| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1502 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "precisely" | | 1 | "really" | | 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) | |
| 66.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1502 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "symphony" | | 1 | "flickered" | | 2 | "traced" | | 3 | "clenching" | | 4 | "electric" | | 5 | "pulse" | | 6 | "could feel" | | 7 | "echo" | | 8 | "pulsed" |
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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 | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 71 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "happened to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 74 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1502 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.10% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 867 | | uniqueNames | 11 | | maxNameDensity | 1.04 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 6 | | Rory | 9 | | Bestiary | 2 | | Western | 1 | | Atelier | 1 | | Lucien | 6 | | Malphora | 1 | | Cardiff | 1 | | Evan | 2 | | Aurora | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Eva" | | 1 | "Rory" | | 2 | "Lucien" | | 3 | "Evan" | | 4 | "Aurora" | | 5 | "Ptolemy" |
| | places | | | globalScore | 0.981 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 3 | | matches | | 0 | "not quite an invitation, not quite a refusal" | | 1 | "not quite a refusal" | | 2 | "looked like a man who'd wandered into a p" | | 3 | "quite blood" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.666 | | wordCount | 1502 | | matches | | 0 | "Not literally, but the sensation registered the same, a sudden stillness in her" |
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| 80.46% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 116 | | matches | | 0 | "do that thing" | | 1 | "holding that glass" | | 2 | "chose that moment" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 64 | | mean | 23.47 | | std | 25.74 | | cv | 1.097 | | sampleLengths | | 0 | 43 | | 1 | 5 | | 2 | 28 | | 3 | 5 | | 4 | 51 | | 5 | 3 | | 6 | 1 | | 7 | 2 | | 8 | 84 | | 9 | 23 | | 10 | 3 | | 11 | 12 | | 12 | 7 | | 13 | 45 | | 14 | 5 | | 15 | 66 | | 16 | 3 | | 17 | 16 | | 18 | 7 | | 19 | 52 | | 20 | 29 | | 21 | 9 | | 22 | 30 | | 23 | 4 | | 24 | 40 | | 25 | 4 | | 26 | 6 | | 27 | 38 | | 28 | 12 | | 29 | 70 | | 30 | 17 | | 31 | 10 | | 32 | 19 | | 33 | 1 | | 34 | 14 | | 35 | 1 | | 36 | 44 | | 37 | 46 | | 38 | 52 | | 39 | 4 | | 40 | 4 | | 41 | 5 | | 42 | 1 | | 43 | 115 | | 44 | 4 | | 45 | 1 | | 46 | 32 | | 47 | 50 | | 48 | 5 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 71 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 144 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 116 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 845 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.027218934911242602 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009467455621301775 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 12.95 | | std | 12.35 | | cv | 0.954 | | sampleLengths | | 0 | 5 | | 1 | 38 | | 2 | 5 | | 3 | 7 | | 4 | 21 | | 5 | 5 | | 6 | 15 | | 7 | 14 | | 8 | 12 | | 9 | 8 | | 10 | 2 | | 11 | 3 | | 12 | 1 | | 13 | 2 | | 14 | 6 | | 15 | 2 | | 16 | 14 | | 17 | 30 | | 18 | 4 | | 19 | 28 | | 20 | 17 | | 21 | 2 | | 22 | 4 | | 23 | 3 | | 24 | 12 | | 25 | 7 | | 26 | 21 | | 27 | 4 | | 28 | 20 | | 29 | 5 | | 30 | 21 | | 31 | 6 | | 32 | 7 | | 33 | 32 | | 34 | 3 | | 35 | 16 | | 36 | 7 | | 37 | 35 | | 38 | 17 | | 39 | 5 | | 40 | 24 | | 41 | 9 | | 42 | 30 | | 43 | 4 | | 44 | 14 | | 45 | 3 | | 46 | 23 | | 47 | 4 | | 48 | 6 | | 49 | 38 |
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| 76.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4827586206896552 | | totalSentences | 116 | | uniqueOpeners | 56 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 64 | | matches | | 0 | "Then he unbuttoned the trouser" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 64 | | matches | | 0 | "He hadn't needed the cane" | | 1 | "He surveyed the chaos with" | | 2 | "She closed the Bestiary." | | 3 | "Her thumb found the crescent" | | 4 | "He lowered himself onto the" | | 5 | "His left leg extended at" | | 6 | "She crossed her arms" | | 7 | "She took a step toward" | | 8 | "He didn't deny it." | | 9 | "She'd taken the name Malphora" | | 10 | "It was darker, with an" | | 11 | "She crouched beside his chair," | | 12 | "She looked up at him" | | 13 | "He was in pain right" | | 14 | "She stumbled, caught Lucien's knee," | | 15 | "His palm was warm through" | | 16 | "His thumb pressed against the" | | 17 | "His thumb was still on" |
| | ratio | 0.281 | |
| 38.13% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 64 | | matches | | 0 | "The deadbolts clicked in sequence." | | 1 | "Lucien stood in the hallway." | | 2 | "The noodles went cold in" | | 3 | "Rory stared at him" | | 4 | "The charcoal suit was new," | | 5 | "The ivory-handled cane hung from" | | 6 | "He hadn't needed the cane" | | 7 | "Ptolemy wound between Lucien's ankles," | | 8 | "Rory stepped back from the" | | 9 | "Lucien interpreted it as the" | | 10 | "The flat swallowed him." | | 11 | "He surveyed the chaos with" | | 12 | "Rory set the noodles on" | | 13 | "She closed the Bestiary." | | 14 | "Her thumb found the crescent" | | 15 | "He lowered himself onto the" | | 16 | "The cane settled across his" | | 17 | "His left leg extended at" | | 18 | "She crossed her arms" | | 19 | "Something shifted behind his expression." |
| | ratio | 0.844 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 68.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 3 | | matches | | 0 | "His left leg extended at an angle that suggested the bullet had struck the thigh or the knee, and the suit trousers, despite excellent tailoring, couldn't entir…" | | 1 | "She'd taken the name Malphora two years ago, in another life, in Cardiff, when Evan had still been Evan and the supernatural had been something that happened to…" | | 2 | "Then he unbuttoned the trouser cuff and rolled the fabric up, revealing a compression bandage stained with something that wasn't quite blood." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "She crouched, her fingers hovering over the bandage without touching it" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0 | | effectiveRatio | 0 | |