| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said quietly [quietly]" |
| | dialogueSentences | 45 | | tagDensity | 0.178 | | leniency | 0.356 | | rawRatio | 0.125 | | effectiveRatio | 0.044 | |
| 90.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1080 | | totalAiIsmAdverbs | 2 | | 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) | |
| 44.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1080 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "chill" | | 1 | "flicked" | | 2 | "pulse" | | 3 | "stomach" | | 4 | "flicker" | | 5 | "glinting" | | 6 | "echoed" | | 7 | "weight" | | 8 | "footsteps" | | 9 | "could feel" |
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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 | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 109 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 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 | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1075 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 905 | | uniqueNames | 7 | | maxNameDensity | 1.44 | | worstName | "Evan" | | maxWindowNameDensity | 3 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 2 | | Nest | 2 | | London | 1 | | Rory | 12 | | Evan | 13 | | Silas | 9 | | Wanted | 3 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Evan" | | 4 | "Silas" |
| | places | | | globalScore | 0.782 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | 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 | 1075 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 144 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 17.34 | | std | 14.77 | | cv | 0.852 | | sampleLengths | | 0 | 77 | | 1 | 37 | | 2 | 8 | | 3 | 15 | | 4 | 17 | | 5 | 39 | | 6 | 21 | | 7 | 35 | | 8 | 8 | | 9 | 20 | | 10 | 57 | | 11 | 6 | | 12 | 41 | | 13 | 13 | | 14 | 15 | | 15 | 5 | | 16 | 8 | | 17 | 3 | | 18 | 28 | | 19 | 14 | | 20 | 19 | | 21 | 11 | | 22 | 31 | | 23 | 4 | | 24 | 9 | | 25 | 22 | | 26 | 8 | | 27 | 9 | | 28 | 20 | | 29 | 6 | | 30 | 12 | | 31 | 3 | | 32 | 38 | | 33 | 5 | | 34 | 19 | | 35 | 6 | | 36 | 20 | | 37 | 9 | | 38 | 9 | | 39 | 12 | | 40 | 10 | | 41 | 35 | | 42 | 5 | | 43 | 25 | | 44 | 3 | | 45 | 42 | | 46 | 1 | | 47 | 4 | | 48 | 25 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 169 | | matches | | 0 | "was fighting" | | 1 | "weren’t saying" |
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| 83.33% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 144 | | ratio | 0.021 | | matches | | 0 | "She hadn’t expected the place to be so quiet—just a handful of regulars nursing drinks in the corners, the low hum of conversation barely rising above the clink of glass." | | 1 | "A gust of cold air rushed in, carrying with it the scent of rain and something else—expensive cologne, maybe, or just the ghost of old memories." | | 2 | "The years had carved lines into his face—sharper jaw, deeper shadows under his eyes." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 910 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.038461538461538464 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01098901098901099 | |
| 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 | 7.47 | | std | 5.77 | | cv | 0.774 | | sampleLengths | | 0 | 10 | | 1 | 18 | | 2 | 30 | | 3 | 19 | | 4 | 12 | | 5 | 16 | | 6 | 9 | | 7 | 8 | | 8 | 5 | | 9 | 10 | | 10 | 10 | | 11 | 7 | | 12 | 13 | | 13 | 26 | | 14 | 10 | | 15 | 11 | | 16 | 9 | | 17 | 4 | | 18 | 22 | | 19 | 5 | | 20 | 3 | | 21 | 1 | | 22 | 10 | | 23 | 9 | | 24 | 10 | | 25 | 14 | | 26 | 16 | | 27 | 6 | | 28 | 11 | | 29 | 6 | | 30 | 3 | | 31 | 4 | | 32 | 34 | | 33 | 13 | | 34 | 3 | | 35 | 1 | | 36 | 11 | | 37 | 4 | | 38 | 1 | | 39 | 6 | | 40 | 2 | | 41 | 2 | | 42 | 1 | | 43 | 9 | | 44 | 14 | | 45 | 5 | | 46 | 9 | | 47 | 5 | | 48 | 15 | | 49 | 4 |
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| 52.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3333333333333333 | | totalSentences | 144 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 93 | | matches | | 0 | "Then his gaze landed on" | | 1 | "Just for a second." | | 2 | "Just long enough for Rory" | | 3 | "Instead, she lifted her glass" | | 4 | "Just for a beat." | | 5 | "Then, finally, he nodded." |
| | ratio | 0.065 | |
| 95.27% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 93 | | matches | | 0 | "She hadn’t expected the place" | | 1 | "She slid onto a stool," | | 2 | "His hazel eyes flicked over" | | 3 | "She opened her mouth to" | | 4 | "She knew that voice." | | 5 | "She turned slowly, her pulse" | | 6 | "He stood in the doorway," | | 7 | "His hair, once dark and" | | 8 | "he said, and her name" | | 9 | "She didn’t answer." | | 10 | "He slid them across the" | | 11 | "She wanted to laugh." | | 12 | "She set her glass down," | | 13 | "She stood abruptly, her stool" | | 14 | "She ignored him, grabbing her" | | 15 | "He just stood there, his" | | 16 | "he said quietly" | | 17 | "She turned, her coat clutched" | | 18 | "She laughed, sharp and bitter." | | 19 | "He stepped closer, his voice" |
| | ratio | 0.312 | |
| 51.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 93 | | matches | | 0 | "The Raven’s Nest smelled of" | | 1 | "Rory wiped her hands on" | | 2 | "She hadn’t expected the place" | | 3 | "The green neon sign outside" | | 4 | "She slid onto a stool," | | 5 | "The bartender, a broad-shouldered man" | | 6 | "His hazel eyes flicked over" | | 7 | "Silas said, setting the glass" | | 8 | "Rory exhaled through her nose." | | 9 | "Silas didn’t smile, but the" | | 10 | "She opened her mouth to" | | 11 | "A gust of cold air" | | 12 | "a voice drawled" | | 13 | "Rory’s fingers stilled around the" | | 14 | "She knew that voice." | | 15 | "Silas didn’t look at her." | | 16 | "The name hit her like" | | 17 | "She turned slowly, her pulse" | | 18 | "He stood in the doorway," | | 19 | "The years had carved lines" |
| | ratio | 0.817 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 93 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 1 | | fancyTags | | 0 | "a voice drawled (drawl)" |
| | dialogueSentences | 45 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 0.167 | | effectiveRatio | 0.044 | |