| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 46 | | tagDensity | 0.217 | | leniency | 0.435 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1444 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 60.00% | 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) | |
| 51.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1444 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "echoed" | | 1 | "silence" | | 2 | "unreadable" | | 3 | "tension" | | 4 | "chaotic" | | 5 | "weight" | | 6 | "charm" | | 7 | "stark" | | 8 | "leveraging" | | 9 | "could feel" | | 10 | "warmth" |
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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 | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 1432 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 804 | | uniqueNames | 11 | | maxNameDensity | 0.62 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 3 | | Atlantean | 1 | | Edinburgh | 1 | | Sunday | 1 | | Moreau | 1 | | Blackwood | 1 | | French | 1 | | Lucien | 5 | | Aurora | 3 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Aurora" |
| | places | | 0 | "Edinburgh" | | 1 | "Brick" | | 2 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.698 | | wordCount | 1432 | | matches | | 0 | "not at the door, but down the stairwell, his profile sharp" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 29.22 | | std | 21.98 | | cv | 0.752 | | sampleLengths | | 0 | 47 | | 1 | 34 | | 2 | 23 | | 3 | 68 | | 4 | 59 | | 5 | 35 | | 6 | 1 | | 7 | 23 | | 8 | 31 | | 9 | 1 | | 10 | 1 | | 11 | 11 | | 12 | 35 | | 13 | 60 | | 14 | 36 | | 15 | 3 | | 16 | 5 | | 17 | 31 | | 18 | 7 | | 19 | 57 | | 20 | 5 | | 21 | 59 | | 22 | 23 | | 23 | 51 | | 24 | 70 | | 25 | 5 | | 26 | 20 | | 27 | 19 | | 28 | 70 | | 29 | 14 | | 30 | 65 | | 31 | 7 | | 32 | 10 | | 33 | 43 | | 34 | 27 | | 35 | 3 | | 36 | 63 | | 37 | 41 | | 38 | 51 | | 39 | 5 | | 40 | 7 | | 41 | 43 | | 42 | 45 | | 43 | 9 | | 44 | 2 | | 45 | 33 | | 46 | 15 | | 47 | 13 | | 48 | 46 |
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| 96.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 80 | | matches | | 0 | "was closed" | | 1 | "been said" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 135 | | matches | | 0 | "wasn’t expecting" | | 1 | "was looking" |
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| 67.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 113 | | ratio | 0.027 | | matches | | 0 | "Those mismatched eyes—amber and bottomless black—took her in." | | 1 | "The noise of Brick Lane—the distant hum of traffic, a shout from a passerby—seemed to fade into a muffled roar." | | 2 | "He was mere inches away, looking down at her with an expression she couldn’t fully decipher—a mix of grim determination and something else, something weary and haunted." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 813 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.02706027060270603 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0036900369003690036 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 12.67 | | std | 10.52 | | cv | 0.831 | | sampleLengths | | 0 | 5 | | 1 | 10 | | 2 | 15 | | 3 | 17 | | 4 | 4 | | 5 | 6 | | 6 | 7 | | 7 | 10 | | 8 | 7 | | 9 | 12 | | 10 | 11 | | 11 | 13 | | 12 | 28 | | 13 | 11 | | 14 | 16 | | 15 | 7 | | 16 | 4 | | 17 | 16 | | 18 | 17 | | 19 | 4 | | 20 | 11 | | 21 | 5 | | 22 | 7 | | 23 | 7 | | 24 | 16 | | 25 | 1 | | 26 | 4 | | 27 | 8 | | 28 | 6 | | 29 | 5 | | 30 | 17 | | 31 | 10 | | 32 | 4 | | 33 | 1 | | 34 | 1 | | 35 | 11 | | 36 | 11 | | 37 | 24 | | 38 | 6 | | 39 | 10 | | 40 | 12 | | 41 | 15 | | 42 | 17 | | 43 | 19 | | 44 | 17 | | 45 | 3 | | 46 | 5 | | 47 | 11 | | 48 | 20 | | 49 | 7 |
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| 40.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3185840707964602 | | totalSentences | 113 | | uniqueOpeners | 36 | |
| 44.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 75 | | matches | | 0 | "Instead, she stepped back, pulling" |
| | ratio | 0.013 | |
| 12.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 75 | | matches | | 0 | "She wasn’t expecting anyone." | | 1 | "She peered through the peephole," | | 2 | "He was a study in" | | 3 | "He was looking not at" | | 4 | "Her fingers hesitated over the" | | 5 | "She hadn’t seen him in" | | 6 | "She slid the bolt back." | | 7 | "She opened the door just" | | 8 | "He turned his head." | | 9 | "He’d known she’d be here." | | 10 | "His voice was the same," | | 11 | "It did things to her" | | 12 | "She wanted to slam the" | | 13 | "He entered, bringing with him" | | 14 | "He filled the cramped space" | | 15 | "He didn’t move further in," | | 16 | "He finally looked directly at" | | 17 | "He leaned his cane against" | | 18 | "she said, and meant it," | | 19 | "She could see the library," |
| | ratio | 0.52 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 75 | | matches | | 0 | "The first knock was soft." | | 1 | "Aurora ignored it, thinking it" | | 2 | "The second was firm, three" | | 3 | "Ptolemy, sprawled across a pile" | | 4 | "She wasn’t expecting anyone." | | 5 | "Eva was in Edinburgh until" | | 6 | "The curry house below was" | | 7 | "The silence after the knocks" | | 8 | "Aurora padded to the door," | | 9 | "She peered through the peephole," | | 10 | "Lucien Moreau stood on the" | | 11 | "He was a study in" | | 12 | "He was looking not at" | | 13 | "Her fingers hesitated over the" | | 14 | "The metal was cold." | | 15 | "She hadn’t seen him in" | | 16 | "There had been a bottle" | | 17 | "Things had been said." | | 18 | "Things she’d replayed in her" | | 19 | "She slid the bolt back." |
| | ratio | 0.947 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "The second was firm, three deliberate raps that echoed in the quiet of the flat." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, his voice dropping," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 46 | | tagDensity | 0.087 | | leniency | 0.174 | | rawRatio | 0.25 | | effectiveRatio | 0.043 | |