| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 2 | | adverbTags | | 0 | "He looked almost [almost]" | | 1 | "He gestured vaguely [vaguely]" |
| | dialogueSentences | 53 | | tagDensity | 0.321 | | leniency | 0.642 | | rawRatio | 0.118 | | effectiveRatio | 0.075 | |
| 78.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1140 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "lightly" | | 3 | "slowly" |
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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) | |
| 69.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1140 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "flickered" | | 1 | "eyebrow" | | 2 | "flicked" | | 3 | "silence" | | 4 | "warmth" |
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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 | 51 | | matches | (empty) | |
| 86.83% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 51 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 9 | | totalWords | 1140 | | ratio | 0.008 | | matches | | 0 | "that can't be him." | | 1 | "want me to stay close?" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 787 | | uniqueNames | 9 | | maxNameDensity | 0.64 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Rory | 3 | | Raven | 1 | | Nest | 1 | | Tom | 4 | | Whitfield | 1 | | Italian | 1 | | Silas | 5 | | Kant | 1 | | Evan | 1 |
| | persons | | 0 | "Rory" | | 1 | "Raven" | | 2 | "Tom" | | 3 | "Whitfield" | | 4 | "Silas" | | 5 | "Evan" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 82.43% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 1 | | matches | | 0 | "quite manage the top button on the first try, and for a second he hesitated, like there was something else he meant to say, some door he wanted to leave open a crack" |
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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 | 1140 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 21.11 | | std | 18.48 | | cv | 0.875 | | sampleLengths | | 0 | 14 | | 1 | 34 | | 2 | 7 | | 3 | 46 | | 4 | 1 | | 5 | 20 | | 6 | 6 | | 7 | 53 | | 8 | 2 | | 9 | 7 | | 10 | 6 | | 11 | 34 | | 12 | 19 | | 13 | 7 | | 14 | 2 | | 15 | 4 | | 16 | 51 | | 17 | 3 | | 18 | 41 | | 19 | 7 | | 20 | 61 | | 21 | 13 | | 22 | 3 | | 23 | 2 | | 24 | 9 | | 25 | 43 | | 26 | 50 | | 27 | 21 | | 28 | 30 | | 29 | 8 | | 30 | 12 | | 31 | 46 | | 32 | 4 | | 33 | 51 | | 34 | 2 | | 35 | 34 | | 36 | 6 | | 37 | 20 | | 38 | 4 | | 39 | 39 | | 40 | 7 | | 41 | 6 | | 42 | 50 | | 43 | 25 | | 44 | 7 | | 45 | 28 | | 46 | 2 | | 47 | 65 | | 48 | 31 | | 49 | 6 |
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| 98.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 51 | | matches | | |
| 21.03% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 149 | | matches | | 0 | "wasn't listening" | | 1 | "was looking" | | 2 | "was thinking" | | 3 | "wasn't listening" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 87 | | ratio | 0 | | matches | (empty) | |
| 95.03% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 788 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.04568527918781726 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.01015228426395939 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 13.1 | | std | 11.32 | | cv | 0.864 | | sampleLengths | | 0 | 14 | | 1 | 22 | | 2 | 12 | | 3 | 3 | | 4 | 4 | | 5 | 3 | | 6 | 43 | | 7 | 1 | | 8 | 3 | | 9 | 17 | | 10 | 6 | | 11 | 4 | | 12 | 24 | | 13 | 25 | | 14 | 2 | | 15 | 3 | | 16 | 4 | | 17 | 6 | | 18 | 14 | | 19 | 20 | | 20 | 19 | | 21 | 7 | | 22 | 2 | | 23 | 4 | | 24 | 39 | | 25 | 12 | | 26 | 3 | | 27 | 10 | | 28 | 22 | | 29 | 9 | | 30 | 7 | | 31 | 9 | | 32 | 52 | | 33 | 9 | | 34 | 4 | | 35 | 3 | | 36 | 2 | | 37 | 9 | | 38 | 32 | | 39 | 5 | | 40 | 6 | | 41 | 36 | | 42 | 14 | | 43 | 21 | | 44 | 7 | | 45 | 4 | | 46 | 19 | | 47 | 6 | | 48 | 2 | | 49 | 12 |
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| 75.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4942528735632184 | | totalSentences | 87 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 46 | | matches | | 0 | "Then he glanced at his" | | 1 | "Instead, he reached into his" |
| | ratio | 0.043 | |
| 2.61% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 46 | | matches | | 0 | "It didn't shatter, just clattered" | | 1 | "She wasn't listening." | | 2 | "She was looking at the" | | 3 | "He crossed the room." | | 4 | "He laughed, but it came" | | 5 | "He sat on the stool" | | 6 | "he told Silas, who raised" | | 7 | "He turned the stool slightly," | | 8 | "He didn't remember" | | 9 | "She could tell from the" | | 10 | "He said it like an" | | 11 | "He didn't finish the sentence" | | 12 | "He didn't need to." | | 13 | "She almost laughed, the old" | | 14 | "He looked almost sheepish saying" | | 15 | "He said it lightly, but" | | 16 | "She didn't elaborate" | | 17 | "He studied her for a" | | 18 | "He didn't sound convinced" | | 19 | "He glanced at his watch" |
| | ratio | 0.543 | |
| 3.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 42 | | totalSentences | 46 | | matches | | 0 | "The glass slipped from her" | | 1 | "It didn't shatter, just clattered" | | 2 | "Silas, three feet away and" | | 3 | "She wasn't listening." | | 4 | "She was looking at the" | | 5 | "The man turned." | | 6 | "Recognition flickered, then something else," | | 7 | "He crossed the room." | | 8 | "He laughed, but it came" | | 9 | "He sat on the stool" | | 10 | "he told Silas, who raised" | | 11 | "He turned the stool slightly," | | 12 | "He didn't remember" | | 13 | "She could tell from the" | | 14 | "The silence that followed lasted" | | 15 | "Silas set the whisky down" | | 16 | "Tom turned his glass a" | | 17 | "Something flickered behind his eyes," | | 18 | "That boy would have laughed." | | 19 | "This one just took a" |
| | ratio | 0.913 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 46 | | matches | | 0 | "Now his shoes gleamed, Italian" |
| | ratio | 0.022 | |
| 57.14% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 3 | | matches | | 0 | "She was looking at the man who'd just walked through the door of the Raven's Nest like he owned the place, shaking rain from a coat that cost more than her mont…" | | 1 | "Something flickered behind his eyes, the ghost of the boy who used to sit up with her until three in the morning arguing about Kant, about whether ethics could …" | | 2 | "He studied her for a long moment, the way he used to when they'd stayed up debating something that mattered, back before mattering became a luxury neither of th…" |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "He said, but his knuckles had gone pale around the glass" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.151 | | leniency | 0.302 | | rawRatio | 0 | | effectiveRatio | 0 | |