| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1557 | | 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) | |
| 48.62% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1557 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "scanned" | | 1 | "lilt" | | 2 | "weight" | | 3 | "eyebrow" | | 4 | "methodical" | | 5 | "silence" | | 6 | "traced" | | 7 | "trembled" | | 8 | "silk" | | 9 | "measured" | | 10 | "flickered" | | 11 | "unspoken" | | 12 | "tinged" |
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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 | 120 | | matches | (empty) | |
| 95.24% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 120 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 183 | | 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 | 1555 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 1178 | | uniqueNames | 26 | | maxNameDensity | 0.85 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Nate" | | discoveredNames | | Sichuan | 1 | | Italian | 1 | | Rory | 10 | | Cardiff | 2 | | Aurora | 2 | | Silas | 8 | | Golden | 1 | | Empress | 1 | | Carter | 2 | | Nate | 10 | | Soho | 1 | | Costa | 1 | | Queen | 1 | | Street | 1 | | London | 1 | | Evan | 1 | | Christmas | 1 | | March | 1 | | Adam | 1 | | Canary | 1 | | Wharf | 1 | | Can | 1 | | Human | 1 | | Rights | 1 | | Act | 1 | | You | 4 |
| | persons | | 0 | "Rory" | | 1 | "Silas" | | 2 | "Carter" | | 3 | "Nate" | | 4 | "Costa" | | 5 | "Queen" | | 6 | "Evan" | | 7 | "Adam" | | 8 | "You" |
| | places | | 0 | "Sichuan" | | 1 | "Cardiff" | | 2 | "Golden" | | 3 | "Soho" | | 4 | "Street" | | 5 | "London" | | 6 | "Christmas" | | 7 | "Canary" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a subpoena" |
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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 | 1555 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 183 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 25.08 | | std | 23.86 | | cv | 0.951 | | sampleLengths | | 0 | 88 | | 1 | 65 | | 2 | 8 | | 3 | 1 | | 4 | 42 | | 5 | 23 | | 6 | 1 | | 7 | 73 | | 8 | 5 | | 9 | 3 | | 10 | 3 | | 11 | 44 | | 12 | 9 | | 13 | 5 | | 14 | 21 | | 15 | 10 | | 16 | 32 | | 17 | 10 | | 18 | 16 | | 19 | 6 | | 20 | 20 | | 21 | 18 | | 22 | 6 | | 23 | 9 | | 24 | 62 | | 25 | 15 | | 26 | 1 | | 27 | 71 | | 28 | 7 | | 29 | 28 | | 30 | 3 | | 31 | 66 | | 32 | 15 | | 33 | 8 | | 34 | 58 | | 35 | 28 | | 36 | 9 | | 37 | 23 | | 38 | 4 | | 39 | 16 | | 40 | 86 | | 41 | 54 | | 42 | 31 | | 43 | 7 | | 44 | 3 | | 45 | 79 | | 46 | 57 | | 47 | 10 | | 48 | 7 | | 49 | 2 |
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| 96.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 120 | | matches | | 0 | "were manicured" | | 1 | "gone" | | 2 | "was swamped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 205 | | matches | | 0 | "was rearranging" | | 1 | "were coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 183 | | ratio | 0.011 | | matches | | 0 | "He stamped his shoes—Italian leather, Rory noted, the kind that cost more than her monthly rent—and ran a hand through hair cut sharp against his skull." | | 1 | "A drop leapt onto the back of his hand; he ignored it." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 163 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.018404907975460124 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.006134969325153374 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 183 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 183 | | mean | 8.5 | | std | 6.82 | | cv | 0.803 | | sampleLengths | | 0 | 16 | | 1 | 34 | | 2 | 15 | | 3 | 23 | | 4 | 16 | | 5 | 26 | | 6 | 17 | | 7 | 6 | | 8 | 2 | | 9 | 6 | | 10 | 1 | | 11 | 17 | | 12 | 5 | | 13 | 5 | | 14 | 9 | | 15 | 6 | | 16 | 5 | | 17 | 18 | | 18 | 1 | | 19 | 8 | | 20 | 6 | | 21 | 25 | | 22 | 19 | | 23 | 9 | | 24 | 6 | | 25 | 5 | | 26 | 3 | | 27 | 3 | | 28 | 15 | | 29 | 19 | | 30 | 10 | | 31 | 2 | | 32 | 4 | | 33 | 3 | | 34 | 5 | | 35 | 8 | | 36 | 1 | | 37 | 8 | | 38 | 4 | | 39 | 5 | | 40 | 5 | | 41 | 2 | | 42 | 17 | | 43 | 10 | | 44 | 2 | | 45 | 1 | | 46 | 10 | | 47 | 13 | | 48 | 3 | | 49 | 1 |
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| 42.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.3333333333333333 | | totalSentences | 183 | | uniqueOpeners | 61 | |
| 93.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 107 | | matches | | 0 | "Then his gaze snagged on" | | 1 | "Once, those thumbs had held" | | 2 | "Instead I sent you a" |
| | ratio | 0.028 | |
| 70.47% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 107 | | matches | | 0 | "He stamped his shoes—Italian leather," | | 1 | "He scanned the room with" | | 2 | "His voice carried the remnants" | | 3 | "She turned on the stool." | | 4 | "Her fingers found the crescent" | | 5 | "He approached, leaving wet footprints" | | 6 | "He smelled of cedar and" | | 7 | "His trousers creased perfectly." | | 8 | "He laughed, a dry click" | | 9 | "He lifted the glass Silas" | | 10 | "He didn't deny it." | | 11 | "His thumb traced the rim" | | 12 | "His were grey, unchanged despite" | | 13 | "I needed a drink that" | | 14 | "Your mother told mine you'd" | | 15 | "You just didn't take" | | 16 | "She remembered that last week" | | 17 | "She remembered Nate's voicemail, something" | | 18 | "She'd deleted it." | | 19 | "It had seemed cleaner that" |
| | ratio | 0.374 | |
| 25.42% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 107 | | matches | | 0 | "The green neon from the" | | 1 | "Rory sat on a stool" | | 2 | "Silas wiped a tumbler with" | | 3 | "The maps on the walls" | | 4 | "The door swung inward, admitting" | | 5 | "He stamped his shoes—Italian leather," | | 6 | "He scanned the room with" | | 7 | "The door clicked shut behind" | | 8 | "His voice carried the remnants" | | 9 | "Nobody here called her Aurora." | | 10 | "The name sounded like a" | | 11 | "She turned on the stool." | | 12 | "Her fingers found the crescent" | | 13 | "He approached, leaving wet footprints" | | 14 | "The boy she'd known at" | | 15 | "This Nate had filled out," | | 16 | "A scar bisected his right" | | 17 | "He smelled of cedar and" | | 18 | "Silas placed a glass of" | | 19 | "Nate looked at it, then" |
| | ratio | 0.869 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 107 | | matches | | 0 | "To Silas she was Rory." | | 1 | "To the chefs at Golden" | | 2 | "Now they were manicured, the" | | 3 | "If I'd told you, you'd" |
| | ratio | 0.037 | |
| 43.19% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 6 | | matches | | 0 | "He stamped his shoes—Italian leather, Rory noted, the kind that cost more than her monthly rent—and ran a hand through hair cut sharp against his skull." | | 1 | "This Nate had filled out, the wool of his coat straining against shoulders that hadn't carried that weight before." | | 2 | "Nate looked at it, then at Silas, who had already turned his attention back to the shelf of bottles." | | 3 | "Nate glanced at the older man, who was rearranging bottles with methodical calm." | | 4 | "The wife who likes my salary more than my conversation." | | 5 | "The green neon flickered, bathing Nate's face in a sickly hue that rendered him a stranger for a heartbeat." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |