| 42.31% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 7 | | adverbTags | | 0 | "she corrected gently [gently]" | | 1 | "she said finally [finally]" | | 2 | "He gestured vaguely [vaguely]" | | 3 | "she said suddenly [suddenly]" | | 4 | "Her fingers curled around [around]" | | 5 | "she corrected gently [gently]" | | 6 | "She smiled again [again]" |
| | dialogueSentences | 65 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.269 | | effectiveRatio | 0.215 | |
| 71.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1772 | | totalAiIsmAdverbs | 10 | | found | | | highlights | | 0 | "gently" | | 1 | "slowly" | | 2 | "slightly" | | 3 | "carefully" | | 4 | "very" | | 5 | "completely" | | 6 | "suddenly" |
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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) | |
| 71.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1772 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "flicker" | | 1 | "weight" | | 2 | "chill" | | 3 | "sense of" | | 4 | "echoed" | | 5 | "silence" | | 6 | "flickered" |
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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 | 95 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 95 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 134 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1755 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 1130 | | uniqueNames | 10 | | maxNameDensity | 0.18 | | worstName | "Raven" | | maxWindowNameDensity | 1 | | worstWindowName | "Raven" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Tuesday | 1 | | Silas | 2 | | Prague | 2 | | Soho | 2 | | October | 1 | | Green | 1 | | Spot | 1 | | Moscow | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Spot" |
| | places | | 0 | "Prague" | | 1 | "Soho" | | 2 | "Moscow" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like herself again, like the woman" |
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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 | 1755 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 134 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 32.5 | | std | 25.81 | | cv | 0.794 | | sampleLengths | | 0 | 73 | | 1 | 67 | | 2 | 76 | | 3 | 13 | | 4 | 87 | | 5 | 2 | | 6 | 43 | | 7 | 1 | | 8 | 12 | | 9 | 19 | | 10 | 41 | | 11 | 86 | | 12 | 16 | | 13 | 4 | | 14 | 4 | | 15 | 7 | | 16 | 31 | | 17 | 39 | | 18 | 17 | | 19 | 33 | | 20 | 17 | | 21 | 2 | | 22 | 5 | | 23 | 11 | | 24 | 44 | | 25 | 4 | | 26 | 3 | | 27 | 58 | | 28 | 62 | | 29 | 9 | | 30 | 49 | | 31 | 40 | | 32 | 3 | | 33 | 32 | | 34 | 4 | | 35 | 79 | | 36 | 33 | | 37 | 13 | | 38 | 72 | | 39 | 14 | | 40 | 56 | | 41 | 5 | | 42 | 53 | | 43 | 3 | | 44 | 17 | | 45 | 22 | | 46 | 41 | | 47 | 32 | | 48 | 32 | | 49 | 54 |
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| 97.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 95 | | matches | | 0 | "was concerned" | | 1 | "was pressed" |
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| 96.37% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 193 | | matches | | 0 | "were looking" | | 1 | "was testing" | | 2 | "was waiting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 134 | | ratio | 0.082 | | matches | | 0 | "He didn't look up immediately—customer service was a performance he'd never quite learned, and besides, most people who came to The Raven's Nest knew what they were looking for." | | 1 | "Ten years—actually eleven, he realized, doing the math with the same precision he'd once applied to asset movements and extraction windows—eleven years could reshape a person, and it had reshaped her." | | 2 | "That was the thing that struck him first—the way the vowels still curled at the edges, that slight lift on his name that had always made it sound like something other than a word." | | 3 | "She'd been beautiful once in a way that made other people nervous—dangerous beauty, the kind that made men underestimate her and women envy her." | | 4 | "Outside, a car passed, its headlights sweeping briefly across the window and casting their reflections back at them—two ghosts in a dim room, older than they remembered being." | | 5 | "\"The bar needed me.\" He gestured vaguely at the room—the maps, the photographs, the carefully curated sense of age and mystery." | | 6 | "She met his eyes then, and for a moment he saw her as she'd been—twenty-six, brilliant, impossible." | | 7 | "Silas poured himself a whiskey—he didn't usually drink on the job, but this wasn't a job, this was something else—and raised the glass in a small toast." | | 8 | "Somewhere in the back room—the hidden room, the one behind the bookshelf—someone was waiting for a contact that might never come." | | 9 | "He'd forgotten he'd given it to her—Moscow, 1998, the night before the op that had nearly gotten them both killed." | | 10 | "The street outside was growing busier now, the sounds of Soho at night filtering in—a shout, a laugh, the rumble of a bus." |
