| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "He drank anyway [anyway]" |
| | dialogueSentences | 47 | | tagDensity | 0.404 | | leniency | 0.809 | | rawRatio | 0.053 | | effectiveRatio | 0.043 | |
| 96.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1464 | | 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) | |
| 31.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1464 | | totalAiIsms | 20 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "scanning" | | 1 | "tinged" | | 2 | "eyebrow" | | 3 | "traced" | | 4 | "reminder" | | 5 | "flicked" | | 6 | "echoing" | | 7 | "sentinel" | | 8 | "echoed" | | 9 | "whisper" | | 10 | "flicker" | | 11 | "glinting" | | 12 | "jaw clenched" | | 13 | "weight" | | 14 | "tension" | | 15 | "flickered" | | 16 | "echo" | | 17 | "unspoken" | | 18 | "resolved" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "jaw clenched" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 75 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1462 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 949 | | uniqueNames | 3 | | maxNameDensity | 1.16 | | worstName | "Liam" | | maxWindowNameDensity | 3 | | worstWindowName | "Liam" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.92 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.684 | | wordCount | 1462 | | matches | | 0 | "not sure what’s coming, but I know there’s no turning back now" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 71.13% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 31.78 | | std | 12.68 | | cv | 0.399 | | sampleLengths | | 0 | 38 | | 1 | 32 | | 2 | 13 | | 3 | 31 | | 4 | 22 | | 5 | 48 | | 6 | 38 | | 7 | 27 | | 8 | 35 | | 9 | 56 | | 10 | 28 | | 11 | 38 | | 12 | 17 | | 13 | 35 | | 14 | 14 | | 15 | 45 | | 16 | 21 | | 17 | 40 | | 18 | 29 | | 19 | 26 | | 20 | 26 | | 21 | 44 | | 22 | 30 | | 23 | 24 | | 24 | 44 | | 25 | 21 | | 26 | 40 | | 27 | 30 | | 28 | 33 | | 29 | 9 | | 30 | 52 | | 31 | 46 | | 32 | 9 | | 33 | 42 | | 34 | 10 | | 35 | 26 | | 36 | 47 | | 37 | 11 | | 38 | 21 | | 39 | 51 | | 40 | 34 | | 41 | 41 | | 42 | 21 | | 43 | 19 | | 44 | 53 | | 45 | 45 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 75 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 158 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 104 | | ratio | 0.01 | | matches | | 0 | "“I’m a barrister now. Got my own chambers on Old Street. The work’s… demanding.” He brushed a finger over his signet ring, the one he wore on the left hand now; “My old one got sold in a charity auction after the case went sideways.”" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 816 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.0196078431372549 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004901960784313725 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 14.06 | | std | 7.74 | | cv | 0.551 | | sampleLengths | | 0 | 20 | | 1 | 18 | | 2 | 17 | | 3 | 15 | | 4 | 7 | | 5 | 6 | | 6 | 9 | | 7 | 22 | | 8 | 6 | | 9 | 13 | | 10 | 3 | | 11 | 12 | | 12 | 26 | | 13 | 10 | | 14 | 14 | | 15 | 21 | | 16 | 3 | | 17 | 16 | | 18 | 11 | | 19 | 16 | | 20 | 12 | | 21 | 7 | | 22 | 11 | | 23 | 45 | | 24 | 3 | | 25 | 11 | | 26 | 14 | | 27 | 7 | | 28 | 17 | | 29 | 14 | | 30 | 4 | | 31 | 13 | | 32 | 6 | | 33 | 29 | | 34 | 5 | | 35 | 9 | | 36 | 14 | | 37 | 31 | | 38 | 11 | | 39 | 10 | | 40 | 12 | | 41 | 17 | | 42 | 8 | | 43 | 3 | | 44 | 15 | | 45 | 14 | | 46 | 2 | | 47 | 20 | | 48 | 4 | | 49 | 14 |
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| 45.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.2980769230769231 | | totalSentences | 104 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 72 | | matches | (empty) | | ratio | 0 | |
| 70.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 72 | | matches | | 0 | "He glanced up, his hazel" | | 1 | "he said, voice low and" | | 2 | "She lifted the crate, hands" | | 3 | "He turned, his eyes bright" | | 4 | "Her breath caught, the scar" | | 5 | "she stopped, hand hovering over" | | 6 | "He pulled off his coat," | | 7 | "He lifted a glass from" | | 8 | "She let the crate rest" | | 9 | "He brushed a finger over" | | 10 | "She set the crate down" | | 11 | "He set his glass down" | | 12 | "He leaned forward, elbows resting" | | 13 | "She smirked, a half‑smile that" | | 14 | "He placed a hand on" | | 15 | "He poured a measure of" | | 16 | "He drank anyway" | | 17 | "His fingers tightened around the" | | 18 | "He turned his gaze to" | | 19 | "He slipped it into a" |
| | ratio | 0.375 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 72 | | matches | | 0 | "The bell clanged and a" | | 1 | "Aurora froze, the delivery crate" | | 2 | "Silas stood behind the bar," | | 3 | "He glanced up, his hazel" | | 4 | "he said, voice low and" | | 5 | "She lifted the crate, hands" | | 6 | "A laugh cracked from the" | | 7 | "He turned, his eyes bright" | | 8 | "Her breath caught, the scar" | | 9 | "Liam had been the only" | | 10 | "she stopped, hand hovering over" | | 11 | "He pulled off his coat," | | 12 | "He lifted a glass from" | | 13 | "She let the crate rest" | | 14 | "Silas set a glass down," | | 15 | "Silas murmured, his tone dry" | | 16 | "Liam chuckled, a sound that" | | 17 | "He brushed a finger over" | | 18 | "Aurora’s mouth twitched." | | 19 | "She set the crate down" |
| | ratio | 0.986 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 72 | | matches | (empty) | | ratio | 0 | |
| 59.80% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 5 | | matches | | 0 | "Silas stood behind the bar, polishing the same mahogany tap as if it might hide a secret." | | 1 | "He pulled off his coat, revealing a charcoal suit that had seen better tailoring." | | 2 | "She smirked, a half‑smile that caught the edge of her teeth." | | 3 | "Liam picked up the glass, examined it as if it were a lab specimen." | | 4 | "The door behind her shuddered open, a sliver of light breaking into the darkness, and a figure stepped out, clutching a briefcase that seemed too heavy for the …" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 6 | | matches | | 0 | "he said, voice low and steady" | | 1 | "He lifted, eyes scanning the copper‑tinged walls" | | 2 | "Silas murmured, his tone dry" | | 3 | "Aurora asked, voice dropping to a whisper" | | 4 | "the shadows demanded, the tone clipped and hard" | | 5 | "he asked, voice dropping to a lower register" |
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| 86.17% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "Silas murmured (murmur)" | | 1 | "the shadows demanded (demand)" | | 2 | "She whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.17 | | leniency | 0.34 | | rawRatio | 0.375 | | effectiveRatio | 0.128 | |