| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 56 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1133 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 51.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1133 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "weight" | | 1 | "unspoken" | | 2 | "reminder" | | 3 | "echoed" | | 4 | "flicker" | | 5 | "footsteps" | | 6 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "the weight of his words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 98 | | matches | | 0 | "was afraid" | | 1 | "was bitter" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 147 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 16 | | totalWords | 1128 | | ratio | 0.014 | | matches | | 0 | "The Raven’s Nest" | | 1 | "thunk" | | 2 | "Christ." | | 3 | "clink" | | 4 | "at" | | 5 | "Dr. Elias Voss. Private clinic. Baker Street." | | 6 | "thud" | | 7 | "thunk" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 822 | | uniqueNames | 5 | | maxNameDensity | 2.07 | | worstName | "Silas" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Blackwood | 1 | | Rory | 7 | | Silas | 17 | | Voss | 1 |
| | persons | | 0 | "Blackwood" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Voss" |
| | places | | | globalScore | 0.466 | | windowScore | 0.167 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 4 | | matches | | 0 | "sounded like a question" | | 1 | "smelled like rain and something metallic—o" | | 2 | "looked like the Rory he remembered" | | 3 | "looked like it had been written in a hurr" |
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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 | 1128 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 147 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 76 | | mean | 14.84 | | std | 16.03 | | cv | 1.08 | | sampleLengths | | 0 | 1 | | 1 | 76 | | 2 | 64 | | 3 | 46 | | 4 | 2 | | 5 | 36 | | 6 | 1 | | 7 | 15 | | 8 | 66 | | 9 | 17 | | 10 | 30 | | 11 | 4 | | 12 | 18 | | 13 | 6 | | 14 | 10 | | 15 | 13 | | 16 | 28 | | 17 | 8 | | 18 | 1 | | 19 | 2 | | 20 | 44 | | 21 | 15 | | 22 | 5 | | 23 | 6 | | 24 | 3 | | 25 | 9 | | 26 | 16 | | 27 | 3 | | 28 | 10 | | 29 | 15 | | 30 | 4 | | 31 | 4 | | 32 | 32 | | 33 | 1 | | 34 | 17 | | 35 | 11 | | 36 | 6 | | 37 | 5 | | 38 | 47 | | 39 | 2 | | 40 | 6 | | 41 | 1 | | 42 | 14 | | 43 | 39 | | 44 | 7 | | 45 | 7 | | 46 | 3 | | 47 | 6 | | 48 | 17 | | 49 | 1 |
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| 94.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 98 | | matches | | 0 | "was singed" | | 1 | "been written" | | 2 | "was gone" |
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| 32.29% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 159 | | matches | | 0 | "was debating" | | 1 | "was imagining" | | 2 | "was trying" | | 3 | "was, staring" |
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| 84.55% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 147 | | ratio | 0.02 | | matches | | 0 | "The air inside hit like a fist—damp, thick with the scent of aged whisky and something sharper, like ozone after a storm." | | 1 | "The light caught her eyes—bright blue, sharp as a blade—and for a second, he forgot how to breathe." | | 2 | "The fabric smelled like rain and something metallic—old blood, maybe." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 828 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.03864734299516908 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 147 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 147 | | mean | 7.67 | | std | 6.75 | | cv | 0.88 | | sampleLengths | | 0 | 28 | | 1 | 22 | | 2 | 21 | | 3 | 5 | | 4 | 23 | | 5 | 22 | | 6 | 19 | | 7 | 8 | | 8 | 4 | | 9 | 27 | | 10 | 6 | | 11 | 1 | | 12 | 2 | | 13 | 11 | | 14 | 7 | | 15 | 18 | | 16 | 1 | | 17 | 6 | | 18 | 9 | | 19 | 3 | | 20 | 9 | | 21 | 2 | | 22 | 1 | | 23 | 14 | | 24 | 32 | | 25 | 5 | | 26 | 13 | | 27 | 4 | | 28 | 3 | | 29 | 2 | | 30 | 25 | | 31 | 4 | | 32 | 4 | | 33 | 5 | | 34 | 9 | | 35 | 6 | | 36 | 5 | | 37 | 5 | | 38 | 7 | | 39 | 6 | | 40 | 14 | | 41 | 10 | | 42 | 4 | | 43 | 8 | | 44 | 1 | | 45 | 2 | | 46 | 23 | | 47 | 10 | | 48 | 11 | | 49 | 9 |
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| 47.39% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3129251700680272 | | totalSentences | 147 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 81 | | matches | | 0 | "Then the door banged shut" | | 1 | "Just stared at him like" | | 2 | "Just watched him, eyes unblinking." | | 3 | "Just stared at it like" | | 4 | "Just gestured to the paper." | | 5 | "Just stared at the paper," | | 6 | "Just watched her, the way" | | 7 | "Then she turned, her heels" | | 8 | "Then he poured himself another" |
| | ratio | 0.111 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 81 | | matches | | 0 | "She stood frozen for a" | | 1 | "He knew that coat." | | 2 | "His fingers tightened around his" | | 3 | "She exhaled, slow and deliberate," | | 4 | "Her name sounded like a" | | 5 | "She looked different." | | 6 | "It looked like a brand." | | 7 | "She didn’t move." | | 8 | "She laughed, sharp and unexpected." | | 9 | "She hesitated, then slid onto" | | 10 | "She leaned forward, elbows on" | | 11 | "She didn’t deny it." | | 12 | "She wasn’t fine." | | 13 | "She laughed, but it was" | | 14 | "She met his gaze." | | 15 | "She reached for the paper," | | 16 | "she said, voice hollow" | | 17 | "She looked up, eyes wide." | | 18 | "She didn’t argue." | | 19 | "She stood, her coat brushing" |
| | ratio | 0.272 | |
| 46.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 81 | | matches | | 0 | "The door to *The Raven’s" | | 1 | "The air inside hit like" | | 2 | "The jukebox wheezed out a" | | 3 | "A woman in a fitted" | | 4 | "She stood frozen for a" | | 5 | "Silas Blackwood didn’t look up" | | 6 | "He knew that coat." | | 7 | "His fingers tightened around his" | | 8 | "The voice was smooth, amused," | | 9 | "She exhaled, slow and deliberate," | | 10 | "The light caught her eyes—bright" | | 11 | "Her name sounded like a" | | 12 | "She looked different." | | 13 | "The kind of hard that" | | 14 | "The scar on her wrist," | | 15 | "It looked like a brand." | | 16 | "Silas set his glass down" | | 17 | "She didn’t move." | | 18 | "That got a flicker." | | 19 | "A ghost of a smile." |
| | ratio | 0.827 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "The jukebox wheezed out a half-forgotten tune, the kind that made the older patrons at the bar hum along without thinking." | | 1 | "Silas set his glass down with a *clink* that echoed in the quiet." |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, voice hollow" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 56 | | tagDensity | 0.107 | | leniency | 0.214 | | rawRatio | 0 | | effectiveRatio | 0 | |