| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.51% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1823 | | totalAiIsmAdverbs | 2 | | 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) | |
| 80.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1823 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "grave" | | 1 | "charged" | | 2 | "whisper" | | 3 | "perfect" | | 4 | "tenderness" | | 5 | "eyebrow" | | 6 | "stomach" |
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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 | 95 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 95 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 60 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1823 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 1 | | matches | | 0 | "Behind her, Ptolemy hissed." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1500 | | uniqueNames | 25 | | maxNameDensity | 0.53 | | worstName | "Lucien" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 7 | | Ptolemy | 5 | | Oxford | 1 | | Thursday | 1 | | Brick | 1 | | Lane | 1 | | Eva | 5 | | Moreau | 2 | | Silas | 3 | | One | 1 | | Cardiff | 3 | | Pre-Law | 1 | | Brendan | 1 | | Carter | 1 | | Evan | 2 | | Golden | 2 | | Empress | 2 | | Bengali | 1 | | Italian | 1 | | Mandarin | 1 | | Yu-Fei | 1 | | French | 2 | | Lucien | 8 | | English | 1 | | Three | 4 |
| | persons | | 0 | "Rory" | | 1 | "Ptolemy" | | 2 | "Thursday" | | 3 | "Eva" | | 4 | "Moreau" | | 5 | "Silas" | | 6 | "One" | | 7 | "Brendan" | | 8 | "Carter" | | 9 | "Evan" | | 10 | "Italian" | | 11 | "Lucien" |
| | places | | 0 | "Oxford" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Cardiff" | | 4 | "Golden" | | 5 | "Bengali" | | 6 | "French" | | 7 | "English" | | 8 | "Three" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like bitters and lime" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1823 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 112 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 45.58 | | std | 33.61 | | cv | 0.737 | | sampleLengths | | 0 | 62 | | 1 | 65 | | 2 | 18 | | 3 | 72 | | 4 | 7 | | 5 | 66 | | 6 | 4 | | 7 | 94 | | 8 | 8 | | 9 | 38 | | 10 | 2 | | 11 | 88 | | 12 | 54 | | 13 | 44 | | 14 | 83 | | 15 | 33 | | 16 | 4 | | 17 | 5 | | 18 | 89 | | 19 | 8 | | 20 | 68 | | 21 | 16 | | 22 | 22 | | 23 | 64 | | 24 | 39 | | 25 | 5 | | 26 | 2 | | 27 | 93 | | 28 | 52 | | 29 | 30 | | 30 | 98 | | 31 | 9 | | 32 | 50 | | 33 | 17 | | 34 | 111 | | 35 | 89 | | 36 | 74 | | 37 | 41 | | 38 | 9 | | 39 | 90 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 42.52% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 254 | | matches | | 0 | "wasn't expecting" | | 1 | "was looking" | | 2 | "wasn't listening" | | 3 | "was sticking" | | 4 | "was dripping" | | 5 | "was asking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 112 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1508 | | adjectiveStacks | 1 | | stackExamples | | 0 | "white against white shirt," |
| | adverbCount | 33 | | adverbRatio | 0.021883289124668436 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005968169761273209 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 16.28 | | std | 13.39 | | cv | 0.823 | | sampleLengths | | 0 | 30 | | 1 | 32 | | 2 | 4 | | 3 | 41 | | 4 | 10 | | 5 | 10 | | 6 | 18 | | 7 | 34 | | 8 | 12 | | 9 | 18 | | 10 | 8 | | 11 | 6 | | 12 | 1 | | 13 | 23 | | 14 | 4 | | 15 | 16 | | 16 | 12 | | 17 | 11 | | 18 | 4 | | 19 | 2 | | 20 | 57 | | 21 | 35 | | 22 | 3 | | 23 | 5 | | 24 | 11 | | 25 | 27 | | 26 | 2 | | 27 | 22 | | 28 | 52 | | 29 | 14 | | 30 | 9 | | 31 | 10 | | 32 | 25 | | 33 | 7 | | 34 | 3 | | 35 | 24 | | 36 | 20 | | 37 | 11 | | 38 | 19 | | 39 | 9 | | 40 | 8 | | 41 | 24 | | 42 | 12 | | 43 | 28 | | 44 | 5 | | 45 | 4 | | 46 | 5 | | 47 | 2 | | 48 | 22 | | 49 | 43 |
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| 60.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.41964285714285715 | | totalSentences | 112 | | uniqueOpeners | 47 | |
| 39.22% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 85 | | matches | | 0 | "Somewhere downstairs a pan clattered" |
| | ratio | 0.012 | |
| 36.47% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 85 | | matches | | 0 | "She wasn't expecting anyone." | | 1 | "She had kicked a path" | | 2 | "She had told exactly one" | | 3 | "He looked wrong without the" | | 4 | "His mouth tipped, but it" | | 5 | "She didn't move." | | 6 | "His gaze dropped to her" | | 7 | "His eyes lingered half a" | | 8 | "His suit was dark with" | | 9 | "She hated that her first" | | 10 | "She stepped back because if" | | 11 | "He ducked under the lintel" | | 12 | "She had seen him smooth-talking" | | 13 | "He used language like his" | | 14 | "She wiped it on her" | | 15 | "Her heart banged against her" | | 16 | "She thought of her scooter" | | 17 | "She thought of Evan's voice" | | 18 | "She crossed her arms to" | | 19 | "Her voice came out steady," |
| | ratio | 0.459 | |
| 65.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 85 | | matches | | 0 | "The third deadbolt stuck the" | | 1 | "She wasn't expecting anyone." | | 2 | "Eva was in Oxford until" | | 3 | "She had kicked a path" | | 4 | "She had told exactly one" | | 5 | "The door swung inward and" | | 6 | "Lucien Moreau stood on the" | | 7 | "He looked wrong without the" | | 8 | "Rory's fingers tightened on the" | | 9 | "His mouth tipped, but it" | | 10 | "She didn't move." | | 11 | "His gaze dropped to her" | | 12 | "A childhood accident on a" | | 13 | "His eyes lingered half a" | | 14 | "Rain ticked on the skylight" | | 15 | "His suit was dark with" | | 16 | "Lucien Moreau did not scuff" | | 17 | "She hated that her first" | | 18 | "She stepped back because if" | | 19 | "He ducked under the lintel" |
| | ratio | 0.788 | |
| 58.82% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 85 | | matches | | 0 | "Now he cleared his throat" |
| | ratio | 0.012 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 4 | | matches | | 0 | "Below the floorboards the curry house exhaled heat and cumin and fried onion straight up through the vents, and Ptolemy the tabby wound himself hard around her …" | | 1 | "Three weeks since she had told herself good, fine, she had left Cardiff and Pre-Law and Brendan Carter's disappointed silences and Evan's hands to stop needing …" | | 2 | "Cool-headed, Eva always teased, our Rory with the ice water in her veins, the girl who talked a Cardiff landlord out of keeping her deposit with case law quoted…" | | 3 | "Ptolemy crept out and butted his head against Lucien's polished, ruined shoe, and Lucien, the impeccable fixer who charged two hundred pounds just to answer a q…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0 | | effectiveRatio | 0 | |