| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 1 | | adverbTags | | 0 | "He gestured vaguely [vaguely]" |
| | dialogueSentences | 67 | | tagDensity | 0.149 | | leniency | 0.299 | | rawRatio | 0.1 | | effectiveRatio | 0.03 | |
| 95.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1198 | | totalAiIsmAdverbs | 1 | | 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) | |
| 49.92% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1198 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "shattered" | | 1 | "flickered" | | 2 | "tracing" | | 3 | "flicked" | | 4 | "tension" | | 5 | "trembled" | | 6 | "pulse" | | 7 | "unreadable" | | 8 | "eyebrow" |
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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 | 113 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 113 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 166 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 11 | | markdownWords | 16 | | totalWords | 1188 | | ratio | 0.013 | | matches | | 0 | "\"You’re a fucking liar, Blackwood!\"" | | 1 | "recognition" | | 2 | "is" | | 3 | "his" | | 4 | "everything" | | 5 | "me" | | 6 | "let go" | | 7 | "secret" | | 8 | "someone" | | 9 | "hard" | | 10 | "are" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 6.80% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 838 | | uniqueNames | 6 | | maxNameDensity | 2.86 | | worstName | "Silas" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Silas" | | discoveredNames | | Rory | 14 | | Raven | 2 | | Nest | 2 | | Evan | 11 | | Silas | 24 | | London | 1 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Evan" | | 4 | "Silas" |
| | places | | | globalScore | 0.068 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1188 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 166 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 74 | | mean | 16.05 | | std | 14.64 | | cv | 0.912 | | sampleLengths | | 0 | 37 | | 1 | 74 | | 2 | 7 | | 3 | 30 | | 4 | 9 | | 5 | 4 | | 6 | 63 | | 7 | 11 | | 8 | 32 | | 9 | 6 | | 10 | 14 | | 11 | 14 | | 12 | 10 | | 13 | 9 | | 14 | 18 | | 15 | 11 | | 16 | 13 | | 17 | 1 | | 18 | 10 | | 19 | 13 | | 20 | 8 | | 21 | 8 | | 22 | 22 | | 23 | 11 | | 24 | 36 | | 25 | 4 | | 26 | 5 | | 27 | 43 | | 28 | 6 | | 29 | 18 | | 30 | 14 | | 31 | 20 | | 32 | 24 | | 33 | 5 | | 34 | 11 | | 35 | 3 | | 36 | 26 | | 37 | 13 | | 38 | 17 | | 39 | 7 | | 40 | 15 | | 41 | 1 | | 42 | 12 | | 43 | 8 | | 44 | 1 | | 45 | 80 | | 46 | 13 | | 47 | 17 | | 48 | 11 | | 49 | 34 |
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| 95.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 113 | | matches | | 0 | "was squared" | | 1 | "been replaced" | | 2 | "were lined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 164 | | matches | | |
| 5.16% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 166 | | ratio | 0.048 | | matches | | 0 | "A man’s voice, rough as gravel, cut through the hum of the bar—*\"You’re a fucking liar, Blackwood!\"*—and then the crash." | | 1 | "The Raven’s Nest smelled the same—whiskey, old wood, and the faint metallic tang of something beneath it, something that didn’t belong in a place like this." | | 2 | "His eyes locked onto hers—*recognition*—and for a second, the bar fell silent." | | 3 | "He looked different—older, harder, the kind of man who’d spent years grinding his teeth into dust." | | 4 | "\"You think you’re better than this? Than *me*?\" His hand shot out, fingers closing around her wrist—the one with the crescent scar." | | 5 | "The walls were lined with maps—some old, some new—pinned with red tacks and yellowed notes." | | 6 | "\"Not like this.\" He gestured vaguely at her—her posture, her clothes, the way she held herself." | | 7 | "She turned away, her fingers tracing the edge of an old map—London, pre-WWII, the streets marked in faded ink." