| 37.21% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 34 | | adverbTagCount | 7 | | adverbTags | | 0 | "she said softly [softly]" | | 1 | "Max said suddenly [suddenly]" | | 2 | "she said quickly [quickly]" | | 3 | "Max said quietly [quietly]" | | 4 | "Max observed once [once]" | | 5 | "Max said so [so]" | | 6 | "he said softly [softly]" |
| | dialogueSentences | 86 | | tagDensity | 0.395 | | leniency | 0.791 | | rawRatio | 0.206 | | effectiveRatio | 0.163 | |
| 74.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1783 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "very" | | 3 | "suddenly" | | 4 | "quickly" | | 5 | "carefully" |
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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) | |
| 46.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1783 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | word | "practiced ease" | | count | 1 |
| | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | word | "the last thing" | | count | 1 |
| | 17 | |
| | highlights | | 0 | "traced" | | 1 | "methodical" | | 2 | "weight" | | 3 | "eyebrow" | | 4 | "footsteps" | | 5 | "practiced ease" | | 6 | "flickered" | | 7 | "stomach" | | 8 | "sense of" | | 9 | "warmth" | | 10 | "tension" | | 11 | "comfortable" | | 12 | "silence" | | 13 | "otherworldly" | | 14 | "familiar" | | 15 | "pang" | | 16 | "the last thing" | | 17 | "navigating" |
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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 | 1 | | narrationSentences | 94 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 144 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1773 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 29 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1075 | | uniqueNames | 11 | | maxNameDensity | 2.14 | | worstName | "Max" | | maxWindowNameDensity | 5 | | worstWindowName | "Max" | | discoveredNames | | Raven | 4 | | Nest | 4 | | Silas | 7 | | Aurora | 18 | | London | 2 | | Maximilian | 1 | | Hughes | 1 | | Max | 23 | | Welsh | 1 | | Cardiff | 1 | | Evan | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Maximilian" | | 5 | "Hughes" | | 6 | "Max" | | 7 | "Welsh" | | 8 | "Evan" |
| | places | | | globalScore | 0.43 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like his third whiskey" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.564 | | wordCount | 1773 | | matches | | 0 | "not the one I imagined, but it's mine" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 144 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 77 | | mean | 23.03 | | std | 17.25 | | cv | 0.749 | | sampleLengths | | 0 | 78 | | 1 | 54 | | 2 | 9 | | 3 | 13 | | 4 | 12 | | 5 | 8 | | 6 | 56 | | 7 | 7 | | 8 | 3 | | 9 | 26 | | 10 | 88 | | 11 | 15 | | 12 | 11 | | 13 | 16 | | 14 | 22 | | 15 | 20 | | 16 | 35 | | 17 | 9 | | 18 | 6 | | 19 | 28 | | 20 | 37 | | 21 | 9 | | 22 | 35 | | 23 | 11 | | 24 | 17 | | 25 | 29 | | 26 | 26 | | 27 | 22 | | 28 | 31 | | 29 | 23 | | 30 | 33 | | 31 | 13 | | 32 | 7 | | 33 | 5 | | 34 | 28 | | 35 | 47 | | 36 | 6 | | 37 | 3 | | 38 | 34 | | 39 | 23 | | 40 | 11 | | 41 | 20 | | 42 | 9 | | 43 | 50 | | 44 | 20 | | 45 | 21 | | 46 | 10 | | 47 | 22 | | 48 | 16 | | 49 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 94 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 203 | | matches | | 0 | "was already looking" | | 1 | "was searching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 1 | | flaggedSentences | 9 | | totalSentences | 144 | | ratio | 0.063 | | matches | | 0 | "The usual evening crowd had thinned to a handful of patrons scattered across the bar—a couple in deep conversation at a corner table, a woman typing furiously on her laptop, and an older man nursing what looked like his third whiskey." | | 1 | "Aurora didn't look up immediately; newcomers weren't unusual, even on slow nights." | | 2 | "It was only when the figure approached the bar that something—the cadence of footsteps, perhaps—made her glance up." | | 3 | "Maximilian Hughes had been her closest friend through university—the boy with the wild ideas and wilder laugh who'd convinced her to skip lectures to see obscure bands, who'd stayed up all night helping her cram for exams she'd neglected." | | 4 | "His once shaggy blonde hair was cut short and neatly styled, but his eyes—those were still the same startling green that had always reminded her of sea glass." | | 5 | "Something flickered across his face—surprise, perhaps, that she knew what he'd been doing since university." | | 6 | "She absently rubbed the crescent-shaped scar on her left wrist—a remnant from when she'd fallen from that very shed at age twelve." | | 7 | "The mention of her hasty departure from Cardiff—from Evan—was not something she had expected." | | 8 | "There were regrets, certainly—the wasted years with Evan, the unfinished degree, the strained relationship with her parents." |
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| 81.83% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 951 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 54 | | adverbRatio | 0.056782334384858045 | | lyAdverbCount | 23 | | lyAdverbRatio | 0.024185068349106203 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 144 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 144 | | mean | 12.31 | | std | 9.39 | | cv | 0.763 | | sampleLengths | | 0 | 26 | | 1 | 11 | | 2 | 41 | | 3 | 28 | | 4 | 26 | | 5 | 9 | | 6 | 4 | | 7 | 9 | | 8 | 4 | | 9 | 8 | | 10 | 8 | | 11 | 26 | | 12 | 12 | | 13 | 18 | | 14 | 7 | | 15 | 3 | | 16 | 16 | | 17 | 10 | | 18 | 39 | | 19 | 21 | | 20 | 28 | | 21 | 15 | | 22 | 7 | | 23 | 4 | | 24 | 16 | | 25 | 10 | | 26 | 12 | | 27 | 20 | | 28 | 15 | | 29 | 10 | | 30 | 10 | | 31 | 3 | | 32 | 6 | | 33 | 6 | | 34 | 10 | | 35 | 8 | | 36 | 10 | | 37 | 25 | | 38 | 12 | | 39 | 7 | | 40 | 2 | | 41 | 35 | | 42 | 7 | | 43 | 4 | | 44 | 7 | | 45 | 10 | | 46 | 29 | | 47 | 15 | | 48 | 11 | | 49 | 15 |
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| 79.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.4930555555555556 | | totalSentences | 144 | | uniqueOpeners | 71 | |
| 38.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 87 | | matches | | 0 | "Of course her father would" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 87 | | matches | | 0 | "It was only when the" | | 1 | "He was already looking at" | | 2 | "he said, his voice deeper" | | 3 | "His once shaggy blonde hair" | | 4 | "she asked, too stunned to" | | 5 | "She nodded, unable to find" | | 6 | "he ordered, then turned to" | | 7 | "He loosened his tie slightly" | | 8 | "She took a sip of" | | 9 | "he asked, his Welsh accent" | | 10 | "They shook, and Aurora didn't" | | 11 | "She brushed her hair behind" | | 12 | "She faltered, realizing she was" | | 13 | "He swirled his drink" | | 14 | "He stared into his glass." | | 15 | "she said softly" | | 16 | "She absently rubbed the crescent-shaped" | | 17 | "He leaned closer, his voice" | | 18 | "she said quickly, too quickly" | | 19 | "she replied, not unkindly" |
| | ratio | 0.276 | |
| 28.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 87 | | matches | | 0 | "Aurora's fingers traced a lazy" | | 1 | "Tuesday nights were usually quiet," | | 2 | "The usual evening crowd had" | | 3 | "The neon green sign outside" | | 4 | "Silas asked, nodding at her" | | 5 | "Aurora shook her head." | | 6 | "Silas raised an eyebrow." | | 7 | "Aurora replied with a wry" | | 8 | "The door swung open, letting" | | 9 | "Aurora didn't look up immediately;" | | 10 | "It was only when the" | | 11 | "The glass nearly slipped from" | | 12 | "He was already looking at" | | 13 | "he said, his voice deeper" | | 14 | "Maximilian Hughes had been her" | | 15 | "The Max who stood before" | | 16 | "His once shaggy blonde hair" | | 17 | "she asked, too stunned to" | | 18 | "Max gestured to the stool" | | 19 | "She nodded, unable to find" |
| | ratio | 0.862 | |
| 57.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 87 | | matches | | 0 | "Before reality and expectations had" |
| | ratio | 0.011 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 6 | | matches | | 0 | "The door swung open, letting in a gust of London drizzle and a tall figure who paused at the threshold, shaking water from a wool overcoat." | | 1 | "Maximilian Hughes had been her closest friend through university—the boy with the wild ideas and wilder laugh who'd convinced her to skip lectures to see obscur…" | | 2 | "Silas placed Max's drink before him, his hazel eyes assessing the newcomer with the quiet scrutiny of someone who'd made a career of reading people." | | 3 | "Beneath the polished exterior, she caught glimpses of fatigue in the fine lines around his eyes, a tension in his shoulders that hadn't been there before." | | 4 | "Aurora reached out, her fingers brushing his wrist briefly before retreating." | | 5 | "Inside The Raven's Nest, beneath maps of places they'd once dreamed of visiting together and photographs of strangers who'd seen more of the world than they had…" |
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| 80.88% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 34 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, his voice deeper than she remembered" | | 1 | "He leaned, his voice dropping" | | 2 | "she replied, not unkindly" |
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| 68.60% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 22 | | fancyCount | 7 | | fancyTags | | 0 | "she breathed (breathe)" | | 1 | "he ordered (order)" | | 2 | "Max laughed (laugh)" | | 3 | "She faltered (falter)" | | 4 | "she admitted (admit)" | | 5 | "Max observed once (observe)" | | 6 | "she admitted (admit)" |
| | dialogueSentences | 86 | | tagDensity | 0.256 | | leniency | 0.512 | | rawRatio | 0.318 | | effectiveRatio | 0.163 | |