| 49.06% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 4 | | adverbTags | | 0 | "Aurora said finally [finally]" | | 1 | "Eva said quietly [quietly]" | | 2 | "she said again [again]" | | 3 | "Eva said slowly [slowly]" |
| | dialogueSentences | 53 | | tagDensity | 0.396 | | leniency | 0.792 | | rawRatio | 0.19 | | effectiveRatio | 0.151 | |
| 82.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1132 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "quickly" | | 2 | "slowly" |
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| 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) | |
| 60.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1132 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "calculating" | | 1 | "weight" | | 2 | "silence" | | 3 | "glinting" | | 4 | "flicker" | | 5 | "echoed" | | 6 | "jaw clenched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 66 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 66 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 4 | | totalWords | 1128 | | ratio | 0.004 | | matches | | 0 | "there" | | 1 | "An accident" | | 2 | "saw" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 722 | | uniqueNames | 5 | | maxNameDensity | 3.05 | | worstName | "Eva" | | maxWindowNameDensity | 5 | | worstWindowName | "Aurora" | | discoveredNames | | Silas | 3 | | Nest | 2 | | Cardiff | 2 | | Eva | 22 | | Aurora | 20 |
| | persons | | 0 | "Silas" | | 1 | "Nest" | | 2 | "Eva" | | 3 | "Aurora" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 90.48% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 1 | | matches | | 0 | "as if carrying something heavier than the weight of twenty-five years" |
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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 | 1128 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 22.56 | | std | 15.84 | | cv | 0.702 | | sampleLengths | | 0 | 60 | | 1 | 79 | | 2 | 16 | | 3 | 20 | | 4 | 28 | | 5 | 19 | | 6 | 18 | | 7 | 9 | | 8 | 42 | | 9 | 12 | | 10 | 26 | | 11 | 33 | | 12 | 16 | | 13 | 6 | | 14 | 36 | | 15 | 12 | | 16 | 16 | | 17 | 29 | | 18 | 8 | | 19 | 6 | | 20 | 14 | | 21 | 22 | | 22 | 15 | | 23 | 24 | | 24 | 33 | | 25 | 9 | | 26 | 11 | | 27 | 36 | | 28 | 59 | | 29 | 5 | | 30 | 20 | | 31 | 2 | | 32 | 22 | | 33 | 38 | | 34 | 10 | | 35 | 33 | | 36 | 7 | | 37 | 23 | | 38 | 15 | | 39 | 10 | | 40 | 41 | | 41 | 5 | | 42 | 3 | | 43 | 30 | | 44 | 13 | | 45 | 40 | | 46 | 13 | | 47 | 41 | | 48 | 12 | | 49 | 31 |
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| 89.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 66 | | matches | | 0 | "was streaked" | | 1 | "been seventeen" | | 2 | "were meant" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 134 | | matches | | |
| 23.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 96 | | ratio | 0.042 | | matches | | 0 | "Eva stood in the doorway, framed by the green neon of the Nest, but it was the way she moved—like a cat testing the edge of a roof—the way she’d always moved when they were kids, running through the streets of Cardiff with scraped knees and dreams too big for their small town." | | 1 | "Silas grunted, but there was a flicker in his eye—recognition, maybe, or the ghost of the man he used to be before the Nest became a refuge for lost souls and quieter regrets." | | 2 | "Aurora looked at her reflection in the bar’s mirrored back wall—same bright blue eyes, same scar, same face that had aged too fast in the shadows." | | 3 | "Eva nodded, and for a moment, Aurora saw the girl she’d once been—the girl who believed in forever, in promises, in the unbreakable thread between them." |
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| 89.87% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 349 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.05157593123209169 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.008595988538681949 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 11.75 | | std | 8.79 | | cv | 0.748 | | sampleLengths | | 0 | 20 | | 1 | 30 | | 2 | 10 | | 3 | 53 | | 4 | 26 | | 5 | 13 | | 6 | 3 | | 7 | 14 | | 8 | 6 | | 9 | 12 | | 10 | 16 | | 11 | 6 | | 12 | 13 | | 13 | 15 | | 14 | 3 | | 15 | 9 | | 16 | 21 | | 17 | 21 | | 18 | 7 | | 19 | 5 | | 20 | 13 | | 21 | 13 | | 22 | 33 | | 23 | 16 | | 24 | 6 | | 25 | 19 | | 26 | 17 | | 27 | 7 | | 28 | 5 | | 29 | 7 | | 30 | 9 | | 31 | 8 | | 32 | 2 | | 33 | 3 | | 34 | 16 | | 35 | 8 | | 36 | 4 | | 37 | 2 | | 38 | 7 | | 39 | 7 | | 40 | 6 | | 41 | 16 | | 42 | 3 | | 43 | 4 | | 44 | 8 | | 45 | 20 | | 46 | 4 | | 47 | 7 | | 48 | 26 | | 49 | 6 |
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| 50.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3645833333333333 | | totalSentences | 96 | | uniqueOpeners | 35 | |
| 57.47% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 58 | | matches | | 0 | "Only now Eva’s hair was" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 58 | | matches | | 0 | "she said, the name tumbling" | | 1 | "he said, nodding at Eva" | | 2 | "He shuffled past them, leaving" | | 3 | "They both knew what they" | | 4 | "Her voice cracked slightly." | | 5 | "They stared at each other" | | 6 | "She’d been seventeen, scared, confused," | | 7 | "She’d stayed until she couldn’t" | | 8 | "she said again, the words" | | 9 | "She thought about the rooftop," | | 10 | "she said at last" |
| | ratio | 0.19 | |
| 11.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 58 | | matches | | 0 | "The amber glow from the" | | 1 | "Aurora wiped it down with" | | 2 | "The bell above the door" | | 3 | "Eva stood in the doorway," | | 4 | "she said, the name tumbling" | | 5 | "Aurora set the glass down" | | 6 | "Eva stepped inside, her heels" | | 7 | "Aurora’s fingers tightened around the" | | 8 | "Eva ran a hand through" | | 9 | "The silence stretched, punctuated only" | | 10 | "Silas emerged from the back," | | 11 | "he said, nodding at Eva" | | 12 | "Eva’s voice was softer now," | | 13 | "Silas grunted, but there was" | | 14 | "He shuffled past them, leaving" | | 15 | "Aurora said finally" | | 16 | "Eva corrected, She shifted her" | | 17 | "Aurora laughed, but it came" | | 18 | "They both knew what they" | | 19 | "The hospital bed." |
| | ratio | 0.897 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 2 | | matches | | 0 | "Only now Eva’s hair was streaked with silver at the temples, her shoulders hunched slightly, as if carrying something heavier than the weight of twenty-five yea…" | | 1 | "Aurora looked at her reflection in the bar’s mirrored back wall—same bright blue eyes, same scar, same face that had aged too fast in the shadows." |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 3 | | matches | | 0 | "she said, the name tumbling out like a stone skipping across water" | | 1 | "Eva stepped, her heels clicking against the worn wooden floor" | | 2 | "Aurora stood, her chair scraping against the floor" |
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| 93.40% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 3 | | fancyTags | | 0 | "Eva corrected (correct)" | | 1 | "Aurora whispered (whisper)" | | 2 | "Eva repeated (repeat)" |
| | dialogueSentences | 53 | | tagDensity | 0.226 | | leniency | 0.453 | | rawRatio | 0.25 | | effectiveRatio | 0.113 | |