| 96.55% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 3 | | adverbTags | | 0 | "he admitted quietly [quietly]" | | 1 | "He smiled wryly [wryly]" | | 2 | "Eva said coldly [coldly]" |
| | dialogueSentences | 58 | | tagDensity | 0.345 | | leniency | 0.69 | | rawRatio | 0.15 | | effectiveRatio | 0.103 | |
| 91.66% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1199 | | 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) | |
| 16.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1199 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "familiar" | | 1 | "echoing" | | 2 | "silence" | | 3 | "flicked" | | 4 | "glint" | | 5 | "weight" | | 6 | "flickered" | | 7 | "traced" | | 8 | "fractured" | | 9 | "echo" | | 10 | "shattered" | | 11 | "scanning" | | 12 | "pulse" | | 13 | "raced" | | 14 | "tension" | | 15 | "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 | 95 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 95 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1188 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 58.57% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 875 | | uniqueNames | 8 | | maxNameDensity | 1.83 | | worstName | "Lukas" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Rory | 15 | | Lukas | 16 | | Welsh | 1 | | Silas | 5 | | Eva | 5 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Lukas" | | 4 | "Silas" | | 5 | "Eva" |
| | places | | | globalScore | 0.586 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 5 | | matches | | 0 | "as if dragging half the decade behind him" | | 1 | "tasted like ash" | | 2 | "not quite meeting his" | | 3 | "as if mapping their fractured bond" | | 4 | "as though reaching to touch the pain he never noticed" |
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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 | 1188 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 129 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 70 | | mean | 16.97 | | std | 10.06 | | cv | 0.593 | | sampleLengths | | 0 | 49 | | 1 | 46 | | 2 | 25 | | 3 | 43 | | 4 | 16 | | 5 | 41 | | 6 | 17 | | 7 | 9 | | 8 | 32 | | 9 | 38 | | 10 | 25 | | 11 | 20 | | 12 | 20 | | 13 | 10 | | 14 | 9 | | 15 | 20 | | 16 | 8 | | 17 | 40 | | 18 | 13 | | 19 | 17 | | 20 | 15 | | 21 | 5 | | 22 | 14 | | 23 | 13 | | 24 | 15 | | 25 | 20 | | 26 | 5 | | 27 | 22 | | 28 | 19 | | 29 | 15 | | 30 | 18 | | 31 | 18 | | 32 | 12 | | 33 | 19 | | 34 | 17 | | 35 | 7 | | 36 | 9 | | 37 | 4 | | 38 | 26 | | 39 | 10 | | 40 | 9 | | 41 | 18 | | 42 | 12 | | 43 | 17 | | 44 | 16 | | 45 | 22 | | 46 | 7 | | 47 | 7 | | 48 | 16 | | 49 | 12 |
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| 97.88% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 95 | | matches | | 0 | "been edged" | | 1 | "was clipped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 172 | | matches | | |
| 32.12% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 129 | | ratio | 0.039 | | matches | | 0 | "And those eyes—familiar, but heavier." | | 1 | "She hadn’t expected to see Lukas here, not after the last time they’d parted—words left unsaid hanging like cobwebs between them." | | 2 | "Lukas smirked, and the old glint—half-danger, half-mischief—returned." | | 3 | "It was the weight of all they’d lost—the trust, the hope, the innocence." | | 4 | "The moment stretched fragile—a thread pulled tight between who they were and who they might yet become." |
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| 92.58% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 887 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.048478015783540024 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.012401352874859075 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 9.21 | | std | 4.76 | | cv | 0.517 | | sampleLengths | | 0 | 19 | | 1 | 15 | | 2 | 15 | | 3 | 16 | | 4 | 16 | | 5 | 14 | | 6 | 14 | | 7 | 8 | | 8 | 3 | | 9 | 8 | | 10 | 17 | | 11 | 5 | | 12 | 13 | | 13 | 16 | | 14 | 21 | | 15 | 16 | | 16 | 4 | | 17 | 17 | | 18 | 6 | | 19 | 3 | | 20 | 10 | | 21 | 16 | | 22 | 6 | | 23 | 11 | | 24 | 27 | | 25 | 11 | | 26 | 14 | | 27 | 7 | | 28 | 13 | | 29 | 11 | | 30 | 9 | | 31 | 5 | | 32 | 5 | | 33 | 3 | | 34 | 6 | | 35 | 11 | | 36 | 9 | | 37 | 5 | | 38 | 3 | | 39 | 10 | | 40 | 17 | | 41 | 13 | | 42 | 5 | | 43 | 8 | | 44 | 6 | | 45 | 11 | | 46 | 11 | | 47 | 4 | | 48 | 5 | | 49 | 5 |
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| 68.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4186046511627907 | | totalSentences | 129 | | uniqueOpeners | 54 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 92 | | matches | (empty) | | ratio | 0 | |
| 85.22% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 92 | | matches | | 0 | "he muttered under his breath," | | 1 | "Her voice was lower than" | | 2 | "He dropped his bag awkwardly" | | 3 | "She hadn’t expected to see" | | 4 | "She forced a grin, trying" | | 5 | "He gave a brief, humourless" | | 6 | "It was a lie neither" | | 7 | "His eyes flicked between them," | | 8 | "Her tone was sharper than" | | 9 | "She tapped the crescent scar" | | 10 | "she added, eyes not quite" | | 11 | "His voice dropped" | | 12 | "She remembered the reckless nights" | | 13 | "Her gaze cut through him" | | 14 | "He exhaled slowly, the years" | | 15 | "Her words fell like stones." | | 16 | "he admitted quietly" | | 17 | "He smiled wryly, the faintest" | | 18 | "she said, voice hoarse" | | 19 | "She leaned in, voice dropping." |
| | ratio | 0.337 | |
| 14.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 82 | | totalSentences | 92 | | matches | | 0 | "The door at the back" | | 1 | "Rory glanced up from the" | | 2 | "The clatter wasn’t the usual" | | 3 | "A man stood in the" | | 4 | "Silas leaned against the far" | | 5 | "he muttered under his breath," | | 6 | "Rory stiffened, heart hitching like" | | 7 | "Her voice was lower than" | | 8 | "The man’s gaze met hers," | | 9 | "He dropped his bag awkwardly" | | 10 | "She hadn’t expected to see" | | 11 | "She forced a grin, trying" | | 12 | "He gave a brief, humourless" | | 13 | "It was a lie neither" | | 14 | "Rory’s once bright and careless" | | 15 | "Lukas’s presence was an unwelcome" | | 16 | "Silas cleared his throat, setting" | | 17 | "His eyes flicked between them," | | 18 | "Rory took a sip, letting" | | 19 | "Her tone was sharper than" |
| | ratio | 0.891 | |
| 54.35% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 92 | | matches | | 0 | "Now, something had withered." |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 5 | | matches | | 0 | "he muttered, eyes fixed on the newcomer" | | 1 | "He dropped, the sound echoing like a dropped truth" | | 2 | "She forced, trying to fill the silence, but it tasted like ash" | | 3 | "she added, eyes not quite meeting his" | | 4 | "He traced, as if mapping their fractured bond" |
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| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 6 | | fancyTags | | 0 | "he muttered (mutter)" | | 1 | "she added (add)" | | 2 | "he admitted quietly (admit)" | | 3 | "she admitted (admit)" | | 4 | "Lukas whispered (whisper)" | | 5 | "Eva warned (warn)" |
| | dialogueSentences | 58 | | tagDensity | 0.155 | | leniency | 0.31 | | rawRatio | 0.667 | | effectiveRatio | 0.207 | |