| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 24 | | adverbTagCount | 2 | | adverbTags | | 0 | "she corrected automatically [automatically]" | | 1 | "he said quietly [quietly]" |
| | dialogueSentences | 39 | | tagDensity | 0.615 | | leniency | 1 | | rawRatio | 0.083 | | effectiveRatio | 0.083 | |
| 79.49% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1219 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "very" | | 1 | "softly" | | 2 | "slowly" | | 3 | "quickly" | | 4 | "truly" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1219 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "gloom" | | 1 | "glinting" | | 2 | "weight" | | 3 | "pulsed" |
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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 | 71 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 71 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 49 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1204 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 800 | | uniqueNames | 18 | | maxNameDensity | 1.38 | | worstName | "Evan" | | maxWindowNameDensity | 3 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Yu-Fei | 1 | | Cheung | 1 | | Silas | 5 | | Prague | 1 | | Rory | 10 | | Aurora | 2 | | Evan | 11 | | Pre | 1 | | Law | 1 | | Cardiff | 1 | | University | 1 | | Soho | 1 | | London | 1 | | Carter | 2 | | Laila | 1 | | Malphora | 1 |
| | persons | | 0 | "Raven" | | 1 | "Yu-Fei" | | 2 | "Cheung" | | 3 | "Silas" | | 4 | "Rory" | | 5 | "Aurora" | | 6 | "Evan" | | 7 | "Carter" | | 8 | "Laila" | | 9 | "Malphora" |
| | places | | 0 | "Prague" | | 1 | "Cardiff" | | 2 | "Soho" | | 3 | "London" |
| | globalScore | 0.813 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 3 | | matches | | 0 | "felt like surrender rather than defeat" | | 1 | "felt like a wall" | | 2 | "felt like a woman who had finally set d" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.492 | | wordCount | 1204 | | matches | | 0 | "not with the old proprietary swagger, but with a hesitation" | | 1 | "not with recognition, exactly, but with the evaluation of a former MI6 field agent who had seen" | | 2 | "not with pain, but with the strange peace of something" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 28.67 | | std | 19.5 | | cv | 0.68 | | sampleLengths | | 0 | 86 | | 1 | 6 | | 2 | 58 | | 3 | 1 | | 4 | 89 | | 5 | 24 | | 6 | 10 | | 7 | 27 | | 8 | 18 | | 9 | 25 | | 10 | 22 | | 11 | 17 | | 12 | 12 | | 13 | 37 | | 14 | 14 | | 15 | 43 | | 16 | 22 | | 17 | 30 | | 18 | 29 | | 19 | 16 | | 20 | 14 | | 21 | 48 | | 22 | 34 | | 23 | 54 | | 24 | 25 | | 25 | 14 | | 26 | 34 | | 27 | 12 | | 28 | 8 | | 29 | 41 | | 30 | 28 | | 31 | 39 | | 32 | 23 | | 33 | 12 | | 34 | 42 | | 35 | 4 | | 36 | 34 | | 37 | 19 | | 38 | 5 | | 39 | 40 | | 40 | 58 | | 41 | 30 |
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| 95.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 71 | | matches | | 0 | "been polished" | | 1 | "been seen" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 145 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 86 | | ratio | 0.07 | | matches | | 0 | "She needed air that smelled of nothing—no fried oil from Yu-Fei Cheung’s kitchen, no damp plaster of the flat above this very bar." | | 1 | "Not Silas—he was behind the bar, grey-streaked auburn beard catching the low light, silver signet ring glinting as he polished a glass with the efficiency of a retired intelligence operative who still believed in ritual." | | 2 | "The boy she had known—Pre-Law at Cardiff University, relentless, controlling—had been polished to this: a man in expensive wool sitting in a Soho bar named after some hidden intelligence, carrying a briefcase that probably weighed more in guilt than paper." | | 3 | "The bar around them continued its murmur—Silas moving with his slight limp behind the counter, some other patrons arguing softly about politics or debts—but Rory felt the weight of years pressing against her ribs." | | 4 | "Silas looked at Evan—not with recognition, exactly, but with the evaluation of a former MI6 field agent who had seen every kind of damage a person could carry." | | 5 | "Inside, beneath the green neon glow filtering through the window, Rory Carter—Aurora, Laila, Carter, Malphora—felt the strange lightness of a weight she had not realized she was still carrying." |