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 848 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.031839622641509434 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00589622641509434 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 166 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 166 | | mean | 7.15 | | std | 5.39 | | cv | 0.754 | | sampleLengths | | 0 | 12 | | 1 | 20 | | 2 | 3 | | 3 | 2 | | 4 | 26 | | 5 | 12 | | 6 | 16 | | 7 | 4 | | 8 | 16 | | 9 | 7 | | 10 | 4 | | 11 | 14 | | 12 | 12 | | 13 | 4 | | 14 | 5 | | 15 | 3 | | 16 | 1 | | 17 | 9 | | 18 | 16 | | 19 | 14 | | 20 | 24 | | 21 | 10 | | 22 | 1 | | 23 | 7 | | 24 | 25 | | 25 | 3 | | 26 | 3 | | 27 | 6 | | 28 | 3 | | 29 | 5 | | 30 | 8 | | 31 | 3 | | 32 | 3 | | 33 | 10 | | 34 | 3 | | 35 | 6 | | 36 | 3 | | 37 | 4 | | 38 | 4 | | 39 | 7 | | 40 | 4 | | 41 | 7 | | 42 | 9 | | 43 | 4 | | 44 | 1 | | 45 | 10 | | 46 | 9 | | 47 | 3 | | 48 | 1 | | 49 | 5 |
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| 47.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.2469879518072289 | | totalSentences | 166 | | uniqueOpeners | 41 | |
| 32.68% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 102 | | matches | | 0 | "Just stared at him, unblinking." |
| | ratio | 0.01 | |
| 82.75% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 102 | | matches | | 0 | "She didn’t flinch." | | 1 | "She hadn’t ordered it." | | 2 | "She turned, slow, deliberate." | | 3 | "His eyes locked onto hers—*recognition*—and" | | 4 | "His voice cracked" | | 5 | "She didn’t smile." | | 6 | "He looked different—older, harder, the" | | 7 | "His jaw was squared, his" | | 8 | "His fingers twitched at his" | | 9 | "She set the glass down." | | 10 | "He leaned in, close enough" | | 11 | "His hand shot out, fingers" | | 12 | "She didn’t pull away." | | 13 | "His grip tightened." | | 14 | "She could have stepped in." | | 15 | "He shoved Silas away, straightening" | | 16 | "She didn’t answer." | | 17 | "He stormed out, the door" | | 18 | "She set the glass down." | | 19 | "He exhaled, running a hand" |
| | ratio | 0.343 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 97 | | totalSentences | 102 | | matches | | 0 | "The glass shattered against the" | | 1 | "A man’s voice, rough as" | | 2 | "She didn’t flinch." | | 3 | "The Raven’s Nest smelled the" | | 4 | "The green neon sign outside" | | 5 | "Rory leaned against the bar," | | 6 | "She hadn’t ordered it." | | 7 | "Silas had slid it toward" | | 8 | "A hand clamped down on" | | 9 | "She turned, slow, deliberate." | | 10 | "The man behind her was" | | 11 | "His eyes locked onto hers—*recognition*—and" | | 12 | "His voice cracked" | | 13 | "She didn’t smile." | | 14 | "The name hung between them," | | 15 | "He looked different—older, harder, the" | | 16 | "His jaw was squared, his" | | 17 | "The last time she’d seen" | | 18 | "Silas appeared at her elbow," | | 19 | "Evan’s laugh was a dry," |
| | ratio | 0.951 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 102 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 2 | | matches | | 0 | "The Raven’s Nest smelled the same—whiskey, old wood, and the faint metallic tang of something beneath it, something that didn’t belong in a place like this." | | 1 | "He looked different—older, harder, the kind of man who’d spent years grinding his teeth into dust." |
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| 75.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 1 | | matches | | 0 | "He gestured vaguely, her clothes, the way she held herself" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 67 | | tagDensity | 0.045 | | leniency | 0.09 | | rawRatio | 0.333 | | effectiveRatio | 0.03 | |