 | | 21 | 30 | | 22 | 79 | | 23 | 37 | | 24 | 2 | | 25 | 19 | | 26 | 24 | | 27 | 32 | | 28 | 5 | | 29 | 12 | | 30 | 3 | | 31 | 39 | | 32 | 15 | | 33 | 4 | | 34 | 52 | | 35 | 20 | | 36 | 1 | | 37 | 13 | | 38 | 7 | | 39 | 59 | | 40 | 17 | | 41 | 57 | | 42 | 2 | | 43 | 11 | | 44 | 8 | | 45 | 34 | | 46 | 19 | | 47 | 52 | | 48 | 19 | | 49 | 52 |
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| 88.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 84 | | matches | | 0 | "been opened" | | 1 | "been pulled" | | 2 | "was etched" | | 3 | "was pulled" |
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| 99.75% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 133 | | matches | | 0 | "was looking" | | 1 | "was climbing" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 116 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 834 | | adjectiveStacks | 1 | | stackExamples | | 0 | "pressing cold against her" |
| | adverbCount | 28 | | adverbRatio | 0.03357314148681055 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.01079136690647482 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 11.52 | | std | 8.61 | | cv | 0.748 | | sampleLengths | | 0 | 4 | | 1 | 27 | | 2 | 17 | | 3 | 19 | | 4 | 7 | | 5 | 16 | | 6 | 20 | | 7 | 16 | | 8 | 2 | | 9 | 21 | | 10 | 4 | | 11 | 30 | | 12 | 8 | | 13 | 5 | | 14 | 3 | | 15 | 8 | | 16 | 20 | | 17 | 5 | | 18 | 21 | | 19 | 19 | | 20 | 7 | | 21 | 3 | | 22 | 4 | | 23 | 3 | | 24 | 10 | | 25 | 13 | | 26 | 19 | | 27 | 7 | | 28 | 3 | | 29 | 9 | | 30 | 24 | | 31 | 7 | | 32 | 8 | | 33 | 2 | | 34 | 4 | | 35 | 3 | | 36 | 5 | | 37 | 21 | | 38 | 7 | | 39 | 6 | | 40 | 7 | | 41 | 4 | | 42 | 11 | | 43 | 3 | | 44 | 6 | | 45 | 18 | | 46 | 22 | | 47 | 3 | | 48 | 3 | | 49 | 21 |
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| 65.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.43103448275862066 | | totalSentences | 116 | | uniqueOpeners | 50 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 81 | | matches | | 0 | "Instead, the floor around him" | | 1 | "Unnaturally so for an object" | | 2 | "Then the mask slid back" | | 3 | "Somewhere above them, footsteps crossed" |
| | ratio | 0.049 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 81 | | matches | | 0 | "His throat had been opened" | | 1 | "His skin had a waxy," | | 2 | "She pushed the thought down." | | 3 | "She moved along the shelves," | | 4 | "She reached in." | | 5 | "She held it up for" | | 6 | "It pointed steadily toward the" | | 7 | "She pocketed it." | | 8 | "Her curly red hair was" | | 9 | "She also noticed the faint" | | 10 | "She placed the brass compass" | | 11 | "Her eyes widened, her fingers" | | 12 | "She nodded at Eva's hands" | | 13 | "She'd attributed it to old" | | 14 | "She followed him down the" | | 15 | "She read the address, and" | | 16 | "She'd been to that address" | | 17 | "Her phone buzzed." | | 18 | "*He opened the door, Detective." | | 19 | "He won't be the last." |
| | ratio | 0.247 | |
| 46.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 81 | | matches | | 0 | "The body hadn't bled." | | 1 | "Quinn crouched beside the remains" | | 2 | "The man, mid-thirties by the" | | 3 | "His throat had been opened" | | 4 | "His skin had a waxy," | | 5 | "Quinn tilted her head." | | 6 | "The wound itself was clean," | | 7 | "DS Morris had been standing" | | 8 | "She pushed the thought down." | | 9 | "Reeves consulted his notebook" | | 10 | "Quinn stood, her knees protesting." | | 11 | "The archive stretched deeper into" | | 12 | "The air tasted of recycled" | | 13 | "She moved along the shelves," | | 14 | "Sumerian cylinder seals." | | 15 | "Mesopotamian clay tablets." | | 16 | "Quinn shone her torch into" | | 17 | "The beam caught something on" | | 18 | "She reached in." | | 19 | "A small brass compass, its" |
| | ratio | 0.827 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 27.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 5 | | matches | | 0 | "His throat had been opened from ear to ear, a wound that should have painted the beige linoleum crimson." | | 1 | "Quinn shone her torch into the gap and caught glimpses of old brickwork that didn't match the museum's construction." | | 2 | "The face was etched with symbols she didn't recognise, and the needle spun in lazy, uneven circles, as if it couldn't settle on north." | | 3 | "She also noticed the faint discolouration on Eva's fingertips, a greyish residue under the nails that looked like charcoal but had an odd iridescent quality." | | 4 | "The compass needle in her pocket pulsed against her thigh, pointing steadily downward, toward the archives, toward the gap in the wall, toward whatever was clim…" |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva stood, her chair scraping against linoleum" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |