| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1105 | | 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) | |
| 59.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1105 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "beacon" | | 1 | "navigating" | | 2 | "flicker" | | 3 | "crystal" | | 4 | "chill" | | 5 | "weight" | | 6 | "scanned" | | 7 | "traced" | | 8 | "silence" |
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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 | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 81 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1098 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 15 | | wordCount | 882 | | uniqueNames | 10 | | maxNameDensity | 0.45 | | worstName | "Silas" | | maxWindowNameDensity | 1 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | London | 1 | | Carter | 1 | | Silas | 4 | | Blackwood | 1 | | Berlin | 1 | | Prague | 1 | | Barcelona | 1 | | English | 1 | | Rory | 3 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Silas" | | 3 | "Blackwood" | | 4 | "Rory" |
| | places | | 0 | "London" | | 1 | "Berlin" | | 2 | "Prague" | | 3 | "Barcelona" |
| | globalScore | 1 | | windowScore | 1 | |
| 57.41% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like it belonged to another person" | | 1 | "looked like a catalogue of damage" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.911 | | wordCount | 1098 | | matches | | 0 | "Not to forget, but to endure" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 28.15 | | std | 27.1 | | cv | 0.962 | | sampleLengths | | 0 | 77 | | 1 | 73 | | 2 | 17 | | 3 | 81 | | 4 | 34 | | 5 | 2 | | 6 | 2 | | 7 | 68 | | 8 | 54 | | 9 | 4 | | 10 | 10 | | 11 | 32 | | 12 | 9 | | 13 | 28 | | 14 | 3 | | 15 | 69 | | 16 | 7 | | 17 | 16 | | 18 | 2 | | 19 | 11 | | 20 | 11 | | 21 | 69 | | 22 | 4 | | 23 | 6 | | 24 | 5 | | 25 | 18 | | 26 | 13 | | 27 | 82 | | 28 | 9 | | 29 | 4 | | 30 | 18 | | 31 | 27 | | 32 | 3 | | 33 | 12 | | 34 | 56 | | 35 | 23 | | 36 | 12 | | 37 | 54 | | 38 | 73 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 81 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 126 | | matches | | 0 | "was arguing" | | 1 | "was looking" | | 2 | "wasn’t judging" | | 3 | "were searching" | | 4 | "was beading" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 110 | | ratio | 0 | | matches | (empty) | |
| 97.90% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 283 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 12 | | adverbRatio | 0.04240282685512368 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.014134275618374558 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 9.98 | | std | 7.64 | | cv | 0.765 | | sampleLengths | | 0 | 19 | | 1 | 30 | | 2 | 12 | | 3 | 16 | | 4 | 5 | | 5 | 17 | | 6 | 20 | | 7 | 5 | | 8 | 10 | | 9 | 12 | | 10 | 4 | | 11 | 17 | | 12 | 22 | | 13 | 8 | | 14 | 19 | | 15 | 32 | | 16 | 19 | | 17 | 8 | | 18 | 2 | | 19 | 5 | | 20 | 2 | | 21 | 2 | | 22 | 10 | | 23 | 20 | | 24 | 8 | | 25 | 20 | | 26 | 10 | | 27 | 13 | | 28 | 20 | | 29 | 21 | | 30 | 4 | | 31 | 10 | | 32 | 12 | | 33 | 10 | | 34 | 10 | | 35 | 4 | | 36 | 5 | | 37 | 9 | | 38 | 15 | | 39 | 4 | | 40 | 3 | | 41 | 3 | | 42 | 19 | | 43 | 5 | | 44 | 8 | | 45 | 5 | | 46 | 20 | | 47 | 9 | | 48 | 7 | | 49 | 3 |
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| 46.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.36363636363636365 | | totalSentences | 110 | | uniqueOpeners | 40 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 75 | | matches | | 0 | "Then he turned, his hazel" | | 1 | "Just a calm, steady appraisal." | | 2 | "Of course, he saw it." | | 3 | "Just buried under a few" | | 4 | "Maybe I belong here after" |
| | ratio | 0.067 | |
| 28.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 75 | | matches | | 0 | "She shook the water from" | | 1 | "His movements were precise, economical." | | 2 | "He didn’t look up, but" | | 3 | "He was always aware." | | 4 | "She didn’t speak immediately, just" | | 5 | "He finished with the glass," | | 6 | "He nodded once, a flicker" | | 7 | "He reached under the bar" | | 8 | "He didn’t need to ask" | | 9 | "He placed a heavy crystal" | | 10 | "She looked down at her" | | 11 | "He leaned against the back" | | 12 | "His silver signet ring glinted" | | 13 | "She didn’t answer." | | 14 | "Her gaze drifted to the" | | 15 | "She used to love looking" | | 16 | "He was arguing a case." | | 17 | "He wasn’t just seeing the" | | 18 | "He was looking for the" | | 19 | "I haven’t seen *you*." |
| | ratio | 0.48 | |
| 53.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 75 | | matches | | 0 | "The green neon of the" | | 1 | "Aurora Carter pushed through the" | | 2 | "She shook the water from" | | 3 | "A long day of navigating" | | 4 | "The bar was mostly empty." | | 5 | "A couple huddled in a" | | 6 | "His movements were precise, economical." | | 7 | "Each circle of the cloth" | | 8 | "He didn’t look up, but" | | 9 | "He was always aware." | | 10 | "The bell above the door" | | 11 | "Rory slid onto a stool" | | 12 | "She didn’t speak immediately, just" | | 13 | "The grey in his auburn" | | 14 | "The slight limp in his" | | 15 | "He finished with the glass," | | 16 | "He nodded once, a flicker" | | 17 | "He reached under the bar" | | 18 | "He didn’t need to ask" | | 19 | "He placed a heavy crystal" |
| | ratio | 0.813 | |
| 66.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 75 | | matches | | 0 | "Now they just looked like" |
| | ratio | 0.013 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 4 | | matches | | 0 | "She looked down at her left wrist, at the small, white crescent scar that stood out against her flushed skin." | | 1 | "He was looking for the girl who used to sit on that very stool, debating constitutional law and the finer points of classic cinema." | | 2 | "The girl who had a whole life mapped out, a bright, clean line stretching into a future he could almost see." | | 3 | "He had seen his own share of things that were over, his own past mapped out in the lines on his face and the ache in his knee." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |