| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said finally [finally]" |
| | dialogueSentences | 73 | | tagDensity | 0.164 | | leniency | 0.329 | | rawRatio | 0.083 | | effectiveRatio | 0.027 | |
| 89.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1965 | | totalAiIsmAdverbs | 4 | | 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) | |
| 49.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1965 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "flickered" | | 1 | "weight" | | 2 | "calibrated" | | 3 | "silence" | | 4 | "traced" | | 5 | "glint" | | 6 | "unspoken" | | 7 | "fractured" | | 8 | "flicked" | | 9 | "familiar" | | 10 | "measured" |
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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 | 151 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 151 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 213 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1952 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 28 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.55% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1438 | | uniqueNames | 10 | | maxNameDensity | 1.67 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Aurora | 1 | | Carter | 2 | | Raven | 1 | | Nest | 1 | | Docs | 1 | | Silas | 24 | | Rory | 18 | | Cardiff | 2 | | Eva | 1 | | Didn | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Carter" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Silas" | | 5 | "Rory" | | 6 | "Eva" |
| | places | | | globalScore | 0.666 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1952 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 213 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 107 | | mean | 18.24 | | std | 15.41 | | cv | 0.845 | | sampleLengths | | 0 | 64 | | 1 | 69 | | 2 | 44 | | 3 | 41 | | 4 | 12 | | 5 | 19 | | 6 | 32 | | 7 | 1 | | 8 | 43 | | 9 | 45 | | 10 | 18 | | 11 | 19 | | 12 | 16 | | 13 | 16 | | 14 | 24 | | 15 | 34 | | 16 | 6 | | 17 | 7 | | 18 | 8 | | 19 | 25 | | 20 | 24 | | 21 | 4 | | 22 | 45 | | 23 | 7 | | 24 | 13 | | 25 | 10 | | 26 | 27 | | 27 | 5 | | 28 | 8 | | 29 | 21 | | 30 | 16 | | 31 | 6 | | 32 | 5 | | 33 | 60 | | 34 | 28 | | 35 | 6 | | 36 | 2 | | 37 | 4 | | 38 | 60 | | 39 | 12 | | 40 | 24 | | 41 | 31 | | 42 | 6 | | 43 | 2 | | 44 | 12 | | 45 | 27 | | 46 | 5 | | 47 | 26 | | 48 | 3 | | 49 | 20 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 151 | | matches | | 0 | "being wasted" | | 1 | "was concerned" | | 2 | "was measured" |
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| 75.62% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 268 | | matches | | 0 | "was trying" | | 1 | "wasn’t just asking" | | 2 | "was asking" | | 3 | "was still running" | | 4 | "was already reaching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 213 | | ratio | 0.056 | | matches | | 0 | "The place hadn’t changed—same black-and-white photographs on the walls, same maps pinned behind the bar, one of them now yellowed at the edges." | | 1 | "Silas never used to joke like this—sharp, brittle humor." | | 2 | "She studied his face—the faint lines around his eyes that hadn’t been there when she knew him, the way his gaze darted to her wrist for half a second before snapping back up." | | 3 | "She could see the gears turning behind his eyes—the way his mind worked, categorizing, assessing." | | 4 | "She wanted to ask about the knee—whether it still gave him trouble, whether the limp had settled into his bones like a permanent tenant." | | 5 | "Silas had been one of the first people she’d fled from—not because he’d done anything wrong, but because he’d seen the worst of her before she could hide it." | | 6 | "The train ride over had been long—cardboard sandwiches and blurry window reflections." | | 7 | "Silas touched the fabric of his rolled-up shirt sleeve—exhibit A." | | 8 | "The use of her full name told her everything—he wasn’t just asking why she was here tonight." | | 9 | "The advantage of the MI6 training, probably—control carved into silence." | | 10 | "Rory finally looked at him, really looked—the grey in his beard, the lines bracketing his mouth, the way his eyes still missed nothing, even after all this time." | | 11 | "He reached under the counter and pulled out a business card—the kind with no name, just a number and a timestamp in the corner." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1318 | | adjectiveStacks | 1 | | stackExamples | | 0 | "existing under fluorescent lights" |
| | adverbCount | 47 | | adverbRatio | 0.03566009104704097 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.009104704097116844 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 213 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 213 | | mean | 9.16 | | std | 6.7 | | cv | 0.732 | | sampleLengths | | 0 | 25 | | 1 | 39 | | 2 | 21 | | 3 | 28 | | 4 | 5 | | 5 | 15 | | 6 | 10 | | 7 | 23 | | 8 | 11 | | 9 | 14 | | 10 | 14 | | 11 | 13 | | 12 | 12 | | 13 | 11 | | 14 | 8 | | 15 | 13 | | 16 | 17 | | 17 | 2 | | 18 | 1 | | 19 | 10 | | 20 | 9 | | 21 | 8 | | 22 | 16 | | 23 | 33 | | 24 | 12 | | 25 | 8 | | 26 | 10 | | 27 | 10 | | 28 | 9 | | 29 | 16 | | 30 | 3 | | 31 | 1 | | 32 | 6 | | 33 | 6 | | 34 | 16 | | 35 | 8 | | 36 | 4 | | 37 | 15 | | 38 | 15 | | 39 | 6 | | 40 | 7 | | 41 | 8 | | 42 | 13 | | 43 | 12 | | 44 | 19 | | 45 | 5 | | 46 | 4 | | 47 | 24 | | 48 | 21 | | 49 | 7 |
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| 45.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.2863849765258216 | | totalSentences | 213 | | uniqueOpeners | 61 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 136 | | matches | | 0 | "Instead, she said," | | 1 | "Just kept moving, kept delivering," | | 2 | "Instead, she watched a regular" | | 3 | "Then he set down his" | | 4 | "Just kept polishing." |
| | ratio | 0.037 | |
| 87.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 136 | | matches | | 0 | "His auburn hair was more" | | 1 | "He didn’t look up immediately." | | 2 | "She exhaled, watching her breath" | | 3 | "She walked forward, boots squeaking" | | 4 | "he said, setting the glass" | | 5 | "He’d been all precision before," | | 6 | "She studied his face—the faint" | | 7 | "He almost smiled." | | 8 | "His fingers stilled on the" | | 9 | "She could see the gears" | | 10 | "She used to love that" | | 11 | "She wanted to ask about" | | 12 | "She had left Cardiff abruptly," | | 13 | "She flexed her left wrist" | | 14 | "he said finally" | | 15 | "She hadn’t planned this reunion." | | 16 | "He reached under the bar" | | 17 | "She set the glass down." | | 18 | "He was asking what had" | | 19 | "She could lie." |
| | ratio | 0.331 | |
| 40.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 114 | | totalSentences | 136 | | matches | | 0 | "The greenneon sign flickered against" | | 1 | "The Raven’s Nest smelled of" | | 2 | "Silas stood behind the bar" | | 3 | "His auburn hair was more" | | 4 | "He didn’t look up immediately." | | 5 | "Rory hesitated near the entrance," | | 6 | "The place hadn’t changed—same black-and-white" | | 7 | "She exhaled, watching her breath" | | 8 | "A regular at the far" | | 9 | "The room held maybe a" | | 10 | "Silas finally looked up, his" | | 11 | "She walked forward, boots squeaking" | | 12 | "he said, setting the glass" | | 13 | "Rory stopped a few feet" | | 14 | "The leather jacket had cost" | | 15 | "A raw laugh escaped her" | | 16 | "Silas never used to joke" | | 17 | "He’d been all precision before," | | 18 | "She studied his face—the faint" | | 19 | "The scar was visible today," |
| | ratio | 0.838 | |
| 73.53% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 136 | | matches | | 0 | "Now it came across like" | | 1 | "What she was still running" |
| | ratio | 0.015 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 3 | | matches | | 0 | "Silas stood behind the bar polishing a glass with the slow precision of someone who had no patience for sloppy work." | | 1 | "Rory traced a finger along the bar’s edge, feeling the grooves worn by years of elbows and absentminded fidgeting." | | 2 | "Silas’s gaze flicked there before snapping back up, his expression tightening." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 73 | | tagDensity | 0.151 | | leniency | 0.301 | | rawRatio | 0.091 | | effectiveRatio | 0.027 | |