| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.268 | | leniency | 0.537 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1128 | | totalAiIsmAdverbs | 3 | | 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) | |
| 73.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1128 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "pulse" | | 1 | "lilt" | | 2 | "whisper" | | 3 | "could feel" | | 4 | "weight" | | 5 | "unsettled" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 66 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 66 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1139 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 857 | | uniqueNames | 7 | | maxNameDensity | 0.35 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Eva" | | discoveredNames | | Rory | 3 | | Eva | 3 | | Ptolemy | 3 | | Lucien | 3 | | Moreau | 2 | | London | 1 | | French | 1 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Lucien" | | 4 | "Moreau" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "as if approving of Eva's paranoia" |
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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 | 1139 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 19.64 | | std | 24.73 | | cv | 1.259 | | sampleLengths | | 0 | 55 | | 1 | 6 | | 2 | 83 | | 3 | 2 | | 4 | 18 | | 5 | 9 | | 6 | 4 | | 7 | 5 | | 8 | 58 | | 9 | 6 | | 10 | 34 | | 11 | 64 | | 12 | 4 | | 13 | 93 | | 14 | 3 | | 15 | 4 | | 16 | 4 | | 17 | 2 | | 18 | 68 | | 19 | 6 | | 20 | 9 | | 21 | 1 | | 22 | 34 | | 23 | 5 | | 24 | 7 | | 25 | 3 | | 26 | 52 | | 27 | 6 | | 28 | 8 | | 29 | 2 | | 30 | 4 | | 31 | 10 | | 32 | 43 | | 33 | 4 | | 34 | 18 | | 35 | 25 | | 36 | 3 | | 37 | 1 | | 38 | 6 | | 39 | 2 | | 40 | 7 | | 41 | 91 | | 42 | 6 | | 43 | 2 | | 44 | 4 | | 45 | 4 | | 46 | 45 | | 47 | 7 | | 48 | 11 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 66 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 141 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 96 | | ratio | 0.063 | | matches | | 0 | "His right eye — the black one, the one that always made her feel like she was being read page by page — stayed level with hers." | | 1 | "She wanted to tell him that she had spent six weeks teaching herself how to not think about the last night they'd stood this close — the rain on his collar, her palm flat against his chest, the moment he had stepped back from her instead of forward." | | 2 | "His gaze moved over the chaos of the flat — the teetering stacks of grimoires on the kitchen counter, the scrolls pinned across the window like makeshift curtains, the half-drunk mug of tea cooling on a pile of Eva's notes — and came to rest, finally, on her." | | 3 | "Her left wrist ached — that small crescent scar going pale in the cold — and she pressed her thumb to it without thinking, the way she always did when she wanted something to hold onto." | | 4 | "And there it was — that quiet, maddening honesty he only ever gave her in pieces, always when she was least prepared to catch it." | | 5 | "The narrow kitchen did the rest — she could smell the cold of the street on his coat, and under it, faintly, cedar and something smokier, that particular scent that had lived in her pillow for a week after the first and only time he had stayed." |
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| 98.03% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 781 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.04225352112676056 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.011523687580025609 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 11.86 | | std | 12.63 | | cv | 1.064 | | sampleLengths | | 0 | 23 | | 1 | 14 | | 2 | 18 | | 3 | 6 | | 4 | 39 | | 5 | 17 | | 6 | 27 | | 7 | 2 | | 8 | 11 | | 9 | 7 | | 10 | 4 | | 11 | 5 | | 12 | 4 | | 13 | 5 | | 14 | 15 | | 15 | 12 | | 16 | 6 | | 17 | 25 | | 18 | 6 | | 19 | 29 | | 20 | 5 | | 21 | 5 | | 22 | 48 | | 23 | 6 | | 24 | 5 | | 25 | 4 | | 26 | 23 | | 27 | 7 | | 28 | 15 | | 29 | 48 | | 30 | 3 | | 31 | 4 | | 32 | 4 | | 33 | 2 | | 34 | 14 | | 35 | 18 | | 36 | 36 | | 37 | 2 | | 38 | 4 | | 39 | 9 | | 40 | 1 | | 41 | 4 | | 42 | 6 | | 43 | 24 | | 44 | 5 | | 45 | 7 | | 46 | 3 | | 47 | 8 | | 48 | 8 | | 49 | 25 |
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| 39.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.3541666666666667 | | totalSentences | 96 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 57 | | matches | | 0 | "Of course the cat liked" | | 1 | "Of course he saw." |
| | ratio | 0.035 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 57 | | matches | | 0 | "She expected Eva, arms full" | | 1 | "She expected the postman with" | | 2 | "She did not expect Lucien" | | 3 | "He stood in the narrow" | | 4 | "His right eye — the" | | 5 | "She had the door half-closed" | | 6 | "His cane slid neatly into" | | 7 | "She didn't open the door" | | 8 | "His voice was soft in" | | 9 | "She wanted to say no." | | 10 | "She wanted to tell him" | | 11 | "She opened the door." | | 12 | "He came in the way" | | 13 | "He wiped his shoes on" | | 14 | "He noted the three deadbolts" | | 15 | "His gaze moved over the" | | 16 | "He made that faint sound" | | 17 | "Her left wrist ached —" | | 18 | "she said, because she had" | | 19 | "She filled the kettle." |
| | ratio | 0.702 | |
| 3.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 57 | | matches | | 0 | "The third deadbolt stuck, the" | | 1 | "She expected Eva, arms full" | | 2 | "She expected the postman with" | | 3 | "She did not expect Lucien" | | 4 | "He stood in the narrow" | | 5 | "The hall's single flickering bulb" | | 6 | "His right eye — the" | | 7 | "She had the door half-closed" | | 8 | "His cane slid neatly into" | | 9 | "She didn't open the door" | | 10 | "Ptolemy wound between her ankles," | | 11 | "Everything in London with a" | | 12 | "His voice was soft in" | | 13 | "She wanted to say no." | | 14 | "She wanted to tell him" | | 15 | "She opened the door." | | 16 | "He came in the way" | | 17 | "He wiped his shoes on" | | 18 | "He noted the three deadbolts" | | 19 | "His gaze moved over the" |
| | ratio | 0.912 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 3 | | matches | | 0 | "She expected the postman with another delivery of ancient-looking tomes that would send Ptolemy skittering under the sofa." | | 1 | "He noted the three deadbolts with a small nod, as if approving of Eva's paranoia." | | 2 | "The narrow kitchen did the rest — she could smell the cold of the street on his coat, and under it, faintly, cedar and something smokier, that particular scent …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | 0 | "Rory whispered (whisper)" |
| | dialogueSentences | 41 | | tagDensity | 0.195 | | leniency | 0.39 | | rawRatio | 0.125 | | effectiveRatio | 0.049 | |