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| 89.93% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1146 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 58 | | adverbRatio | 0.0506108202443281 | | lyAdverbCount | 24 | | lyAdverbRatio | 0.020942408376963352 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 134 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 134 | | mean | 13.1 | | std | 10 | | cv | 0.764 | | sampleLengths | | 0 | 23 | | 1 | 21 | | 2 | 3 | | 3 | 26 | | 4 | 21 | | 5 | 3 | | 6 | 34 | | 7 | 6 | | 8 | 3 | | 9 | 17 | | 10 | 29 | | 11 | 6 | | 12 | 4 | | 13 | 4 | | 14 | 16 | | 15 | 13 | | 16 | 25 | | 17 | 31 | | 18 | 13 | | 19 | 18 | | 20 | 2 | | 21 | 4 | | 22 | 34 | | 23 | 5 | | 24 | 1 | | 25 | 4 | | 26 | 8 | | 27 | 14 | | 28 | 5 | | 29 | 29 | | 30 | 3 | | 31 | 4 | | 32 | 5 | | 33 | 3 | | 34 | 25 | | 35 | 18 | | 36 | 24 | | 37 | 7 | | 38 | 7 | | 39 | 2 | | 40 | 12 | | 41 | 4 | | 42 | 4 | | 43 | 4 | | 44 | 4 | | 45 | 1 | | 46 | 2 | | 47 | 18 | | 48 | 13 | | 49 | 23 |
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| 51.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.35074626865671643 | | totalSentences | 134 | | uniqueOpeners | 47 | |
| 39.22% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 85 | | matches | | 0 | "Somewhere in the back room—the" |
| | ratio | 0.012 | |
| 12.94% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 85 | | matches | | 0 | "He stood behind the bar," | | 1 | "His right hand moved unconsciously" | | 2 | "He didn't sleep at all" | | 3 | "He just rested." | | 4 | "He didn't look up immediately—customer" | | 5 | "She stood just inside the" | | 6 | "Her voice hadn't changed." | | 7 | "He set the glass down." | | 8 | "she corrected gently" | | 9 | "He nodded slowly, reaching for" | | 10 | "She moved toward the bar," | | 11 | "He had it." | | 12 | "He poured a generous measure" | | 13 | "She'd been beautiful once in" | | 14 | "She was beautiful still, but" | | 15 | "she said, and the words" | | 16 | "He flinched, almost imperceptibly." | | 17 | "She took a sip of" | | 18 | "He said it flatly, the" | | 19 | "She repeated the word like" |
| | ratio | 0.518 | |
| 18.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 85 | | matches | | 0 | "The Raven's Nest was quiet" | | 1 | "He stood behind the bar," | | 2 | "The evening crowd wouldn't trickle" | | 3 | "His right hand moved unconsciously" | | 4 | "A nervous habit." | | 5 | "The doctors had told him" | | 6 | "He didn't sleep at all" | | 7 | "He just rested." | | 8 | "The door opened, letting in" | | 9 | "He didn't look up immediately—customer" | | 10 | "The bar attracted a certain" | | 11 | "Researchers of obscure history." | | 12 | "Journalists who'd heard rumors." | | 13 | "She stood just inside the" | | 14 | "The girl he'd known had" | | 15 | "This woman stood in the" | | 16 | "Her voice hadn't changed." | | 17 | "That was the thing that" | | 18 | "He set the glass down." | | 19 | "she corrected gently" |
| | ratio | 0.882 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 14.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 7 | | matches | | 0 | "He stood behind the bar, polishing a glass that didn't need polishing, watching the green neon sign flicker through the window." | | 1 | "He didn't look up immediately—customer service was a performance he'd never quite learned, and besides, most people who came to The Raven's Nest knew what they …" | | 2 | "Occasional former colleagues who needed a safe line and a drink that didn't come with questions." | | 3 | "She'd been beautiful once in a way that made other people nervous—dangerous beauty, the kind that made men underestimate her and women envy her." | | 4 | "Outside, a car passed, its headlights sweeping briefly across the window and casting their reflections back at them—two ghosts in a dim room, older than they re…" | | 5 | "Somewhere in the back room—the hidden room, the one behind the bookshelf—someone was waiting for a contact that might never come." | | 6 | "Tonight there was only this: two people who had once known each other completely, rebuilding a bridge across years of silence." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, and the words came out awkward, rehearsed" |
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| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 5 | | fancyTags | | 0 | "she corrected gently (correct)" | | 1 | "She repeated (repeat)" | | 2 | "he repeated (repeat)" | | 3 | "he admitted (admit)" | | 4 | "she corrected gently (correct)" |
| | dialogueSentences | 65 | | tagDensity | 0.169 | | leniency | 0.338 | | rawRatio | 0.455 | | effectiveRatio | 0.154 | |