| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "He gestured vaguely [vaguely]" | | 1 | "She laughed bitterly [bitterly]" |
| | dialogueSentences | 58 | | tagDensity | 0.328 | | leniency | 0.655 | | rawRatio | 0.105 | | effectiveRatio | 0.069 | |
| 95.32% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1069 | | totalAiIsmAdverbs | 1 | | 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) | |
| 34.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1069 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "flicked" | | 1 | "eyebrow" | | 2 | "stomach" | | 3 | "unspoken" | | 4 | "navigate" | | 5 | "etched" | | 6 | "shattered" | | 7 | "scanning" | | 8 | "silk" | | 9 | "silence" | | 10 | "racing" | | 11 | "weight" | | 12 | "unreadable" | | 13 | "resolve" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "the weight of his words" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 17 | | totalWords | 1064 | | ratio | 0.016 | | matches | | 0 | "Police Investigate Alleged Drug Ring Linked to Local Restaurants." | | 1 | "Imperial Holdings Ltd." | | 2 | "Come to the restaurant. Now." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 57.01% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 699 | | uniqueNames | 13 | | maxNameDensity | 1.86 | | worstName | "Silas" | | maxWindowNameDensity | 3 | | worstWindowName | "Silas" | | discoveredNames | | Silas | 13 | | Raven | 2 | | Nest | 2 | | Investigate | 1 | | Alleged | 1 | | Drug | 1 | | Ring | 1 | | Linked | 1 | | Local | 1 | | Rory | 9 | | Evan | 1 | | Holdings | 1 | | Yu-Fei | 1 |
| | persons | | 0 | "Silas" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Ring" | | 4 | "Rory" | | 5 | "Evan" |
| | places | | | globalScore | 0.57 | | windowScore | 0.667 | |
| 62.28% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it hadn’t been dusted since h" | | 1 | "quite reach his eyes" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1064 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 21.28 | | std | 13.53 | | cv | 0.636 | | sampleLengths | | 0 | 28 | | 1 | 36 | | 2 | 54 | | 3 | 21 | | 4 | 8 | | 5 | 14 | | 6 | 25 | | 7 | 2 | | 8 | 30 | | 9 | 31 | | 10 | 7 | | 11 | 19 | | 12 | 3 | | 13 | 11 | | 14 | 30 | | 15 | 33 | | 16 | 17 | | 17 | 16 | | 18 | 28 | | 19 | 7 | | 20 | 27 | | 21 | 18 | | 22 | 26 | | 23 | 39 | | 24 | 21 | | 25 | 11 | | 26 | 20 | | 27 | 73 | | 28 | 33 | | 29 | 9 | | 30 | 27 | | 31 | 15 | | 32 | 33 | | 33 | 14 | | 34 | 12 | | 35 | 28 | | 36 | 19 | | 37 | 18 | | 38 | 9 | | 39 | 25 | | 40 | 15 | | 41 | 4 | | 42 | 32 | | 43 | 15 | | 44 | 10 | | 45 | 2 | | 46 | 12 | | 47 | 11 | | 48 | 19 | | 49 | 47 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 129 | | matches | | |
| 88.95% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 106 | | ratio | 0.019 | | matches | | 0 | "The Raven’s Nest hadn’t changed much—same maps on the walls, same faint smell of polish and regret." | | 1 | "And for a moment, she wanted to tell him everything—about Evan, about the nights she spent staring at the ceiling, about the hollowness that had taken root in her chest." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 702 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.027065527065527065 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008547008547008548 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 10.04 | | std | 5.67 | | cv | 0.565 | | sampleLengths | | 0 | 15 | | 1 | 13 | | 2 | 11 | | 3 | 20 | | 4 | 5 | | 5 | 20 | | 6 | 17 | | 7 | 17 | | 8 | 13 | | 9 | 8 | | 10 | 8 | | 11 | 9 | | 12 | 5 | | 13 | 6 | | 14 | 16 | | 15 | 3 | | 16 | 2 | | 17 | 10 | | 18 | 20 | | 19 | 12 | | 20 | 19 | | 21 | 7 | | 22 | 14 | | 23 | 5 | | 24 | 3 | | 25 | 3 | | 26 | 8 | | 27 | 8 | | 28 | 15 | | 29 | 7 | | 30 | 12 | | 31 | 21 | | 32 | 7 | | 33 | 10 | | 34 | 9 | | 35 | 7 | | 36 | 9 | | 37 | 19 | | 38 | 7 | | 39 | 15 | | 40 | 12 | | 41 | 13 | | 42 | 5 | | 43 | 11 | | 44 | 15 | | 45 | 13 | | 46 | 26 | | 47 | 17 | | 48 | 4 | | 49 | 5 |
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| 52.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.33962264150943394 | | totalSentences | 106 | | uniqueOpeners | 36 | |
| 52.08% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 64 | | matches | | 0 | "Even the bookshelf in the" |
| | ratio | 0.016 | |
| 26.25% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 64 | | matches | | 0 | "he said, the corner of" | | 1 | "His hazel eyes flicked to" | | 2 | "She raised the glass to" | | 3 | "He leaned forward, his signet" | | 4 | "She set the glass down" | | 5 | "She shook her head, her" | | 6 | "He gestured vaguely at her" | | 7 | "She stiffened at the use" | | 8 | "It sounded foreign coming from" | | 9 | "He reached under the bar," | | 10 | "She snatched the paper, crumpling" | | 11 | "His voice softened, but the" | | 12 | "she shot back, her voice" | | 13 | "His voice cracked, a rare" | | 14 | "She laughed bitterly" | | 15 | "He stepped closer, his hand" | | 16 | "She looked at him then," | | 17 | "Her blood turned to ice." | | 18 | "She didn’t answer." | | 19 | "he said, his voice smooth" |
| | ratio | 0.484 | |
| 6.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 64 | | matches | | 0 | "The glass slid across the" | | 1 | "Rory caught it just before" | | 2 | "he said, the corner of" | | 3 | "His hazel eyes flicked to" | | 4 | "She raised the glass to" | | 5 | "The Raven’s Nest hadn’t changed" | | 6 | "Silas wiped down the bar" | | 7 | "He leaned forward, his signet" | | 8 | "The whiskey soured in her" | | 9 | "She set the glass down" | | 10 | "She shook her head, her" | | 11 | "Silas chuckled, a low, rumbling" | | 12 | "He gestured vaguely at her" | | 13 | "She stiffened at the use" | | 14 | "It sounded foreign coming from" | | 15 | "He reached under the bar," | | 16 | "The headline screamed in bold" | | 17 | "Silas said, tapping the article" | | 18 | "She snatched the paper, crumpling" | | 19 | "His voice softened, but the" |
| | ratio | 0.906 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 1 | | matches | | 0 | "A man in a tailored suit stepped into the bar, his eyes scanning the room before landing on Rory." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 9 | | matches | | 0 | "he said, the corner of his mouth twitching" | | 1 | "She raised, the whiskey burning its way down" | | 2 | "His voice softened, but the edge remained" | | 3 | "she shot back, her voice sharper than she intended" | | 4 | "He stepped, his hand brushing her arm" | | 5 | "Silas whispered, his tone urgent" | | 6 | "he said, his voice smooth as silk" | | 7 | "he said, his gaze locking with Rory’s" | | 8 | "he said, his voice low and urgent" |
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| 98.28% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "She laughed bitterly (laugh)" | | 1 | "Silas whispered (whisper)" | | 2 | "He laughed (laugh)" |
| | dialogueSentences | 58 | | tagDensity | 0.138 | | leniency | 0.276 | | rawRatio | 0.375 | | effectiveRatio | 0.103 | |