| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 87.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1233 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "completely" | | 2 | "loosely" |
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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) | |
| 18.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1233 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "flickered" | | 1 | "rhythmic" | | 2 | "sanctuary" | | 3 | "scanned" | | 4 | "weight" | | 5 | "electric" | | 6 | "navigate" | | 7 | "footsteps" | | 8 | "etched" | | 9 | "reminder" | | 10 | "silence" | | 11 | "tracing" | | 12 | "resolve" | | 13 | "familiar" | | 14 | "comfortable" | | 15 | "sturdy" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 87 | | matches | | |
| 77.18% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1224 | | ratio | 0 | | matches | (empty) | |
| 28.85% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 5 | | matches | | 0 | "Rory, he said." | | 1 | "You look well, Evan, she said, her voice a low, steady cadence that surprised even her." | | 2 | "I lied to Eva, she said, sliding into the booth." | | 3 | "I spent months looking for you, Evan said, his gaze fixed on the amber liquid in his glass." | | 4 | "I hope not, she said." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1224 | | uniqueNames | 14 | | maxNameDensity | 0.74 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "You" | | discoveredNames | | London | 3 | | Soho | 2 | | Raven | 1 | | Nest | 1 | | Aurora | 1 | | Carter | 1 | | Prague | 1 | | Atlantic | 1 | | Evan | 6 | | Cardiff | 3 | | Eva | 2 | | Rory | 9 | | Silas | 4 | | You | 5 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Evan" | | 3 | "Eva" | | 4 | "Rory" | | 5 | "Silas" | | 6 | "You" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Raven" | | 3 | "Prague" | | 4 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a canyon etched with the debr" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.817 | | wordCount | 1224 | | matches | | 0 | "not by the law or by logic, but by the undeniable fact" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 87 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 42.21 | | std | 23.94 | | cv | 0.567 | | sampleLengths | | 0 | 76 | | 1 | 84 | | 2 | 38 | | 3 | 4 | | 4 | 50 | | 5 | 63 | | 6 | 60 | | 7 | 17 | | 8 | 49 | | 9 | 16 | | 10 | 29 | | 11 | 33 | | 12 | 64 | | 13 | 37 | | 14 | 45 | | 15 | 25 | | 16 | 60 | | 17 | 73 | | 18 | 32 | | 19 | 37 | | 20 | 54 | | 21 | 91 | | 22 | 44 | | 23 | 4 | | 24 | 37 | | 25 | 7 | | 26 | 23 | | 27 | 5 | | 28 | 67 |
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| 93.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 87 | | matches | | 0 | "was seated" | | 1 | "was terrified" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 220 | | matches | | 0 | "was polishing" | | 1 | "was constantly measuring" | | 2 | "was waiting" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 2 | | flaggedSentences | 9 | | totalSentences | 87 | | ratio | 0.103 | | matches | | 0 | "Rory moved toward the far end of the bar, pulling her jacket tight to hide the thin crescent scar on her left wrist—a habit born of a time when she’d felt the world was constantly measuring her vulnerability." | | 1 | "At first, she only saw the profile—the sharp line of a jaw she hadn’t seen in three years, the way the light caught the hair she remembered being lighter, messier." | | 2 | "She felt the cool, detached analytical side of her brain snap into place—the part of her that remembered how to navigate law school debates and tense domestic standoffs." | | 3 | "He didn't ask if they wanted it; he simply set the glass down in front of each, his hazel eyes locking briefly with Rory’s." | | 4 | "He didn’t stay, but the squeeze of his hand on her shoulder—firm, grounding—was a silent reminder of whose territory she occupied." | | 5 | "The blue of her eyes had always unnerved him, he’d said once—too clear, too capable of seeing through his justifications." | | 6 | "He leaned forward, his hands flat on the table, and for a terrifying second, she felt the old reflex—the urge to bridge the gap, to soothe, to explain her existence in a way that made him comfortable." | | 7 | "The weight of the three years—the cold, the late nights, the fear of turning a corner and seeing him—dissipated." | | 8 | "It wasn't that the memory was gone; it was that it no longer held the power to define her." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1236 | | adjectiveStacks | 1 | | stackExamples | | 0 | "persistent, needle-thin drizzle" |
