| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva stepped back [back]" |
| | dialogueSentences | 56 | | tagDensity | 0.232 | | leniency | 0.464 | | rawRatio | 0.077 | | effectiveRatio | 0.036 | |
| 88.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1309 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "really" | | 2 | "slightly" |
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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) | |
| 73.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1309 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "silence" | | 1 | "coded" | | 2 | "familiar" | | 3 | "trembled" | | 4 | "tracing" |
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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 | 1 | | narrationSentences | 97 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 137 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1309 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 65 | | wordCount | 955 | | uniqueNames | 12 | | maxNameDensity | 3.04 | | worstName | "Eva" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Aurora | 21 | | Eva | 29 | | Practised | 1 | | Brick | 1 | | Lane | 1 | | Bengali | 1 | | Tube | 1 | | Post-it | 1 | | Evan | 2 | | Tuesday | 1 | | November | 1 | | Ptolemy | 5 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Post-it" | | 3 | "Evan" | | 4 | "Ptolemy" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Bengali" | | 3 | "November" |
| | globalScore | 0 | | windowScore | 0.167 | |
| 34.62% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 3 | | matches | | 0 | "Not quite an invitation, but not a refusal either" | | 1 | "looked like, and she had finally understo" | | 2 | "tasted like tea and salt and three years" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.764 | | wordCount | 1309 | | matches | | 0 | "Not quite an invitation, but not a refusal either" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 137 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 16.16 | | std | 15.29 | | cv | 0.946 | | sampleLengths | | 0 | 40 | | 1 | 4 | | 2 | 62 | | 3 | 24 | | 4 | 2 | | 5 | 47 | | 6 | 4 | | 7 | 21 | | 8 | 4 | | 9 | 58 | | 10 | 6 | | 11 | 34 | | 12 | 11 | | 13 | 14 | | 14 | 2 | | 15 | 4 | | 16 | 5 | | 17 | 16 | | 18 | 8 | | 19 | 32 | | 20 | 8 | | 21 | 4 | | 22 | 6 | | 23 | 49 | | 24 | 5 | | 25 | 11 | | 26 | 27 | | 27 | 7 | | 28 | 29 | | 29 | 15 | | 30 | 14 | | 31 | 6 | | 32 | 1 | | 33 | 1 | | 34 | 2 | | 35 | 30 | | 36 | 58 | | 37 | 24 | | 38 | 22 | | 39 | 1 | | 40 | 17 | | 41 | 41 | | 42 | 5 | | 43 | 9 | | 44 | 27 | | 45 | 41 | | 46 | 2 | | 47 | 8 | | 48 | 23 | | 49 | 23 |
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| 98.03% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 97 | | matches | | 0 | "been edited" | | 1 | "was wrecked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 162 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 137 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 961 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 38 | | adverbRatio | 0.03954214360041623 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.013527575442247659 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 137 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 137 | | mean | 9.55 | | std | 7.01 | | cv | 0.734 | | sampleLengths | | 0 | 7 | | 1 | 2 | | 2 | 31 | | 3 | 4 | | 4 | 18 | | 5 | 11 | | 6 | 15 | | 7 | 18 | | 8 | 12 | | 9 | 1 | | 10 | 11 | | 11 | 2 | | 12 | 4 | | 13 | 23 | | 14 | 20 | | 15 | 4 | | 16 | 6 | | 17 | 9 | | 18 | 6 | | 19 | 4 | | 20 | 11 | | 21 | 18 | | 22 | 29 | | 23 | 6 | | 24 | 8 | | 25 | 9 | | 26 | 8 | | 27 | 9 | | 28 | 11 | | 29 | 10 | | 30 | 4 | | 31 | 2 | | 32 | 4 | | 33 | 5 | | 34 | 6 | | 35 | 4 | | 36 | 6 | | 37 | 8 | | 38 | 20 | | 39 | 12 | | 40 | 8 | | 41 | 4 | | 42 | 6 | | 43 | 3 | | 44 | 13 | | 45 | 33 | | 46 | 5 | | 47 | 11 | | 48 | 19 | | 49 | 8 |
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| 47.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.34306569343065696 | | totalSentences | 137 | | uniqueOpeners | 47 | |
| 76.63% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 87 | | matches | | 0 | "Just for a moment." | | 1 | "Then she set it to" |
| | ratio | 0.023 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 87 | | matches | | 0 | "He was thinner than Aurora" | | 1 | "He stared up at her" | | 2 | "They had all evaporated." | | 3 | "It meant something to two," | | 4 | "She had told herself it" | | 5 | "She had told herself Eva" | | 6 | "She had told herself a" | | 7 | "Her eyes were bright, and" | | 8 | "Her face was wrecked, mascara" | | 9 | "She switched the phone off." |
| | ratio | 0.115 | |
| 11.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 87 | | matches | | 0 | "The deadbolts clicked back, one" | | 1 | "A small ritual that had" | | 2 | "The door swung open." | | 3 | "Eva stood in the narrow" | | 4 | "Ptolemy wound between her ankles," | | 5 | "He was thinner than Aurora" | | 6 | "He stared up at her" | | 7 | "Eva's voice came out flat" | | 8 | "The way she delivered information" | | 9 | "Silence stretched between them." | | 10 | "The sounds of Brick Lane" | | 11 | "Aurora gripped the strap of" | | 12 | "They had all evaporated." | | 13 | "Eva stepped back" | | 14 | "Aurora crossed the threshold." | | 15 | "The flat hit her like" | | 16 | "Stacks of books lined every" | | 17 | "Scrolls competed for space with" | | 18 | "It meant something to two," | | 19 | "Hardback, second-hand, filled with texts" |
| | ratio | 0.897 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 4 | | matches | | 0 | "A small ritual that had not changed in the three years since Aurora last stood on this worn doormat, smelling curry from the restaurant below and something olde…" | | 1 | "Stacks of books lined every wall, balanced in precarious towers that obeyed laws of physics only Eva understood." | | 2 | "Scrolls competed for space with takeaway containers, and a patchwork of Post-it notes covered the kitchen counter in a colour-coded system that meant something …" | | 3 | "Eva's hand flew to her mouth, as if she could catch the words and shove them back in." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva said, not turning around" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 56 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |