| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said finally [finally]" | | 1 | "he said quietly [quietly]" |
| | dialogueSentences | 43 | | tagDensity | 0.256 | | leniency | 0.512 | | rawRatio | 0.182 | | effectiveRatio | 0.093 | |
| 84.23% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 951 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "carefully" | | 1 | "really" | | 2 | "slightly" |
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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) | |
| 31.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 951 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "weight" | | 1 | "familiar" | | 2 | "flicked" | | 3 | "charged" | | 4 | "pulse" | | 5 | "jaw clenched" | | 6 | "traced" | | 7 | "unspoken" | | 8 | "trembled" | | 9 | "shattered" | | 10 | "unreadable" |
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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 | 0 | | narrationSentences | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 944 | | ratio | 0.004 | | matches | | 0 | "playing" | | 1 | "Don’t look back" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 736 | | uniqueNames | 6 | | maxNameDensity | 0.54 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Rory | 4 | | Silas | 4 | | Cardiff | 1 | | Eva | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 55.66% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 2 | | matches | | 0 | "as if sensing the weight of her stare" | | 1 | "the old Silas, apparently" |
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| 94.07% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.059 | | wordCount | 944 | | matches | | 0 | "Not the easy, familiar grin she remembered, but something tighter, edged with something she couldn’t name" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 18.15 | | std | 16.14 | | cv | 0.889 | | sampleLengths | | 0 | 73 | | 1 | 6 | | 2 | 68 | | 3 | 1 | | 4 | 9 | | 5 | 43 | | 6 | 19 | | 7 | 11 | | 8 | 16 | | 9 | 22 | | 10 | 7 | | 11 | 13 | | 12 | 35 | | 13 | 10 | | 14 | 14 | | 15 | 17 | | 16 | 21 | | 17 | 14 | | 18 | 9 | | 19 | 55 | | 20 | 2 | | 21 | 10 | | 22 | 7 | | 23 | 5 | | 24 | 8 | | 25 | 10 | | 26 | 45 | | 27 | 5 | | 28 | 29 | | 29 | 16 | | 30 | 4 | | 31 | 10 | | 32 | 32 | | 33 | 8 | | 34 | 6 | | 35 | 18 | | 36 | 7 | | 37 | 32 | | 38 | 36 | | 39 | 39 | | 40 | 14 | | 41 | 11 | | 42 | 8 | | 43 | 6 | | 44 | 32 | | 45 | 5 | | 46 | 8 | | 47 | 25 | | 48 | 7 | | 49 | 8 |
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| 96.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 80 | | matches | | 0 | "was streaked" | | 1 | "been eighteen" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 129 | | matches | | |
| 39.90% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 111 | | ratio | 0.036 | | matches | | 0 | "Then the crowd parted, just for a second, and there he was—leaning against the bar, one elbow propped on the polished wood, a half-empty glass of whiskey in front of him." | | 1 | "But the set of his shoulders, the way his jaw clenched—she knew that look." | | 2 | "It was a photograph—her and Eva, arms slung around each other’s shoulders, grinning like idiots in front of the Nest." | | 3 | "The grey in his hair, the lines on his face, the way his hands—once steady and sure—now trembled just slightly around his glass." |
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| 93.78% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 743 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.047106325706594884 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010767160161507403 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 8.5 | | std | 6.26 | | cv | 0.737 | | sampleLengths | | 0 | 26 | | 1 | 23 | | 2 | 24 | | 3 | 6 | | 4 | 31 | | 5 | 19 | | 6 | 18 | | 7 | 1 | | 8 | 3 | | 9 | 6 | | 10 | 12 | | 11 | 13 | | 12 | 18 | | 13 | 3 | | 14 | 16 | | 15 | 8 | | 16 | 3 | | 17 | 8 | | 18 | 8 | | 19 | 14 | | 20 | 8 | | 21 | 2 | | 22 | 5 | | 23 | 6 | | 24 | 7 | | 25 | 7 | | 26 | 15 | | 27 | 7 | | 28 | 6 | | 29 | 5 | | 30 | 5 | | 31 | 13 | | 32 | 1 | | 33 | 5 | | 34 | 9 | | 35 | 3 | | 36 | 18 | | 37 | 3 | | 38 | 9 | | 39 | 5 | | 40 | 6 | | 41 | 3 | | 42 | 13 | | 43 | 19 | | 44 | 15 | | 45 | 5 | | 46 | 3 | | 47 | 2 | | 48 | 10 | | 49 | 2 |
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| 60.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3783783783783784 | | totalSentences | 111 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 72 | | matches | | 0 | "Then the crowd parted, just" | | 1 | "Then he smiled." | | 2 | "Instead, he signaled the bartender" | | 3 | "Somewhere in the distance, a" | | 4 | "Then she turned and walked" |
| | ratio | 0.069 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 72 | | matches | | 0 | "She didn’t see him at" | | 1 | "His auburn hair was streaked" | | 2 | "Her breath hitched." | | 3 | "He turned his head, as" | | 4 | "he said, voice rough as" | | 5 | "She set the tray down" | | 6 | "He gestured to the stool" | | 7 | "His eyebrows lifted, just a" | | 8 | "She opened her mouth, then" | | 9 | "She slid onto the stool." | | 10 | "He studied her for a" | | 11 | "She hesitated, then took it." | | 12 | "His gaze flicked to the" | | 13 | "She swirled the whiskey in" | | 14 | "He’d been the one to" | | 15 | "she asked, nodding at his" | | 16 | "His fingers tightened around his" | | 17 | "She exhaled through her nose." | | 18 | "He leaned forward, just enough" | | 19 | "Her pulse jumped." |
| | ratio | 0.569 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 72 | | matches | | 0 | "The Raven’s Nest hummed with" | | 1 | "Rory wiped her hands on" | | 2 | "The green neon sign outside" | | 3 | "She didn’t see him at" | | 4 | "His auburn hair was streaked" | | 5 | "The signet ring on his" | | 6 | "Her breath hitched." | | 7 | "The tray tilted in her" | | 8 | "He turned his head, as" | | 9 | "Hazel eyes locked onto hers," | | 10 | "The noise of the bar" | | 11 | "he said, voice rough as" | | 12 | "She set the tray down" | | 13 | "He gestured to the stool" | | 14 | "His eyebrows lifted, just a" | | 15 | "She opened her mouth, then" | | 16 | "The old Rory would’ve snapped" | | 17 | "Neither was the old Silas," | | 18 | "She slid onto the stool." | | 19 | "He studied her for a" |
| | ratio | 0.833 | |
| 69.44% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 72 | | matches | | 0 | "If she’d left too much" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 1 | | matches | | 0 | "He turned his head, as if sensing the weight of her stare." |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, voice rough as gravel" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "he agreed (agree)" | | 1 | "she admitted (admit)" |
| | dialogueSentences | 43 | | tagDensity | 0.14 | | leniency | 0.279 | | rawRatio | 0.333 | | effectiveRatio | 0.093 | |