| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 50 | | tagDensity | 0.28 | | leniency | 0.56 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 594 | | 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) | |
| 32.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 594 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flicked" | | 1 | "silence" | | 2 | "shattered" | | 3 | "pulse" | | 4 | "familiar" | | 5 | "perfect" | | 6 | "echoed" | | 7 | "whisper" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 17 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 8 | | totalWords | 587 | | ratio | 0.014 | | matches | | 0 | "You're like a broken metronome." | | 1 | "Return to Sender" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 57.19% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 431 | | uniqueNames | 8 | | maxNameDensity | 1.86 | | worstName | "Evan" | | maxWindowNameDensity | 3 | | worstWindowName | "Evan" | | discoveredNames | | Rory | 4 | | Silas | 6 | | Raven | 1 | | Nest | 1 | | Evan | 8 | | Cardiff | 1 | | Celtic | 1 | | Warm | 1 |
| | persons | | 0 | "Rory" | | 1 | "Silas" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Evan" |
| | places | | | globalScore | 0.572 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 34 | | 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 | 587 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 111 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 10.87 | | std | 10.21 | | cv | 0.939 | | sampleLengths | | 0 | 26 | | 1 | 1 | | 2 | 44 | | 3 | 15 | | 4 | 25 | | 5 | 6 | | 6 | 1 | | 7 | 11 | | 8 | 47 | | 9 | 7 | | 10 | 2 | | 11 | 21 | | 12 | 3 | | 13 | 3 | | 14 | 12 | | 15 | 5 | | 16 | 24 | | 17 | 4 | | 18 | 13 | | 19 | 26 | | 20 | 1 | | 21 | 10 | | 22 | 1 | | 23 | 16 | | 24 | 9 | | 25 | 4 | | 26 | 4 | | 27 | 2 | | 28 | 4 | | 29 | 30 | | 30 | 4 | | 31 | 15 | | 32 | 1 | | 33 | 3 | | 34 | 26 | | 35 | 14 | | 36 | 14 | | 37 | 4 | | 38 | 13 | | 39 | 11 | | 40 | 8 | | 41 | 5 | | 42 | 16 | | 43 | 3 | | 44 | 4 | | 45 | 3 | | 46 | 15 | | 47 | 6 | | 48 | 14 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 83 | | matches | (empty) | |
| 39.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 111 | | ratio | 0.036 | | matches | | 0 | "That same lazy smile, but his eyes—different now." | | 1 | "But the way he drummed his fingers—three quick taps, pause, two slower ones—that hadn't changed." | | 2 | "A fresh tattoo peeked from his collar—black ink, Celtic knots." | | 3 | "The cologne was different—spicier, more expensive." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 437 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.038901601830663615 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006864988558352402 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 5.29 | | std | 3.43 | | cv | 0.648 | | sampleLengths | | 0 | 11 | | 1 | 9 | | 2 | 6 | | 3 | 1 | | 4 | 9 | | 5 | 8 | | 6 | 1 | | 7 | 10 | | 8 | 16 | | 9 | 11 | | 10 | 4 | | 11 | 10 | | 12 | 2 | | 13 | 4 | | 14 | 9 | | 15 | 6 | | 16 | 1 | | 17 | 8 | | 18 | 3 | | 19 | 11 | | 20 | 5 | | 21 | 4 | | 22 | 15 | | 23 | 7 | | 24 | 5 | | 25 | 7 | | 26 | 2 | | 27 | 16 | | 28 | 5 | | 29 | 3 | | 30 | 3 | | 31 | 9 | | 32 | 3 | | 33 | 5 | | 34 | 9 | | 35 | 1 | | 36 | 14 | | 37 | 3 | | 38 | 1 | | 39 | 6 | | 40 | 4 | | 41 | 3 | | 42 | 6 | | 43 | 10 | | 44 | 3 | | 45 | 7 | | 46 | 1 | | 47 | 9 | | 48 | 1 | | 49 | 1 |
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| 94.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.5945945945945946 | | totalSentences | 111 | | uniqueOpeners | 66 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 65 | | matches | | 0 | "Of course he knew." | | 1 | "Always watch the hands." | | 2 | "Somewhere, a glass shattered." | | 3 | "Then everything happened at once." |
| | ratio | 0.062 | |
| 84.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 65 | | matches | | 0 | "She didn't move to wipe" | | 1 | "He turned on the stool," | | 2 | "His knuckles bore fresh scars," | | 3 | "He used the old name" | | 4 | "He'd filled out since Cardiff." | | 5 | "She used to tease him" | | 6 | "*You're like a broken metronome.*" | | 7 | "He swirled the fresh drink" | | 8 | "His thumb brushed the rim" | | 9 | "Her fingers found the crescent" | | 10 | "She watched his hands" | | 11 | "He stretched, rolling his shoulders" | | 12 | "His gaze flicked to Silas," | | 13 | "Her pulse jumped." | | 14 | "His jaw tightened." | | 15 | "He leaned in" | | 16 | "She studied the bottles behind" | | 17 | "He rubbed his knuckles" | | 18 | "His hand covered hers" | | 19 | "His hand vanished under his" |
| | ratio | 0.338 | |
| 13.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 65 | | matches | | 0 | "The glass slipped from Rory's" | | 1 | "Vodka splashed across the bar," | | 2 | "She didn't move to wipe" | | 3 | "He turned on the stool," | | 4 | "That same lazy smile, but" | | 5 | "The kind of hardness that" | | 6 | "His knuckles bore fresh scars," | | 7 | "He used the old name" | | 8 | "Silas appeared with a towel," | | 9 | "The Raven's Nest didn't have" | | 10 | "Silas asked, mopping the spill" | | 11 | "Evan pushed a fifty across" | | 12 | "The neon sign outside buzzed," | | 13 | "He'd filled out since Cardiff." | | 14 | "Shoulders broader, jaw sharper." | | 15 | "She used to tease him" | | 16 | "*You're like a broken metronome.*" | | 17 | "He swirled the fresh drink" | | 18 | "His thumb brushed the rim" | | 19 | "Her fingers found the crescent" |
| | ratio | 0.892 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 10 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "she observed (observe)" | | 1 | "Rory murmured (murmur)" |
| | dialogueSentences | 50 | | tagDensity | 0.06 | | leniency | 0.12 | | rawRatio | 0.667 | | effectiveRatio | 0.08 | |