| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 55 | | tagDensity | 0.345 | | leniency | 0.691 | | rawRatio | 0.053 | | effectiveRatio | 0.036 | |
| 67.45% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1229 | | totalAiIsmAdverbs | 8 | | found | | | highlights | | 0 | "slightly" | | 1 | "very" | | 2 | "softly" | | 3 | "carefully" | | 4 | "suddenly" | | 5 | "really" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 14.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1229 | | totalAiIsms | 21 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "comfortable" | | 1 | "gleaming" | | 2 | "familiar" | | 3 | "unspoken" | | 4 | "simmering" | | 5 | "tension" | | 6 | "resonance" | | 7 | "fascinating" | | 8 | "structure" | | 9 | "unwavering" | | 10 | "weight" | | 11 | "constructed" | | 12 | "complex" | | 13 | "potential" | | 14 | "unravel" | | 15 | "depths" | | 16 | "whisper" | | 17 | "flicker" | | 18 | "velvet" | | 19 | "perfect" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 98 | | matches | | |
| 84.55% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 4 | | narrationSentences | 98 | | filterMatches | (empty) | | hedgeMatches | | 0 | "managed to" | | 1 | "seemed to" | | 2 | "began to" | | 3 | "seem to" |
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| 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 | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1223 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 893 | | uniqueNames | 12 | | maxNameDensity | 0.67 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Lucien | 4 | | London | 1 | | Rory | 6 | | Friday | 1 | | Ptolemy | 2 | | Yu | 1 | | Fei | 1 | | Golden | 1 | | Empress | 1 | | Eva | 2 | | Friend | 1 | | Avaros | 2 |
| | persons | | 0 | "Lucien" | | 1 | "Rory" | | 2 | "Ptolemy" | | 3 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 7.14% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 4 | | matches | | 0 | "quite reach his amber and black eyes" | | 1 | "quite managed to shed the delivery uniform—Yu—Fei was short-staffed as usual—and she felt distinctly underdressed in faded jeans and a Golden Empress t-shirt" | | 2 | "looked like he’d walked straight out of a" | | 3 | "felt like a deliberate act, a stripping" |
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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 | 1223 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 134 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 20.73 | | std | 15.81 | | cv | 0.763 | | sampleLengths | | 0 | 63 | | 1 | 36 | | 2 | 9 | | 3 | 5 | | 4 | 9 | | 5 | 28 | | 6 | 41 | | 7 | 44 | | 8 | 33 | | 9 | 14 | | 10 | 11 | | 11 | 33 | | 12 | 17 | | 13 | 39 | | 14 | 4 | | 15 | 57 | | 16 | 3 | | 17 | 16 | | 18 | 8 | | 19 | 5 | | 20 | 21 | | 21 | 42 | | 22 | 10 | | 23 | 29 | | 24 | 5 | | 25 | 12 | | 26 | 22 | | 27 | 6 | | 28 | 11 | | 29 | 25 | | 30 | 4 | | 31 | 29 | | 32 | 11 | | 33 | 15 | | 34 | 17 | | 35 | 3 | | 36 | 35 | | 37 | 25 | | 38 | 2 | | 39 | 14 | | 40 | 19 | | 41 | 3 | | 42 | 15 | | 43 | 33 | | 44 | 6 | | 45 | 35 | | 46 | 41 | | 47 | 37 | | 48 | 12 | | 49 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 174 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 134 | | ratio | 0.007 | | matches | | 0 | "She hadn’t quite managed to shed the delivery uniform—Yu-Fei was short-staffed as usual—and she felt distinctly underdressed in faded jeans and a Golden Empress t-shirt." |
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| 78.35% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 470 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.0574468085106383 | | lyAdverbCount | 13 | | lyAdverbRatio | 0.027659574468085105 | |
