| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.229 | | leniency | 0.458 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.62% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1479 | | 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) | |
| 45.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1479 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "gloom" | | 1 | "scanned" | | 2 | "traced" | | 3 | "shattered" | | 4 | "weight" | | 5 | "intricate" | | 6 | "etched" | | 7 | "magnetic" | | 8 | "pawn" | | 9 | "methodical" | | 10 | "furrowing" | | 11 | "porcelain" | | 12 | "chill" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 123 | | 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 | 0 | | markdownWords | 0 | | totalWords | 1477 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 49.60% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 996 | | uniqueNames | 7 | | maxNameDensity | 2.01 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Miller" | | discoveredNames | | Harlow | 20 | | Quinn | 1 | | Camden | 1 | | High | 1 | | Street | 1 | | Miller | 16 | | Victorian | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Miller" |
| | places | (empty) | | globalScore | 0.496 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | 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 | 1477 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 72 | | mean | 20.51 | | std | 15.32 | | cv | 0.747 | | sampleLengths | | 0 | 57 | | 1 | 18 | | 2 | 4 | | 3 | 24 | | 4 | 17 | | 5 | 52 | | 6 | 4 | | 7 | 28 | | 8 | 17 | | 9 | 28 | | 10 | 5 | | 11 | 7 | | 12 | 48 | | 13 | 19 | | 14 | 29 | | 15 | 4 | | 16 | 1 | | 17 | 10 | | 18 | 11 | | 19 | 52 | | 20 | 11 | | 21 | 21 | | 22 | 33 | | 23 | 8 | | 24 | 8 | | 25 | 24 | | 26 | 33 | | 27 | 16 | | 28 | 10 | | 29 | 15 | | 30 | 4 | | 31 | 38 | | 32 | 15 | | 33 | 10 | | 34 | 26 | | 35 | 10 | | 36 | 36 | | 37 | 9 | | 38 | 35 | | 39 | 21 | | 40 | 44 | | 41 | 8 | | 42 | 41 | | 43 | 9 | | 44 | 58 | | 45 | 26 | | 46 | 3 | | 47 | 10 | | 48 | 10 | | 49 | 17 |
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| 93.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 86 | | matches | | 0 | "been wiped" | | 1 | "was cracked" | | 2 | "was elongated" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 157 | | matches | (empty) | |
| 96.40% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 123 | | ratio | 0.016 | | matches | | 0 | "The weight felt wrong—far too heavy for hollow brass." | | 1 | "The compass needle pulled hard toward the solid brick wall five yards down the line—a wall sealing off a disused branch line closed since 1924." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1003 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.019940179461615155 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006979062811565304 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 123 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 123 | | mean | 12.01 | | std | 6.69 | | cv | 0.558 | | sampleLengths | | 0 | 21 | | 1 | 13 | | 2 | 1 | | 3 | 22 | | 4 | 18 | | 5 | 4 | | 6 | 15 | | 7 | 9 | | 8 | 17 | | 9 | 6 | | 10 | 9 | | 11 | 14 | | 12 | 17 | | 13 | 6 | | 14 | 4 | | 15 | 18 | | 16 | 10 | | 17 | 17 | | 18 | 16 | | 19 | 8 | | 20 | 4 | | 21 | 5 | | 22 | 7 | | 23 | 5 | | 24 | 20 | | 25 | 9 | | 26 | 14 | | 27 | 10 | | 28 | 9 | | 29 | 13 | | 30 | 16 | | 31 | 4 | | 32 | 1 | | 33 | 10 | | 34 | 11 | | 35 | 13 | | 36 | 15 | | 37 | 7 | | 38 | 17 | | 39 | 11 | | 40 | 21 | | 41 | 13 | | 42 | 20 | | 43 | 8 | | 44 | 8 | | 45 | 24 | | 46 | 10 | | 47 | 8 | | 48 | 15 | | 49 | 7 |
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| 59.84% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.39344262295081966 | | totalSentences | 122 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 93.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 79 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "He shone his light down" | | 2 | "Her coat cleared the damp" | | 3 | "She adjusted her grip on" | | 4 | "She stopped three paces short" | | 5 | "Her brown eyes narrowed." | | 6 | "She dipped a gloved index" | | 7 | "She stood up, pulling back" | | 8 | "He wore a tailored wool" | | 9 | "She pulled a thin wooden" | | 10 | "She traced the rim of" | | 11 | "She stepped off the platform," | | 12 | "She crouched, pulling fresh nitrile" | | 13 | "It was a heavy brass" | | 14 | "Its surface carried a thick" | | 15 | "She turned it over in" | | 16 | "She stood up, staring into" | | 17 | "She held the brass compass" | | 18 | "They were not cardinal directions." | | 19 | "She unbuttoned her coat, pulling" |
| | ratio | 0.316 | |
| 23.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 79 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "Flashlight beams cut through the" | | 2 | "Sergeant Miller stepped around a" | | 3 | "He shone his light down" | | 4 | "Harlow stepped off the iron" | | 5 | "Her coat cleared the damp" | | 6 | "She adjusted her grip on" | | 7 | "Victorian white tiles, blackened by" | | 8 | "Miller gestured toward the far" | | 9 | "A heavy yellow tarp covered" | | 10 | "Harlow walked down the edge" | | 11 | "She stopped three paces short" | | 12 | "Her brown eyes narrowed." | | 13 | "Miller swung his torch across" | | 14 | "Harlow pointed her light down." | | 15 | "A three-metre circle of concrete" | | 16 | "Soot had been wiped away" | | 17 | "Miller offered, tapping his notebook" | | 18 | "Harlow crouched, lowering her flashlight" | | 19 | "She dipped a gloved index" |
| | ratio | 0.873 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 2 | | matches | | 0 | "He wore a tailored wool coat fitted with concealed inner pockets that swung open, empty." | | 1 | "Miller leaned in, his brows furrowing as he took in the sharp angles carved into the brass casing." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Miller said, though his tone lost its firm edge" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 2 | | fancyTags | | 0 | "Miller called down (call dow)" | | 1 | "Harlow murmured (murmur)" |
| | dialogueSentences | 48 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.25 | | effectiveRatio | 0.083 | |