| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 90.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1630 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "suddenly" | | 1 | "softly" | | 2 | "very" |
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| 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) | |
| 47.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1630 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "echoed" | | 1 | "silk" | | 2 | "marble" | | 3 | "weight" | | 4 | "tracing" | | 5 | "intricate" | | 6 | "charged" | | 7 | "rhythmic" | | 8 | "throb" | | 9 | "pulse" | | 10 | "silence" | | 11 | "velvet" | | 12 | "stomach" | | 13 | "pumping" | | 14 | "racing" | | 15 | "shattered" |
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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 | 69 | | matches | (empty) | |
| 60.04% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1630 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 1062 | | uniqueNames | 10 | | maxNameDensity | 0.38 | | worstName | "Eva" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 4 | | Moreau | 1 | | Avaros | 1 | | Carrara | 1 | | Cardiff | 1 | | Brick | 2 | | Lane | 2 | | East | 1 | | London | 1 | | Lucien | 3 |
| | persons | | | places | | 0 | "Cardiff" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "East" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 75.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a sudden drop in atmospheric" | | 1 | "looked like a misplaced statue in an atti" |
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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 | 1630 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 60 | | mean | 27.17 | | std | 21.58 | | cv | 0.794 | | sampleLengths | | 0 | 80 | | 1 | 2 | | 2 | 18 | | 3 | 74 | | 4 | 12 | | 5 | 10 | | 6 | 66 | | 7 | 22 | | 8 | 10 | | 9 | 67 | | 10 | 18 | | 11 | 22 | | 12 | 6 | | 13 | 82 | | 14 | 19 | | 15 | 15 | | 16 | 39 | | 17 | 11 | | 18 | 24 | | 19 | 69 | | 20 | 28 | | 21 | 13 | | 22 | 20 | | 23 | 68 | | 24 | 5 | | 25 | 7 | | 26 | 49 | | 27 | 25 | | 28 | 8 | | 29 | 24 | | 30 | 31 | | 31 | 3 | | 32 | 15 | | 33 | 3 | | 34 | 8 | | 35 | 68 | | 36 | 27 | | 37 | 13 | | 38 | 7 | | 39 | 37 | | 40 | 33 | | 41 | 25 | | 42 | 15 | | 43 | 5 | | 44 | 36 | | 45 | 3 | | 46 | 21 | | 47 | 31 | | 48 | 28 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 69 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 168 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 108 | | ratio | 0 | | matches | (empty) | |
| 76.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1068 | | adjectiveStacks | 4 | | stackExamples | | 0 | "small, rectangular black velvet" | | 1 | "heavy, black metallic canister" | | 2 | "thick, acrid green smoke" | | 3 | "smooth, reflective silver mask" |
| | adverbCount | 31 | | adverbRatio | 0.02902621722846442 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.011235955056179775 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 15.09 | | std | 8 | | cv | 0.53 | | sampleLengths | | 0 | 21 | | 1 | 17 | | 2 | 9 | | 3 | 33 | | 4 | 2 | | 5 | 18 | | 6 | 7 | | 7 | 16 | | 8 | 14 | | 9 | 10 | | 10 | 27 | | 11 | 12 | | 12 | 10 | | 13 | 29 | | 14 | 14 | | 15 | 11 | | 16 | 12 | | 17 | 22 | | 18 | 10 | | 19 | 18 | | 20 | 31 | | 21 | 18 | | 22 | 18 | | 23 | 22 | | 24 | 6 | | 25 | 6 | | 26 | 19 | | 27 | 25 | | 28 | 32 | | 29 | 19 | | 30 | 15 | | 31 | 13 | | 32 | 13 | | 33 | 13 | | 34 | 11 | | 35 | 24 | | 36 | 25 | | 37 | 9 | | 38 | 7 | | 39 | 28 | | 40 | 28 | | 41 | 13 | | 42 | 20 | | 43 | 5 | | 44 | 29 | | 45 | 10 | | 46 | 24 | | 47 | 5 | | 48 | 7 | | 49 | 14 |
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| 44.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.35185185185185186 | | totalSentences | 108 | | uniqueOpeners | 38 | |
| 96.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 69 | | matches | | 0 | "Even the animals knew when" | | 1 | "Instead, he used the tip" |
| | ratio | 0.029 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 69 | | matches | | 0 | "It finally yielded with a" | | 1 | "I didn't wait for the" | | 2 | "I pulled the heavy oak" | | 3 | "He stepped past me, the" | | 4 | "He moved with a predatory" | | 5 | "His presence felt like a" | | 6 | "He came to a halt" | | 7 | "He turned, the platinum blond" | | 8 | "He leaned his weight onto" | | 9 | "He took a step toward" | | 10 | "I didn't retreat, though the" | | 11 | "I could smell him now," | | 12 | "It was a scent that" | | 13 | "I instinctively pulled my sleeve" | | 14 | "It felt hot, a dull" | | 15 | "I had told no one" | | 16 | "He moved again, faster than" | | 17 | "He reached out, his hand" | | 18 | "I flinched, but he didn't" | | 19 | "I looked at his eyes," |
| | ratio | 0.594 | |
| 32.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 69 | | matches | | 0 | "The third deadbolt groaned, a" | | 1 | "It finally yielded with a" | | 2 | "I didn't wait for the" | | 3 | "I pulled the heavy oak" | | 4 | "Lucien Moreau didn't wait for" | | 5 | "He stepped past me, the" | | 6 | "He moved with a predatory" | | 7 | "His presence felt like a" | | 8 | "He came to a halt" | | 9 | "Ptolemy, the tabby cat, uncurled" | | 10 | "The feline’s hackles rose, his" | | 11 | "He turned, the platinum blond" | | 12 | "The harsh light of the" | | 13 | "He leaned his weight onto" | | 14 | "He took a step toward" | | 15 | "I didn't retreat, though the" | | 16 | "I could smell him now," | | 17 | "It was a scent that" | | 18 | "I instinctively pulled my sleeve" | | 19 | "It felt hot, a dull" |
| | ratio | 0.855 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 69 | | matches | | 0 | "If anything, he leaned into" | | 1 | "If we could get to" |
| | ratio | 0.029 | |
| 35.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 8 | | matches | | 0 | "It finally yielded with a sharp metallic crack that echoed through the cramped hallway of Eva’s flat." | | 1 | "I pulled the heavy oak door open, the wood scraping against the uneven floorboards, and found myself staring at a charcoal silk waistcoat that cost more than my…" | | 2 | "It was a scent that triggered a frantic, rhythmic thumping in my chest, a memory of a night in a rain-slicked alleyway in Cardiff that I had spent months trying…" | | 3 | "I looked at his eyes, the amber one glowing with a faint, inner light that made the black one look like a bottomless pit." | | 4 | "He looked entirely out of place against the backdrop of a cracked tiled splashback and a leaking tap that went drip, drip, drip into a plastic basin." | | 5 | "A heavy, black metallic canister skidded across the floorboards, hissing a thick, acrid green smoke that smelled of rot and sulphur." | | 6 | "The figure didn't have a face, only a smooth, reflective silver mask that mirrored my own terrified expression." | | 7 | "The ivory sleeve fell away, revealing a thin, shimmering steel blade that hummed with a low, predatory frequency." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |