| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 70 | | tagDensity | 0.229 | | leniency | 0.457 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.77% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1084 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | 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) | |
| 81.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1084 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "pulse" | | 1 | "flicker" | | 2 | "weight" | | 3 | "silence" |
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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) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 69 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1089 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 694 | | uniqueNames | 8 | | maxNameDensity | 0.58 | | worstName | "Ptolemy" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Mrs | 1 | | Ptolemy | 4 | | Moreau | 1 | | Welsh | 1 | | English | 1 | | Amused | 1 | | Lucien | 4 | | Eva | 2 |
| | persons | | 0 | "Mrs" | | 1 | "Ptolemy" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 69.35% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a woman who'd already made up" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.918 | | wordCount | 1089 | | matches | | 0 | "not pain exactly, but the memory of it" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 82 | | mean | 13.28 | | std | 16.04 | | cv | 1.208 | | sampleLengths | | 0 | 46 | | 1 | 11 | | 2 | 1 | | 3 | 4 | | 4 | 40 | | 5 | 26 | | 6 | 6 | | 7 | 1 | | 8 | 31 | | 9 | 4 | | 10 | 40 | | 11 | 5 | | 12 | 17 | | 13 | 14 | | 14 | 1 | | 15 | 1 | | 16 | 38 | | 17 | 5 | | 18 | 43 | | 19 | 5 | | 20 | 9 | | 21 | 4 | | 22 | 2 | | 23 | 55 | | 24 | 2 | | 25 | 4 | | 26 | 1 | | 27 | 1 | | 28 | 9 | | 29 | 8 | | 30 | 70 | | 31 | 11 | | 32 | 1 | | 33 | 3 | | 34 | 1 | | 35 | 4 | | 36 | 1 | | 37 | 2 | | 38 | 54 | | 39 | 6 | | 40 | 11 | | 41 | 7 | | 42 | 2 | | 43 | 42 | | 44 | 7 | | 45 | 3 | | 46 | 3 | | 47 | 11 | | 48 | 3 | | 49 | 14 |
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| 95.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 69 | | matches | | 0 | "been poured" | | 1 | "was shaped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 127 | | matches | | |
| 73.73% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 124 | | ratio | 0.024 | | matches | | 0 | "He rose, slow, and she caught a flicker of something in his face when his weight went through the cane — not pain exactly, but the memory of it." | | 1 | "The floorboards gave him away — Eva's flat had no secrets from its own floor — and she heard him stop when she flinched." | | 2 | "She looked at him — the platinum hair slicked back, the cane, the slight favour he was still giving his left side — and at the door she hadn't locked, and at her own hands, which had begun to shake somewhere around the word *seventh*." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 471 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.03184713375796178 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.008492569002123142 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 8.78 | | std | 9.68 | | cv | 1.102 | | sampleLengths | | 0 | 9 | | 1 | 23 | | 2 | 14 | | 3 | 11 | | 4 | 1 | | 5 | 4 | | 6 | 2 | | 7 | 19 | | 8 | 19 | | 9 | 11 | | 10 | 1 | | 11 | 3 | | 12 | 11 | | 13 | 6 | | 14 | 1 | | 15 | 7 | | 16 | 11 | | 17 | 13 | | 18 | 4 | | 19 | 3 | | 20 | 22 | | 21 | 7 | | 22 | 8 | | 23 | 5 | | 24 | 17 | | 25 | 12 | | 26 | 2 | | 27 | 1 | | 28 | 1 | | 29 | 38 | | 30 | 5 | | 31 | 14 | | 32 | 2 | | 33 | 24 | | 34 | 3 | | 35 | 5 | | 36 | 9 | | 37 | 4 | | 38 | 2 | | 39 | 29 | | 40 | 26 | | 41 | 2 | | 42 | 4 | | 43 | 1 | | 44 | 1 | | 45 | 9 | | 46 | 8 | | 47 | 3 | | 48 | 35 | | 49 | 3 |
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| 54.57% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3709677419354839 | | totalSentences | 124 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 52 | | matches | | 0 | "Then she stood with her" | | 1 | "Of course amused." | | 2 | "Only him, and only when" |
| | ratio | 0.058 | |
| 12.31% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 52 | | matches | | 0 | "She shut the door." | | 1 | "She took her time on" | | 2 | "he called from the other" | | 3 | "She undid the locks." | | 4 | "He hadn't moved." | | 5 | "He inclined his head at" | | 6 | "He rose, slow, and she" | | 7 | "She stepped back." | | 8 | "He took it as invitation," | | 9 | "He didn't sit." | | 10 | "He knew better than to" | | 11 | "He set the cane against" | | 12 | "She closed the door." | | 13 | "She wanted the option." | | 14 | "She folded her arms" | | 15 | "She uncrossed her arms." | | 16 | "He looked at her properly" | | 17 | "His voice had gone quiet" | | 18 | "She looked at the ceiling" | | 19 | "He took a step." |
| | ratio | 0.519 | |
| 36.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 52 | | matches | | 0 | "The third deadbolt stuck, the" | | 1 | "Rory jiggled the chain, swore" | | 2 | "Patel from below come to" | | 3 | "Lucien Moreau leaned against the" | | 4 | "She shut the door." | | 5 | "She took her time on" | | 6 | "he called from the other" | | 7 | "Nobody said her full name" | | 8 | "She undid the locks." | | 9 | "He hadn't moved." | | 10 | "The amber eye caught the" | | 11 | "The black one didn't reflect" | | 12 | "He inclined his head at" | | 13 | "Ptolemy wound between her ankles," | | 14 | "Lucien crouched with the kind" | | 15 | "Ptolemy head-butted them." | | 16 | "He rose, slow, and she" | | 17 | "The last time she'd seen" | | 18 | "She stepped back." | | 19 | "He took it as invitation," |
| | ratio | 0.846 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 3 | | matches | | 0 | "Ptolemy jumped onto the back of the sofa and began washing a paw with tremendous dignity, as if the two of them were very much beneath his notice." | | 1 | "She looked at him — the platinum hair slicked back, the cane, the slight favour he was still giving his left side — and at the door she hadn't locked, and at he…" | | 2 | "And she took a very long time filling the kettle, because her reflection in the dark window above the sink looked like a woman who'd already made up her mind, a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 70 | | tagDensity | 0.114 | | leniency | 0.229 | | rawRatio | 0 | | effectiveRatio | 0 | |