| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stepped aside [aside]" |
| | dialogueSentences | 32 | | tagDensity | 0.281 | | leniency | 0.563 | | rawRatio | 0.111 | | effectiveRatio | 0.063 | |
| 95.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1198 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 70.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1198 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "churned" | | 1 | "pawn" | | 2 | "velvet" | | 3 | "unsettled" | | 4 | "pulse" | | 5 | "warmth" | | 6 | "grave" |
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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 | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1198 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 960 | | uniqueNames | 13 | | maxNameDensity | 0.83 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Herrera" | | discoveredNames | | Tomás | 1 | | Herrera | 7 | | Camden | 2 | | Raven | 1 | | Nest | 1 | | Mornington | 1 | | Crescent | 1 | | Quinn | 8 | | Victorian | 2 | | Warm | 2 | | Seville | 1 | | Whitechapel | 1 | | Morris | 2 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Quinn" | | 3 | "Warm" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "Raven" | | 2 | "Mornington" | | 3 | "Crescent" | | 4 | "Seville" | | 5 | "Whitechapel" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1198 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 108 | | matches | | 0 | "knew that voice" | | 1 | "heard that voice" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 24.45 | | std | 21.37 | | cv | 0.874 | | sampleLengths | | 0 | 10 | | 1 | 48 | | 2 | 3 | | 3 | 6 | | 4 | 72 | | 5 | 47 | | 6 | 6 | | 7 | 51 | | 8 | 59 | | 9 | 9 | | 10 | 38 | | 11 | 1 | | 12 | 25 | | 13 | 1 | | 14 | 27 | | 15 | 1 | | 16 | 1 | | 17 | 35 | | 18 | 39 | | 19 | 27 | | 20 | 3 | | 21 | 47 | | 22 | 81 | | 23 | 8 | | 24 | 21 | | 25 | 53 | | 26 | 38 | | 27 | 10 | | 28 | 8 | | 29 | 35 | | 30 | 14 | | 31 | 30 | | 32 | 2 | | 33 | 14 | | 34 | 7 | | 35 | 61 | | 36 | 15 | | 37 | 25 | | 38 | 6 | | 39 | 50 | | 40 | 33 | | 41 | 2 | | 42 | 13 | | 43 | 1 | | 44 | 20 | | 45 | 6 | | 46 | 59 | | 47 | 2 | | 48 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 155 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 108 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 966 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.031055900621118012 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006211180124223602 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 11.09 | | std | 9.45 | | cv | 0.851 | | sampleLengths | | 0 | 10 | | 1 | 6 | | 2 | 23 | | 3 | 19 | | 4 | 3 | | 5 | 2 | | 6 | 4 | | 7 | 46 | | 8 | 9 | | 9 | 17 | | 10 | 8 | | 11 | 16 | | 12 | 8 | | 13 | 15 | | 14 | 1 | | 15 | 5 | | 16 | 36 | | 17 | 6 | | 18 | 9 | | 19 | 37 | | 20 | 1 | | 21 | 5 | | 22 | 11 | | 23 | 4 | | 24 | 1 | | 25 | 9 | | 26 | 22 | | 27 | 10 | | 28 | 4 | | 29 | 1 | | 30 | 1 | | 31 | 1 | | 32 | 15 | | 33 | 10 | | 34 | 1 | | 35 | 4 | | 36 | 14 | | 37 | 2 | | 38 | 7 | | 39 | 1 | | 40 | 1 | | 41 | 3 | | 42 | 12 | | 43 | 20 | | 44 | 6 | | 45 | 33 | | 46 | 23 | | 47 | 4 | | 48 | 3 | | 49 | 10 |
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| 81.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.5462962962962963 | | totalSentences | 108 | | uniqueOpeners | 59 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 74 | | matches | | 0 | "Of course he didn't." | | 1 | "Somewhere behind, a siren wailed" | | 2 | "Actually sniffed, head tilting like" | | 3 | "Somewhere below, water went drip-drop" | | 4 | "Then the stairwell spat her" | | 5 | "Then the next." | | 6 | "Then the next." |
| | ratio | 0.095 | |
| 95.68% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 74 | | matches | | 0 | "She'd tailed him from the" | | 1 | "She filed that under later." | | 2 | "He took the bridge over" | | 3 | "She caught one word." | | 4 | "His eyes caught the light" | | 5 | "She kept her palm closed" | | 6 | "She opened her hand." | | 7 | "His teeth came to points," | | 8 | "She hadn't shown him a" | | 9 | "She'd said police on the" | | 10 | "He stepped aside, and the" | | 11 | "Her phone showed no signal" | | 12 | "Her decision rang hollow." | | 13 | "She found Herrera near the" | | 14 | "He glanced at the cuff," | | 15 | "He smiled, and it didn't" | | 16 | "His voice dropped, and the" | | 17 | "His medallion caught the lamplight" | | 18 | "He looked past her shoulder," | | 19 | "She knew that voice." |
| | ratio | 0.311 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 74 | | matches | | 0 | "Quinn's boots hammered the wet" | | 1 | "Rain needled sideways through the" | | 2 | "She'd tailed him from the" | | 3 | "Men didn't run like that" | | 4 | "Men ran like that when" | | 5 | "Herrera vaulted the chain between" | | 6 | "Something fell from his pocket" | | 7 | "Quinn stooped without slowing and" | | 8 | "A disc of carved bone," | | 9 | "She filed that under later." | | 10 | "He took the bridge over" | | 11 | "Lock water churned black beneath" | | 12 | "Herrera ducked left, into the" | | 13 | "She caught one word." | | 14 | "A man unfolded from the" | | 15 | "His eyes caught the light" | | 16 | "She kept her palm closed" | | 17 | "She opened her hand." | | 18 | "The disc sat there, faintly" | | 19 | "His teeth came to points," |
| | ratio | 0.703 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 79.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 3 | | matches | | 0 | "She found Herrera near the far end, curly dark hair bent low over a stall, a flash of gold at his throat, talking fast and low to a vendor who kept glancing pas…" | | 1 | "Quinn moved along the platform's edge, using the crowd, hand resting on the cuffs at her belt." | | 2 | "Warm brown eyes, tired ones, the calm of a man who'd held strangers together with his hands." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "He stepped aside, and the door swung inward on stairs that went down further than stairs should" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 32 | | tagDensity | 0.031 | | leniency | 0.063 | | rawRatio | 0 | | effectiveRatio | 0 | |