| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1553 | | 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) | |
| 64.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1553 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "silence" | | 1 | "scanned" | | 2 | "throbbed" | | 3 | "pulse" | | 4 | "weight" | | 5 | "resolved" | | 6 | "charged" | | 7 | "rhythmic" | | 8 | "unreadable" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 252 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 252 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 252 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 18 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1553 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 77 | | wordCount | 1553 | | uniqueNames | 18 | | maxNameDensity | 1.03 | | worstName | "You" | | maxWindowNameDensity | 3 | | worstWindowName | "You" | | discoveredNames | | Moreau | 1 | | Brick | 2 | | Lane | 2 | | Eva | 1 | | Soho | 1 | | Paris | 1 | | Cardiff | 1 | | Evan | 5 | | Syndicate | 3 | | Lucien | 5 | | Marseille | 1 | | East | 1 | | London | 2 | | Ptolemy | 4 | | Aurora | 7 | | Lucienne | 13 | | You | 16 | | Rory | 11 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Evan" | | 3 | "Syndicate" | | 4 | "Lucien" | | 5 | "Ptolemy" | | 6 | "Aurora" | | 7 | "Lucienne" | | 8 | "You" | | 9 | "Rory" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Soho" | | 3 | "Paris" | | 4 | "Cardiff" | | 5 | "Marseille" | | 6 | "East" | | 7 | "London" |
| | globalScore | 0.985 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 115 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like expensive cologne and somethi" |
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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 | 1553 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 252 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 130 | | mean | 11.95 | | std | 11.47 | | cv | 0.96 | | sampleLengths | | 0 | 19 | | 1 | 66 | | 2 | 8 | | 3 | 22 | | 4 | 48 | | 5 | 51 | | 6 | 3 | | 7 | 11 | | 8 | 24 | | 9 | 13 | | 10 | 30 | | 11 | 35 | | 12 | 9 | | 13 | 4 | | 14 | 34 | | 15 | 5 | | 16 | 33 | | 17 | 5 | | 18 | 6 | | 19 | 31 | | 20 | 12 | | 21 | 6 | | 22 | 9 | | 23 | 29 | | 24 | 4 | | 25 | 25 | | 26 | 14 | | 27 | 6 | | 28 | 28 | | 29 | 2 | | 30 | 2 | | 31 | 20 | | 32 | 4 | | 33 | 6 | | 34 | 3 | | 35 | 8 | | 36 | 19 | | 37 | 11 | | 38 | 19 | | 39 | 2 | | 40 | 56 | | 41 | 11 | | 42 | 15 | | 43 | 6 | | 44 | 23 | | 45 | 4 | | 46 | 34 | | 47 | 3 | | 48 | 1 | | 49 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 252 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 305 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 252 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1555 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.021864951768488745 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.0038585209003215433 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 252 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 252 | | mean | 6.16 | | std | 3.73 | | cv | 0.606 | | sampleLengths | | 0 | 5 | | 1 | 14 | | 2 | 17 | | 3 | 18 | | 4 | 13 | | 5 | 18 | | 6 | 5 | | 7 | 3 | | 8 | 7 | | 9 | 10 | | 10 | 5 | | 11 | 12 | | 12 | 9 | | 13 | 12 | | 14 | 15 | | 15 | 11 | | 16 | 14 | | 17 | 12 | | 18 | 14 | | 19 | 3 | | 20 | 7 | | 21 | 4 | | 22 | 5 | | 23 | 7 | | 24 | 12 | | 25 | 10 | | 26 | 3 | | 27 | 12 | | 28 | 3 | | 29 | 15 | | 30 | 2 | | 31 | 6 | | 32 | 14 | | 33 | 13 | | 34 | 4 | | 35 | 5 | | 36 | 4 | | 37 | 3 | | 38 | 7 | | 39 | 15 | | 40 | 9 | | 41 | 5 | | 42 | 2 | | 43 | 3 | | 44 | 7 | | 45 | 6 | | 46 | 6 | | 47 | 9 | | 48 | 5 | | 49 | 6 |
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| 42.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.18253968253968253 | | totalSentences | 252 | | uniqueOpeners | 46 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 226 | | matches | (empty) | | ratio | 0 | |
| 9.38% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 119 | | totalSentences | 226 | | matches | | 0 | "His eyes scanned the interior," | | 1 | "His presence filled the threshold." | | 2 | "He hadn’t knocked." | | 3 | "I thought you were dead." | | 4 | "She knew the question hung" | | 5 | "He didn’t stop when he" | | 6 | "You live here." | | 7 | "It’s safer this way." | | 8 | "He stopped two feet away." | | 9 | "His gaze dropped to her" | | 10 | "You told Eva you’d stay" | | 11 | "It’s a safe house while" | | 12 | "It didn’t reach the amber" | | 13 | "He leaned the cane against" | | 14 | "I needed to see you." | | 15 | "You could have written." | | 16 | "He moved closer." | | 17 | "Your ex-husband is in Paris." | | 18 | "He’d died six months ago" | | 19 | "He knew Evan better than" |
| | ratio | 0.527 | |
| 2.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 207 | | totalSentences | 226 | | matches | | 0 | "The chain latch clicked open." | | 1 | "Aurora shoved the door, expecting" | | 2 | "Silence filled the hallway, cut" | | 3 | "Lucienne Moreau stood in the" | | 4 | "The ivory handle of his" | | 5 | "His eyes scanned the interior," | | 6 | "His presence filled the threshold." | | 7 | "He hadn’t knocked." | | 8 | "Aurora kept her hand on" | | 9 | "The scar on her left" | | 10 | "I thought you were dead." | | 11 | "She knew the question hung" | | 12 | "The hallway smelled of curry" | | 13 | "Books stacked along the walls" | | 14 | "Ptolemy, the tabby, lurked behind" | | 15 | "Lucienne pushed past her without" | | 16 | "The fabric of his suit" | | 17 | "He didn’t stop when he" | | 18 | "The space cramped under the" | | 19 | "You live here." |
| | ratio | 0.916 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 8 | | totalSentences | 226 | | matches | | 0 | "Because the deal I made" | | 1 | "To bring you something." | | 2 | "Because he called tonight." | | 3 | "If you don’t open it," | | 4 | "To Brick Lane." | | 5 | "To find you." | | 6 | "If you stay, they’ll burn" | | 7 | "Because I need you to" |
| | ratio | 0.035 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |