| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.20% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1787 | | 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) | |
| 58.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1787 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "flickered" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "velvet" | | 4 | "traced" | | 5 | "porcelain" | | 6 | "measured" | | 7 | "etched" | | 8 | "shattered" | | 9 | "loomed" | | 10 | "pulse" |
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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 | 237 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 237 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 269 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1787 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1495 | | uniqueNames | 17 | | maxNameDensity | 1.4 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Tomás" | | discoveredNames | | Metropolitan | 1 | | Camden | 1 | | Edison | 1 | | Veil | 1 | | Market | 1 | | Morris | 4 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Seville | 1 | | London | 1 | | Harlow | 21 | | Tomás | 20 | | Met | 1 | | Persian | 1 | | Glass | 3 | | Three | 3 |
| | persons | | 0 | "Edison" | | 1 | "Market" | | 2 | "Morris" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" | | 6 | "Harlow" | | 7 | "Tomás" | | 8 | "Glass" |
| | places | | 0 | "Seville" | | 1 | "London" | | 2 | "Persian" |
| | globalScore | 0.798 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 115 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like gravel grinding in a mixer" |
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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 | 1787 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 269 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 70 | | mean | 25.53 | | std | 21.73 | | cv | 0.851 | | sampleLengths | | 0 | 50 | | 1 | 52 | | 2 | 9 | | 3 | 34 | | 4 | 60 | | 5 | 91 | | 6 | 50 | | 7 | 40 | | 8 | 6 | | 9 | 20 | | 10 | 20 | | 11 | 13 | | 12 | 5 | | 13 | 29 | | 14 | 9 | | 15 | 44 | | 16 | 26 | | 17 | 7 | | 18 | 14 | | 19 | 21 | | 20 | 67 | | 21 | 4 | | 22 | 51 | | 23 | 33 | | 24 | 3 | | 25 | 6 | | 26 | 1 | | 27 | 29 | | 28 | 10 | | 29 | 33 | | 30 | 11 | | 31 | 22 | | 32 | 38 | | 33 | 4 | | 34 | 12 | | 35 | 103 | | 36 | 70 | | 37 | 26 | | 38 | 4 | | 39 | 13 | | 40 | 3 | | 41 | 6 | | 42 | 2 | | 43 | 54 | | 44 | 8 | | 45 | 25 | | 46 | 9 | | 47 | 7 | | 48 | 37 | | 49 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 237 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 286 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 269 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1500 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.015333333333333332 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.004 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 269 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 269 | | mean | 6.64 | | std | 4.59 | | cv | 0.691 | | sampleLengths | | 0 | 4 | | 1 | 10 | | 2 | 9 | | 3 | 3 | | 4 | 2 | | 5 | 22 | | 6 | 7 | | 7 | 5 | | 8 | 18 | | 9 | 2 | | 10 | 5 | | 11 | 8 | | 12 | 3 | | 13 | 4 | | 14 | 9 | | 15 | 4 | | 16 | 17 | | 17 | 6 | | 18 | 3 | | 19 | 4 | | 20 | 7 | | 21 | 3 | | 22 | 7 | | 23 | 4 | | 24 | 11 | | 25 | 12 | | 26 | 2 | | 27 | 2 | | 28 | 1 | | 29 | 7 | | 30 | 4 | | 31 | 8 | | 32 | 14 | | 33 | 10 | | 34 | 10 | | 35 | 16 | | 36 | 18 | | 37 | 11 | | 38 | 2 | | 39 | 2 | | 40 | 8 | | 41 | 6 | | 42 | 7 | | 43 | 11 | | 44 | 2 | | 45 | 2 | | 46 | 14 | | 47 | 6 | | 48 | 2 | | 49 | 5 |
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| 51.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.3420074349442379 | | totalSentences | 269 | | uniqueOpeners | 92 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 195 | | matches | | 0 | "Just a case file sealed" | | 1 | "Just dead end and rising" | | 2 | "Just smooth skin and a" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 195 | | matches | | 0 | "She pushed harder." | | 1 | "She cleared a stack of" | | 2 | "Her knees absorbed the impact." | | 3 | "She drew her warrant card," | | 4 | "Her voice bounced off the" | | 5 | "He dodged left, past a" | | 6 | "He slipped inside." | | 7 | "She stumbled into a narrow" | | 8 | "He knew the route." | | 9 | "She checked her worn leather" | | 10 | "His accent carried the soft" | | 11 | "He lowered his hands slowly" | | 12 | "It did not reach his" | | 13 | "She kept her voice level." | | 14 | "He pulled out a small," | | 15 | "He held it up." | | 16 | "It meant career suicide." | | 17 | "It also meant the only" | | 18 | "She stepped forward." | | 19 | "He turned and walked into" |
| | ratio | 0.282 | |
| 11.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 175 | | totalSentences | 195 | | matches | | 0 | "Boots slapped wet tarmac." | | 1 | "Harlow pivoted round the corner," | | 2 | "The suspect’s dark coat whipped" | | 3 | "She pushed harder." | | 4 | "She cleared a stack of" | | 5 | "Glass crunched under her soles." | | 6 | "The suspect vaulted a low" | | 7 | "Her knees absorbed the impact." | | 8 | "She drew her warrant card," | | 9 | "Protocol demanded restraint." | | 10 | "Instinct demanded a tackle." | | 11 | "Her voice bounced off the" | | 12 | "The suspect ignored her." | | 13 | "He dodged left, past a" | | 14 | "He slipped inside." | | 15 | "The door swung shut." | | 16 | "Harlow hit the metal with" | | 17 | "The latch gave." | | 18 | "She stumbled into a narrow" | | 19 | "The air changed instantly." |
| | ratio | 0.897 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 195 | | matches | (empty) | | ratio | 0 | |
| 86.47% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 3 | | matches | | 0 | "Just a case file sealed by superiors who preferred blind eyes to broken rules." | | 1 | "The air hung heavy, pressing against the lungs, thick with the static charge of things that should not exist above ground." | | 2 | "He moved with purpose, weaving past a table of tarot readers and a butcher block displaying something that resembled a ribcage but had too many joints." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "the vendor hissed (hiss)" | | 1 | "the vendor repeated (repeat)" |
| | dialogueSentences | 48 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0.5 | | effectiveRatio | 0.083 | |