| 70.97% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn turned back [back]" | | 1 | "Quinn moved back [back]" |
| | dialogueSentences | 31 | | tagDensity | 0.419 | | leniency | 0.839 | | rawRatio | 0.154 | | effectiveRatio | 0.129 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1187 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 62.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1187 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "weight" | | 1 | "rhythmic" | | 2 | "silk" | | 3 | "etched" | | 4 | "quivered" | | 5 | "chaotic" | | 6 | "pulsed" |
| |
| 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 | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 128 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1187 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 49.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 894 | | uniqueNames | 9 | | maxNameDensity | 2.01 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 18 | | Victorian | 1 | | Brixton | 1 | | Eva | 9 | | Camden | 1 | | High | 1 | | Street | 1 | | Veil | 1 | | Market | 1 |
| | persons | | | places | | 0 | "Brixton" | | 1 | "Camden" | | 2 | "High" | | 3 | "Street" |
| | globalScore | 0.493 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | 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 | 1187 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 128 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 37.09 | | std | 25.77 | | cv | 0.695 | | sampleLengths | | 0 | 11 | | 1 | 31 | | 2 | 65 | | 3 | 43 | | 4 | 43 | | 5 | 108 | | 6 | 41 | | 7 | 94 | | 8 | 22 | | 9 | 56 | | 10 | 39 | | 11 | 6 | | 12 | 64 | | 13 | 22 | | 14 | 66 | | 15 | 18 | | 16 | 15 | | 17 | 19 | | 18 | 65 | | 19 | 32 | | 20 | 35 | | 21 | 26 | | 22 | 29 | | 23 | 27 | | 24 | 71 | | 25 | 10 | | 26 | 14 | | 27 | 65 | | 28 | 23 | | 29 | 7 | | 30 | 13 | | 31 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 110 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 161 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 128 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 896 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.022321428571428572 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0011160714285714285 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 128 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 128 | | mean | 9.27 | | std | 5.61 | | cv | 0.604 | | sampleLengths | | 0 | 8 | | 1 | 3 | | 2 | 16 | | 3 | 9 | | 4 | 6 | | 5 | 13 | | 6 | 5 | | 7 | 22 | | 8 | 7 | | 9 | 6 | | 10 | 7 | | 11 | 5 | | 12 | 9 | | 13 | 15 | | 14 | 19 | | 15 | 6 | | 16 | 12 | | 17 | 12 | | 18 | 13 | | 19 | 14 | | 20 | 5 | | 21 | 1 | | 22 | 15 | | 23 | 4 | | 24 | 10 | | 25 | 7 | | 26 | 12 | | 27 | 8 | | 28 | 10 | | 29 | 11 | | 30 | 11 | | 31 | 4 | | 32 | 11 | | 33 | 26 | | 34 | 2 | | 35 | 11 | | 36 | 10 | | 37 | 20 | | 38 | 4 | | 39 | 1 | | 40 | 26 | | 41 | 5 | | 42 | 9 | | 43 | 6 | | 44 | 8 | | 45 | 14 | | 46 | 18 | | 47 | 15 | | 48 | 23 | | 49 | 7 |
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| 60.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3984375 | | totalSentences | 128 | | uniqueOpeners | 51 | |
| 33.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 100 | | matches | | 0 | "Somewhere in the dark, water" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 100 | | matches | | 0 | "Her worn leather satchel brushed" | | 1 | "She swept the light upward." | | 2 | "Her round glasses caught the" | | 3 | "She pointed to chalk marks" | | 4 | "She touched the man's jaw." | | 5 | "She lifted his chin." | | 6 | "She pulled a pen from" | | 7 | "She steadied it with one" | | 8 | "She swept her torch across" | | 9 | "It dragged her back to" | | 10 | "She shut the memory down." | | 11 | "She nudged one of the" | | 12 | "She withdrew a crumpled notebook" | | 13 | "She checked the jacket pockets." | | 14 | "She checked the trouser pockets." | | 15 | "Her fingers brushed something smooth" | | 16 | "She withdrew a flat disc" | | 17 | "Her freckled complexion paled in" | | 18 | "She checked the breast pocket" | | 19 | "Its face bore etched protective" |
| | ratio | 0.3 | |
| 30.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 100 | | matches | | 0 | "Quinn's torch beam caught the" | | 1 | "The leather gleamed." | | 2 | "Eva's voice carried excessive weight" | | 3 | "Her worn leather satchel brushed" | | 4 | "Quinn stepped onto the platform," | | 5 | "She swept the light upward." | | 6 | "The dead man lay across" | | 7 | "A single neat incision bisected" | | 8 | "The rusted rails remained dry." | | 9 | "The abandoned station curved like" | | 10 | "Eva stopped at the platform's" | | 11 | "Her round glasses caught the" | | 12 | "She pointed to chalk marks" | | 13 | "Quinn crouched beside the track" | | 14 | "She touched the man's jaw." | | 15 | "Rigor had fixed the limbs" | | 16 | "She lifted his chin." | | 17 | "The throat incision was camouflage," | | 18 | "She pulled a pen from" | | 19 | "A pale stripe of skin" |
| | ratio | 0.86 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 100 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "Beyond it, darkness pulsed with a faint violet hue that made her eyes ache." |
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| 48.08% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn stepped, her movements economical" | | 1 | "Eva knelt, her red curls trembling as she hovered over the chalk" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.032 | | leniency | 0.065 | | rawRatio | 0 | | effectiveRatio | 0 | |