| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 63 | | tagDensity | 0.317 | | leniency | 0.635 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1301 | | totalAiIsmAdverbs | 4 | | 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) | |
| 84.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1301 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "weight" | | 1 | "stomach" | | 2 | "pulse" | | 3 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1305 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 24 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 903 | | uniqueNames | 7 | | maxNameDensity | 0.55 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 5 | | Lucien | 5 | | Evan | 1 | | Latin | 1 | | Whitechapel | 1 | | Rain | 2 | | Bengali | 1 |
| | persons | | 0 | "Rory" | | 1 | "Lucien" | | 2 | "Evan" | | 3 | "Rain" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1305 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 104 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 19.48 | | std | 22.13 | | cv | 1.136 | | sampleLengths | | 0 | 21 | | 1 | 70 | | 2 | 3 | | 3 | 5 | | 4 | 57 | | 5 | 14 | | 6 | 10 | | 7 | 38 | | 8 | 1 | | 9 | 7 | | 10 | 58 | | 11 | 13 | | 12 | 3 | | 13 | 8 | | 14 | 40 | | 15 | 32 | | 16 | 6 | | 17 | 68 | | 18 | 11 | | 19 | 4 | | 20 | 38 | | 21 | 3 | | 22 | 1 | | 23 | 4 | | 24 | 98 | | 25 | 13 | | 26 | 1 | | 27 | 14 | | 28 | 45 | | 29 | 43 | | 30 | 3 | | 31 | 4 | | 32 | 6 | | 33 | 50 | | 34 | 88 | | 35 | 2 | | 36 | 44 | | 37 | 8 | | 38 | 3 | | 39 | 4 | | 40 | 24 | | 41 | 2 | | 42 | 1 | | 43 | 19 | | 44 | 27 | | 45 | 8 | | 46 | 6 | | 47 | 22 | | 48 | 1 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 147 | | matches | (empty) | |
| 5.49% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 104 | | ratio | 0.048 | | matches | | 0 | "His mouth moved — not a smile, the thing that came before one, the crease at the corner." | | 1 | "That was the one thing she'd got good at, over the years, with Evan and after — the not-moving of the face." | | 2 | "Eva's flat allowed one clear path — door to kitchenette to the sofa — and everything either side of it was books, some of them open and face-down and spine-broken in ways that would have made her mother weep." | | 3 | "\"—the hide for a binding, yes, she's told me.\" He sat." | | 4 | "It put her lower than him, closer, her shoulder between his knees, and the heat came off him the way it always did — a few degrees hotter than a person should be, the demon half running warm." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 573 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.02617801047120419 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0017452006980802793 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 12.55 | | std | 11.57 | | cv | 0.922 | | sampleLengths | | 0 | 21 | | 1 | 10 | | 2 | 32 | | 3 | 2 | | 4 | 26 | | 5 | 3 | | 6 | 5 | | 7 | 17 | | 8 | 27 | | 9 | 13 | | 10 | 14 | | 11 | 10 | | 12 | 18 | | 13 | 16 | | 14 | 4 | | 15 | 1 | | 16 | 5 | | 17 | 2 | | 18 | 3 | | 19 | 26 | | 20 | 29 | | 21 | 7 | | 22 | 6 | | 23 | 3 | | 24 | 8 | | 25 | 15 | | 26 | 25 | | 27 | 5 | | 28 | 5 | | 29 | 22 | | 30 | 6 | | 31 | 33 | | 32 | 35 | | 33 | 4 | | 34 | 7 | | 35 | 4 | | 36 | 37 | | 37 | 1 | | 38 | 3 | | 39 | 1 | | 40 | 4 | | 41 | 38 | | 42 | 39 | | 43 | 21 | | 44 | 13 | | 45 | 1 | | 46 | 14 | | 47 | 11 | | 48 | 34 | | 49 | 35 |
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| 66.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4423076923076923 | | totalSentences | 104 | | uniqueOpeners | 46 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 52 | | matches | | 0 | "Then she stood there with" |
| | ratio | 0.019 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 52 | | matches | | 0 | "He held the cane loose" | | 1 | "She shifted her weight so" | | 2 | "His mouth moved — not" | | 3 | "He tipped his head" | | 4 | "She hated that." | | 5 | "She hated the ease of" | | 6 | "Her stomach dropped a floor." | | 7 | "She didn't move her face." | | 8 | "He said it like a" | | 9 | "He glanced down at his" | | 10 | "She unhooked the chain." | | 11 | "He came in and she" | | 12 | "He set the cane against" | | 13 | "She got the first aid" | | 14 | "He undid the button himself," | | 15 | "She could see the cost." | | 16 | "It put her lower than" | | 17 | "She'd known that heat in" | | 18 | "She poured antiseptic on it" | | 19 | "He inhaled through his teeth." |
| | ratio | 0.558 | |
| 8.08% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 52 | | matches | | 0 | "Lucien stood on the landing" | | 1 | "The platinum had gone dark" | | 2 | "He held the cane loose" | | 3 | "She shifted her weight so" | | 4 | "His mouth moved — not" | | 5 | "Rain slid down the side" | | 6 | "He tipped his head" | | 7 | "She hated that." | | 8 | "She hated the ease of" | | 9 | "Ptolemy came round her ankles," | | 10 | "Lucien lifted the cane an" | | 11 | "Her stomach dropped a floor." | | 12 | "She didn't move her face." | | 13 | "That was the one thing" | | 14 | "He said it like a" | | 15 | "Rory looked at him." | | 16 | "The chain was cold against" | | 17 | "He glanced down at his" | | 18 | "She unhooked the chain." | | 19 | "He came in and she" |
| | ratio | 0.904 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "He glanced down at his own cuff, where the white shirt had gone rust-coloured from the wrist to the base of the thumb, and his eyebrows went up as if he'd found…" | | 1 | "Eva's flat allowed one clear path — door to kitchenette to the sofa — and everything either side of it was books, some of them open and face-down and spine-brok…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 2 | | fancyTags | | 0 | "She pressed (press)" | | 1 | "she agreed (agree)" |
| | dialogueSentences | 63 | | tagDensity | 0.206 | | leniency | 0.413 | | rawRatio | 0.154 | | effectiveRatio | 0.063 | |