| | adverbCount | 38 | | adverbRatio | 0.030744336569579287 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.011326860841423949 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 14.07 | | std | 9.35 | | cv | 0.665 | | sampleLengths | | 0 | 20 | | 1 | 32 | | 2 | 24 | | 3 | 22 | | 4 | 13 | | 5 | 18 | | 6 | 31 | | 7 | 38 | | 8 | 4 | | 9 | 19 | | 10 | 30 | | 11 | 1 | | 12 | 9 | | 13 | 16 | | 14 | 12 | | 15 | 26 | | 16 | 9 | | 17 | 23 | | 18 | 28 | | 19 | 3 | | 20 | 14 | | 21 | 28 | | 22 | 3 | | 23 | 7 | | 24 | 11 | | 25 | 16 | | 26 | 9 | | 27 | 6 | | 28 | 14 | | 29 | 10 | | 30 | 16 | | 31 | 4 | | 32 | 3 | | 33 | 19 | | 34 | 24 | | 35 | 21 | | 36 | 37 | | 37 | 18 | | 38 | 13 | | 39 | 14 | | 40 | 1 | | 41 | 2 | | 42 | 5 | | 43 | 17 | | 44 | 7 | | 45 | 20 | | 46 | 13 | | 47 | 8 | | 48 | 12 | | 49 | 5 |
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| 32.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.26436781609195403 | | totalSentences | 87 | | uniqueOpeners | 23 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Then she saw him." | | 1 | "Perhaps it was the silence" |
| | ratio | 0.024 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 82 | | matches | | 0 | "She pushed the heavy oak" | | 1 | "It had been a long" | | 2 | "She scanned the room, her" | | 3 | "He was polishing a glass" | | 4 | "He was seated in a" | | 5 | "She tightened her grip on" | | 6 | "She hadn’t expected him to" | | 7 | "He turned, perhaps sensing the" | | 8 | "He stood up slowly, looking" | | 9 | "She felt the cool, detached" | | 10 | "She didn’t run." | | 11 | "She didn’t retreat to the" | | 12 | "She walked toward him, her" | | 13 | "You look well, Evan, she" | | 14 | "He gestured to the empty" | | 15 | "I didn’t think you’d be" | | 16 | "I lied to Eva, she" | | 17 | "I moved to London." | | 18 | "I live upstairs." | | 19 | "He didn't ask if they" |
| | ratio | 0.634 | |
| 14.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 82 | | matches | | 0 | "The London rain was a" | | 1 | "She pushed the heavy oak" | | 2 | "It had been a long" | | 3 | "She scanned the room, her" | | 4 | "Silas was behind the bar," | | 5 | "He was polishing a glass" | | 6 | "Rory moved toward the far" | | 7 | "He was seated in a" | | 8 | "The breath hitched in her" | | 9 | "The room seemed to expand," | | 10 | "She tightened her grip on" | | 11 | "She hadn’t expected him to" | | 12 | "He turned, perhaps sensing the" | | 13 | "He stood up slowly, looking" | | 14 | "Rory, he said." | | 15 | "The name fell from his" | | 16 | "She felt the cool, detached" | | 17 | "She didn’t run." | | 18 | "She didn’t retreat to the" | | 19 | "She walked toward him, her" |
| | ratio | 0.89 | |
| 60.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 82 | | matches | | | ratio | 0.012 | |
| 44.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 7 | | matches | | 0 | "The London rain was a persistent, needle-thin drizzle that glazed the pavement of Soho in a slick of oily neon." | | 1 | "He was polishing a glass with slow, deliberate motions, his movements hampered by the slight, rhythmic hitch in his gait that spoke of the ruinous knee he’d lef…" | | 2 | "For a heartbeat, the recognition was mutual, a sharp, electric shock that pinned them to the space between the bar and the booth." | | 3 | "He stood up slowly, looking older, his suit sharper, his eyes lacking that frantic, charming edge that had once convinced her she was the center of his universe…" | | 4 | "She felt the cool, detached analytical side of her brain snap into place—the part of her that remembered how to navigate law school debates and tense domestic s…" | | 5 | "He leaned forward, his hands flat on the table, and for a terrifying second, she felt the old reflex—the urge to bridge the gap, to soothe, to explain her exist…" | | 6 | "Silas was waiting, his hand hovering near the edge of the bar, ready to intercede, but Rory simply nodded once, a gesture of thanks for the space he had provide…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |