| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 67 | | tagDensity | 0.313 | | leniency | 0.627 | | rawRatio | 0.048 | | effectiveRatio | 0.03 | |
| 96.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1429 | | totalAiIsmAdverbs | 1 | | 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) | |
| 82.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1429 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "dance" | | 1 | "weight" | | 2 | "stomach" | | 3 | "pulse" | | 4 | "charm" |
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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 | 49 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 49 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 64 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1434 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 758 | | uniqueNames | 11 | | maxNameDensity | 0.66 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 5 | | Golden | 1 | | Empress | 1 | | Moreau | 2 | | Ptolemy | 2 | | Lucien | 5 | | Rain | 1 | | Eva | 4 | | Bank | 1 | | England | 1 | | Bengali | 1 |
| | persons | | 0 | "Rory" | | 1 | "Moreau" | | 2 | "Ptolemy" | | 3 | "Lucien" | | 4 | "Rain" | | 5 | "Eva" |
| | places | | 0 | "Golden" | | 1 | "England" | | 2 | "Bengali" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | 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 | 1434 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 23.13 | | std | 26.28 | | cv | 1.136 | | sampleLengths | | 0 | 61 | | 1 | 12 | | 2 | 58 | | 3 | 6 | | 4 | 3 | | 5 | 5 | | 6 | 13 | | 7 | 13 | | 8 | 2 | | 9 | 12 | | 10 | 50 | | 11 | 4 | | 12 | 2 | | 13 | 2 | | 14 | 26 | | 15 | 10 | | 16 | 12 | | 17 | 46 | | 18 | 10 | | 19 | 43 | | 20 | 1 | | 21 | 28 | | 22 | 4 | | 23 | 50 | | 24 | 36 | | 25 | 95 | | 26 | 3 | | 27 | 9 | | 28 | 16 | | 29 | 2 | | 30 | 73 | | 31 | 1 | | 32 | 3 | | 33 | 79 | | 34 | 5 | | 35 | 5 | | 36 | 35 | | 37 | 4 | | 38 | 2 | | 39 | 71 | | 40 | 6 | | 41 | 10 | | 42 | 1 | | 43 | 6 | | 44 | 10 | | 45 | 74 | | 46 | 7 | | 47 | 1 | | 48 | 7 | | 49 | 1 |
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| 98.10% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 49 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 129 | | matches | | 0 | "was frying" | | 1 | "was sitting" | | 2 | "was catching" | | 3 | "was going" | | 4 | "was letting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 1 | | flaggedSentences | 5 | | totalSentences | 95 | | ratio | 0.053 | | matches | | 0 | "Three of them, top to bottom, and Rory worked them slow on purpose, because whoever stood on the other side had knocked in a rhythm she recognised and hated — two short, one long, the same knock he used to give the service door at the Golden Empress when he wanted noodles at two in the morning." | | 1 | "\"I'm making tea.\" She went to the kitchen corner — two feet of counter, a kettle, a stack of Eva's mugs with the glaze crazed." | | 2 | "That was the trouble with him; he never did the thing you set up for him." | | 3 | "When she turned round with two mugs he was sitting forward with his elbows on his knees, and he had that look — the one that had been on his face in the corridor under the Bank of England when he'd told her to run and then hadn't followed." | | 4 | "Somewhere below, the curry house door banged and a man laughed at something in Bengali, and Lucien Moreau — who had once talked a customs officer out of opening a case containing a live thing with too many joints — sat on Eva's sagging sofa and said nothing for the length of eight heartbeats." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 754 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.03580901856763926 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007957559681697613 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 15.09 | | std | 14.96 | | cv | 0.991 | | sampleLengths | | 0 | 4 | | 1 | 57 | | 2 | 12 | | 3 | 26 | | 4 | 32 | | 5 | 6 | | 6 | 3 | | 7 | 5 | | 8 | 11 | | 9 | 2 | | 10 | 13 | | 11 | 2 | | 12 | 6 | | 13 | 6 | | 14 | 35 | | 15 | 6 | | 16 | 6 | | 17 | 3 | | 18 | 4 | | 19 | 2 | | 20 | 2 | | 21 | 21 | | 22 | 5 | | 23 | 10 | | 24 | 12 | | 25 | 37 | | 26 | 9 | | 27 | 10 | | 28 | 39 | | 29 | 4 | | 30 | 1 | | 31 | 28 | | 32 | 4 | | 33 | 26 | | 34 | 24 | | 35 | 25 | | 36 | 11 | | 37 | 3 | | 38 | 16 | | 39 | 27 | | 40 | 49 | | 41 | 3 | | 42 | 9 | | 43 | 16 | | 44 | 2 | | 45 | 7 | | 46 | 20 | | 47 | 46 | | 48 | 1 | | 49 | 3 |
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| 64.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.42105263157894735 | | totalSentences | 95 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 42 | | matches | | 0 | "Then she stepped back and" | | 1 | "Somewhere below, the curry house" |
| | ratio | 0.048 | |
| 0.95% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 42 | | matches | | 0 | "She opened the door six" | | 1 | "She didn't move" | | 2 | "His mouth tipped" | | 3 | "She stood there long enough" | | 4 | "He came in, ducked a" | | 5 | "She went to the kitchen" | | 6 | "He didn't talk." | | 7 | "She heard the coat come" | | 8 | "She held out the mug" | | 9 | "He took it and their" | | 10 | "He set the mug down" | | 11 | "he said quietly" | | 12 | "She counted everything too, apparently." | | 13 | "It was catching." | | 14 | "Her stomach dropped through the" | | 15 | "He picked the mug up" | | 16 | "Her voice came out rougher" | | 17 | "He set the mug down" | | 18 | "He reached over the cat," | | 19 | "His thumb found the small" |
| | ratio | 0.548 | |
| 7.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 42 | | matches | | 0 | "The deadbolts took time." | | 1 | "She opened the door six" | | 2 | "Lucien Moreau filled the gap" | | 3 | "Someone downstairs was frying cumin" | | 4 | "She didn't move" | | 5 | "His mouth tipped" | | 6 | "Ptolemy shoved his skull against" | | 7 | "Lucien looked down at the" | | 8 | "The cat looked up at" | | 9 | "Traitor, Rory thought." | | 10 | "Rain slid off the end" | | 11 | "She stood there long enough" | | 12 | "He came in, ducked a" | | 13 | "Lucien peeled off his gloves," | | 14 | "She went to the kitchen" | | 15 | "He didn't talk." | | 16 | "That was the trouble with" | | 17 | "She heard the coat come" | | 18 | "She held out the mug" | | 19 | "He took it and their" |
| | ratio | 0.905 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 8.93% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 3 | | matches | | 0 | "Someone downstairs was frying cumin and the whole stairwell smelled of it and he stood in the middle of that smell like a man who'd wandered out of a different …" | | 1 | "Ptolemy shoved his skull against Rory's ankle, purring like a badly tuned engine, and then squeezed through the gap and wound a figure of eight around Lucien's …" | | 2 | "Somewhere below, the curry house door banged and a man laughed at something in Bengali, and Lucien Moreau — who had once talked a customs officer out of opening…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 67 | | tagDensity | 0.119 | | leniency | 0.239 | | rawRatio | 0 | | effectiveRatio | 0 | |