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| 80.45% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 757 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped mark" |
| | adverbCount | 42 | | adverbRatio | 0.05548216644649934 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.015852047556142668 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 14 | | std | 10.98 | | cv | 0.784 | | sampleLengths | | 0 | 24 | | 1 | 23 | | 2 | 19 | | 3 | 20 | | 4 | 6 | | 5 | 35 | | 6 | 23 | | 7 | 1 | | 8 | 28 | | 9 | 12 | | 10 | 24 | | 11 | 25 | | 12 | 6 | | 13 | 18 | | 14 | 3 | | 15 | 7 | | 16 | 7 | | 17 | 7 | | 18 | 13 | | 19 | 18 | | 20 | 5 | | 21 | 8 | | 22 | 12 | | 23 | 18 | | 24 | 4 | | 25 | 7 | | 26 | 10 | | 27 | 2 | | 28 | 4 | | 29 | 6 | | 30 | 9 | | 31 | 28 | | 32 | 5 | | 33 | 9 | | 34 | 3 | | 35 | 40 | | 36 | 6 | | 37 | 5 | | 38 | 11 | | 39 | 5 | | 40 | 25 | | 41 | 4 | | 42 | 25 | | 43 | 16 | | 44 | 4 | | 45 | 10 | | 46 | 5 | | 47 | 43 | | 48 | 34 | | 49 | 7 |
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| 59.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.38372093023255816 | | totalSentences | 86 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 54 | | matches | | 0 | "Then he stood, not with" | | 1 | "Only her mother still called" | | 2 | "Only Evan had ever insisted" | | 3 | "Of course he flinched." | | 4 | "Then he limped away, leaving" |
| | ratio | 0.093 | |
| 57.04% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 54 | | matches | | 0 | "She needed air that smelled" | | 1 | "She ordered a whiskey, neat," | | 2 | "She recognized the cut of" | | 3 | "His hair, once meticulously styled," | | 4 | "He wore a navy coat" | | 5 | "she corrected automatically, then regretted" | | 6 | "He smiled, and the expression" | | 7 | "She let the whiskey burn" | | 8 | "He sat back down, leaving" | | 9 | "He had always performed sympathy" | | 10 | "she asked, though she already" | | 11 | "It was not a question." | | 12 | "It was an accusation she" | | 13 | "He did not deny it." | | 14 | "He looked down at his" | | 15 | "he said quietly" | | 16 | "His finger stopped an inch" | | 17 | "His silver signet ring caught" | | 18 | "His voice was low, protective" | | 19 | "she said, standing" |
| | ratio | 0.407 | |
| 80.37% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 54 | | matches | | 0 | "Rory pushed through the heavy" | | 1 | "She needed air that smelled" | | 2 | "The dim interior swallowed her," | | 3 | "She ordered a whiskey, neat," | | 4 | "That was when she saw" | | 5 | "She recognized the cut of" | | 6 | "His hair, once meticulously styled," | | 7 | "He wore a navy coat" | | 8 | "The name landed like a" | | 9 | "she corrected automatically, then regretted" | | 10 | "He smiled, and the expression" | | 11 | "She let the whiskey burn" | | 12 | "He sat back down, leaving" | | 13 | "Rory said, flat and true" | | 14 | "He had always performed sympathy" | | 15 | "she asked, though she already" | | 16 | "The rumor mill at The" | | 17 | "Rory studied him." | | 18 | "The boy she had known—Pre—Law" | | 19 | "It was not a question." |
| | ratio | 0.759 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 3 | | matches | | 0 | "She needed air that smelled of nothing—no fried oil from Yu-Fei Cheung’s kitchen, no damp plaster of the flat above this very bar." | | 1 | "Then he stood, not with the old proprietary swagger, but with a hesitation that made Rory’s breath catch." | | 2 | "The crescent scar on her left wrist pulsed faintly, not with pain, but with the strange peace of something that had finally been seen in the light and left behi…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 24 | | uselessAdditionCount | 1 | | matches | | 0 | "He smiled, and the expression failed to reach the new hollows under his eyes" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 20 | | fancyCount | 2 | | fancyTags | | 0 | "she corrected automatically (correct)" | | 1 | "Rory corrected (correct)" |
| | dialogueSentences | 39 | | tagDensity | 0.513 | | leniency | 1 | | rawRatio | 0.1 | | effectiveRatio | 0.1 | |