| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 2 | | adverbTags | | 0 | "Rory gestured vaguely [vaguely]" | | 1 | "Rory said softly [softly]" |
| | dialogueSentences | 41 | | tagDensity | 0.537 | | leniency | 1 | | rawRatio | 0.091 | | effectiveRatio | 0.091 | |
| 92.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1312 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 46.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1312 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "familiar" | | 1 | "glinting" | | 2 | "scanning" | | 3 | "weight" | | 4 | "flickered" | | 5 | "tension" | | 6 | "unspoken" | | 7 | "silence" | | 8 | "echoing" | | 9 | "unreadable" |
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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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1312 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 1049 | | uniqueNames | 12 | | maxNameDensity | 1.91 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Soho | 2 | | Aurora | 1 | | Golden | 2 | | Empress | 2 | | Cardiff | 3 | | Rory | 20 | | Evan | 2 | | London | 2 | | Eva | 20 | | Silas | 5 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Rory" | | 4 | "Evan" | | 5 | "Eva" | | 6 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "London" |
| | globalScore | 0.547 | | windowScore | 0.167 | |
| 77.54% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 2 | | matches | | 0 | "buzz that seemed to vibrate through the pavement and into the soles of Aurora’s boots" | | 1 | "felt like a canyon" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.762 | | wordCount | 1312 | | matches | | 0 | "not in age, but in hardness" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 115 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 26.24 | | std | 21.56 | | cv | 0.822 | | sampleLengths | | 0 | 92 | | 1 | 87 | | 2 | 17 | | 3 | 48 | | 4 | 12 | | 5 | 46 | | 6 | 16 | | 7 | 1 | | 8 | 57 | | 9 | 54 | | 10 | 14 | | 11 | 21 | | 12 | 28 | | 13 | 21 | | 14 | 47 | | 15 | 7 | | 16 | 4 | | 17 | 18 | | 18 | 7 | | 19 | 60 | | 20 | 31 | | 21 | 24 | | 22 | 24 | | 23 | 6 | | 24 | 23 | | 25 | 52 | | 26 | 8 | | 27 | 36 | | 28 | 7 | | 29 | 26 | | 30 | 14 | | 31 | 14 | | 32 | 10 | | 33 | 36 | | 34 | 30 | | 35 | 10 | | 36 | 43 | | 37 | 6 | | 38 | 23 | | 39 | 42 | | 40 | 14 | | 41 | 16 | | 42 | 10 | | 43 | 4 | | 44 | 7 | | 45 | 26 | | 46 | 22 | | 47 | 10 | | 48 | 4 | | 49 | 77 |
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| 94.41% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 97 | | matches | | 0 | "was supposed" | | 1 | "been ironed" | | 2 | "been sacrificed" |
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| 15.84% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 181 | | matches | | 0 | "wasn’t looking" | | 1 | "was looking" | | 2 | "was watching" | | 3 | "was pouring" | | 4 | "was still falling" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 115 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1053 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.027540360873694207 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008547008547008548 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 11.41 | | std | 6.88 | | cv | 0.603 | | sampleLengths | | 0 | 30 | | 1 | 25 | | 2 | 17 | | 3 | 20 | | 4 | 18 | | 5 | 10 | | 6 | 23 | | 7 | 4 | | 8 | 17 | | 9 | 15 | | 10 | 6 | | 11 | 11 | | 12 | 17 | | 13 | 19 | | 14 | 12 | | 15 | 12 | | 16 | 8 | | 17 | 25 | | 18 | 13 | | 19 | 2 | | 20 | 14 | | 21 | 1 | | 22 | 5 | | 23 | 22 | | 24 | 30 | | 25 | 10 | | 26 | 9 | | 27 | 17 | | 28 | 18 | | 29 | 3 | | 30 | 11 | | 31 | 5 | | 32 | 9 | | 33 | 7 | | 34 | 12 | | 35 | 5 | | 36 | 8 | | 37 | 3 | | 38 | 20 | | 39 | 1 | | 40 | 10 | | 41 | 21 | | 42 | 16 | | 43 | 7 | | 44 | 4 | | 45 | 7 | | 46 | 11 | | 47 | 7 | | 48 | 13 | | 49 | 27 |
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| 36.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.25217391304347825 | | totalSentences | 115 | | uniqueOpeners | 29 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 36.87% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 83 | | matches | | 0 | "She stood under the awning" | | 1 | "She pushed through the door," | | 2 | "He looked up, his hazel" | | 3 | "He didn’t speak, just gave" | | 4 | "He knew the routine." | | 5 | "She was supposed to be" | | 6 | "She wasn’t looking for a" | | 7 | "She was looking for a" | | 8 | "She moved toward a corner" | | 9 | "She rubbed it absently, a" | | 10 | "She wore a coat that" | | 11 | "It had been five years." | | 12 | "She looked older, not in" | | 13 | "Her hair was shorter, dyed" | | 14 | "She stood up, the chair" | | 15 | "She didn’t offer a hug." | | 16 | "He had stopped wiping the" | | 17 | "He was a ghost in" | | 18 | "She placed her bag on" | | 19 | "She didn’t look at Rory." |
| | ratio | 0.458 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 83 | | matches | | 0 | "The green neon sign of" | | 1 | "She stood under the awning" | | 2 | "The air inside the bar" | | 3 | "She pushed through the door," | | 4 | "Silas was behind the bar," | | 5 | "He looked up, his hazel" | | 6 | "He didn’t speak, just gave" | | 7 | "He knew the routine." | | 8 | "Rory worked the deliveries for" | | 9 | "She was supposed to be" | | 10 | "She wasn’t looking for a" | | 11 | "She was looking for a" | | 12 | "She moved toward a corner" | | 13 | "The small crescent-shaped scar there," | | 14 | "She rubbed it absently, a" | | 15 | "The door opened again, cutting" | | 16 | "A woman stepped in, shaking" | | 17 | "She wore a coat that" | | 18 | "The woman turned, scanning the" | | 19 | "The air left her lungs," |
| | ratio | 0.988 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 83 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 2 | | matches | | 0 | "The green neon sign of The Raven’s Nest hummed against the Soho rain, a persistent buzz that seemed to vibrate through the pavement and into the soles of Aurora…" | | 1 | "She wore a coat that cost more than Rory’s monthly rent, tailored wool in a deep charcoal that repelled the rain rather than absorbing it." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 1 | | matches | | 0 | "he asked, his voice low and gravelly" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 2 | | fancyTags | | 0 | "Rory corrected (correct)" | | 1 | "Eva sighed (sigh)" |
| | dialogueSentences | 41 | | tagDensity | 0.317 | | leniency | 0.634 | | rawRatio | 0.154 | | effectiveRatio | 0.098 | |