| 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 | 9.13 | | std | 6.47 | | cv | 0.709 | | sampleLengths | | 0 | 8 | | 1 | 7 | | 2 | 10 | | 3 | 17 | | 4 | 21 | | 5 | 23 | | 6 | 13 | | 7 | 9 | | 8 | 2 | | 9 | 3 | | 10 | 9 | | 11 | 24 | | 12 | 4 | | 13 | 19 | | 14 | 20 | | 15 | 2 | | 16 | 7 | | 17 | 25 | | 18 | 12 | | 19 | 6 | | 20 | 23 | | 21 | 4 | | 22 | 6 | | 23 | 8 | | 24 | 6 | | 25 | 5 | | 26 | 2 | | 27 | 6 | | 28 | 25 | | 29 | 17 | | 30 | 18 | | 31 | 21 | | 32 | 4 | | 33 | 23 | | 34 | 8 | | 35 | 11 | | 36 | 9 | | 37 | 2 | | 38 | 4 | | 39 | 3 | | 40 | 16 | | 41 | 4 | | 42 | 4 | | 43 | 2 | | 44 | 3 | | 45 | 10 | | 46 | 11 | | 47 | 17 | | 48 | 19 | | 49 | 3 |
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| 69.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.43283582089552236 | | totalSentences | 134 | | uniqueOpeners | 58 | |
| 78.43% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 85 | | matches | | 0 | "Very bad news." | | 1 | "Terribly, achingly lonely." |
| | ratio | 0.024 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 50 | | totalSentences | 85 | | matches | | 0 | "She’d figured Lucien would send" | | 1 | "He was a dramatic man," | | 2 | "She hadn’t braced herself for" | | 3 | "He wasn’t smiling, but his" | | 4 | "He held his cane casually," | | 5 | "he said, the single word" | | 6 | "She hadn’t heard anything over" | | 7 | "He stepped inside, not waiting" | | 8 | "She hadn’t quite managed to" | | 9 | "He glanced at Ptolemy’s hiding" | | 10 | "He turned his gaze back" | | 11 | "She laughed, a short, brittle" | | 12 | "He rarely used her full" | | 13 | "It always felt like a" | | 14 | "she asked, her voice tight" | | 15 | "he said, and the lie" | | 16 | "Their history was built on" | | 17 | "He ignored the jab and" | | 18 | "He raised a brow." | | 19 | "She knew better than to" |
| | ratio | 0.588 | |
| 30.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 85 | | matches | | 0 | "The third deadbolt clicked, then" | | 1 | "Rory hadn’t expected him to" | | 2 | "She’d figured Lucien would send" | | 3 | "He was a dramatic man," | | 4 | "She hadn’t braced herself for" | | 5 | "He wasn’t smiling, but his" | | 6 | "He held his cane casually," | | 7 | "he said, the single word" | | 8 | "She hadn’t heard anything over" | | 9 | "He stepped inside, not waiting" | | 10 | "Ptolemy, roused from a nap" | | 11 | "Rory said, crossing her arms" | | 12 | "She hadn’t quite managed to" | | 13 | "Lucien, as always, looked like" | | 14 | "He glanced at Ptolemy’s hiding" | | 15 | "He turned his gaze back" | | 16 | "She laughed, a short, brittle" | | 17 | "The color drained from his" | | 18 | "He rarely used her full" | | 19 | "It always felt like a" |
| | ratio | 0.859 | |
| 58.82% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 85 | | matches | | 0 | "Yet, here he was, admitting" |
| | ratio | 0.012 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 4 | | matches | | 0 | "He wasn’t smiling, but his mouth tipped slightly at the corners, a habitual expression that didn’t quite reach his amber and black eyes." | | 1 | "She hadn’t heard anything over the bass thrumming from the street below, a weekly Friday night drum circle that did little for her temper." | | 2 | "Their history was built on expectations, on unspoken promises, on a simmering tension that had finally, spectacularly, imploded six months ago." | | 3 | "Eva had spent years reinforcing the flat’s defenses, layering enchantments and protective sigils into the very structure of the building." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 6 | | matches | | 0 | "she asked, her voice tight" | | 1 | "he said, and the lie hung heavy in the air between them" | | 2 | "He said, but the words carried weight" | | 3 | "His gaze met, vulnerability flickering in the amber depths of his eyes" | | 4 | "she asked, her voice barely a whisper" | | 5 | "he said, his voice suddenly rough" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 55 | | tagDensity | 0.164 | | leniency | 0.327 | | rawRatio | 0.111 | | effectiveRatio | 0.036 | |