| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 2 | | adverbTags | | 0 | "He glanced around [around]" | | 1 | "he finally said [finally]" |
| | dialogueSentences | 44 | | tagDensity | 0.386 | | leniency | 0.773 | | rawRatio | 0.118 | | effectiveRatio | 0.091 | |
| 80.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1756 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "suddenly" | | 1 | "really" | | 2 | "softly" | | 3 | "very" | | 4 | "carefully" |
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| 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) | |
| 40.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1756 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "glinting" | | 1 | "flickered" | | 2 | "beacon" | | 3 | "pumping" | | 4 | "raced" | | 5 | "standard" | | 6 | "pulsed" | | 7 | "echoed" | | 8 | "dance" | | 9 | "stark" | | 10 | "scanning" | | 11 | "traced" | | 12 | "facade" | | 13 | "pulse" | | 14 | "racing" | | 15 | "potential" | | 16 | "familiar" |
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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 | 1 | | narrationSentences | 157 | | matches | | |
| 88.26% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 157 | | filterMatches | | | hedgeMatches | | 0 | "seem to" | | 1 | "seemed to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 184 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1756 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 67.21% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 69 | | wordCount | 1389 | | uniqueNames | 20 | | maxNameDensity | 1.66 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Quinn | 23 | | Herrera | 21 | | Saint | 2 | | Christopher | 2 | | Raven | 3 | | Nest | 3 | | Old | 1 | | Compton | 1 | | Street | 1 | | Camden | 1 | | Morris | 1 | | Rules | 1 | | Veil | 1 | | Market | 1 | | Seville | 1 | | London | 2 | | Metropolitan | 1 | | Police | 1 | | Spanish | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Raven" | | 5 | "Nest" | | 6 | "Morris" | | 7 | "Rules" |
| | places | | 0 | "Soho" | | 1 | "Old" | | 2 | "Compton" | | 3 | "Street" | | 4 | "Camden" | | 5 | "Seville" | | 6 | "London" |
| | globalScore | 0.672 | | windowScore | 0.833 | |
| 59.09% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 110 | | glossingSentenceCount | 4 | | matches | | 0 | "something like fear" | | 1 | "looked like jars of moving liquid" | | 2 | "looked like a map drawn on human skin" | | 3 | "smelled like rain on hot pavement and secr" |
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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 | 1756 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 184 | | matches | | 0 | "spotted that medallion" | | 1 | "heard that term" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 75 | | mean | 23.41 | | std | 11.83 | | cv | 0.505 | | sampleLengths | | 0 | 42 | | 1 | 10 | | 2 | 49 | | 3 | 45 | | 4 | 39 | | 5 | 12 | | 6 | 27 | | 7 | 44 | | 8 | 38 | | 9 | 2 | | 10 | 38 | | 11 | 26 | | 12 | 22 | | 13 | 47 | | 14 | 3 | | 15 | 36 | | 16 | 33 | | 17 | 6 | | 18 | 27 | | 19 | 18 | | 20 | 25 | | 21 | 7 | | 22 | 42 | | 23 | 30 | | 24 | 10 | | 25 | 35 | | 26 | 38 | | 27 | 19 | | 28 | 11 | | 29 | 34 | | 30 | 22 | | 31 | 22 | | 32 | 24 | | 33 | 18 | | 34 | 31 | | 35 | 16 | | 36 | 32 | | 37 | 4 | | 38 | 19 | | 39 | 27 | | 40 | 24 | | 41 | 21 | | 42 | 39 | | 43 | 14 | | 44 | 17 | | 45 | 27 | | 46 | 32 | | 47 | 36 | | 48 | 22 | | 49 | 11 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 157 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 252 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 184 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1394 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 50 | | adverbRatio | 0.035868005738880916 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.011477761836441894 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 184 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 184 | | mean | 9.54 | | std | 5.46 | | cv | 0.572 | | sampleLengths | | 0 | 16 | | 1 | 15 | | 2 | 11 | | 3 | 10 | | 4 | 3 | | 5 | 8 | | 6 | 10 | | 7 | 18 | | 8 | 10 | | 9 | 7 | | 10 | 8 | | 11 | 15 | | 12 | 15 | | 13 | 8 | | 14 | 16 | | 15 | 15 | | 16 | 12 | | 17 | 11 | | 18 | 2 | | 19 | 14 | | 20 | 3 | | 21 | 4 | | 22 | 2 | | 23 | 2 | | 24 | 11 | | 25 | 22 | | 26 | 12 | | 27 | 10 | | 28 | 6 | | 29 | 10 | | 30 | 2 | | 31 | 14 | | 32 | 7 | | 33 | 17 | | 34 | 13 | | 35 | 13 | | 36 | 7 | | 37 | 3 | | 38 | 2 | | 39 | 10 | | 40 | 13 | | 41 | 8 | | 42 | 16 | | 43 | 10 | | 44 | 3 | | 45 | 11 | | 46 | 9 | | 47 | 16 | | 48 | 3 | | 49 | 13 |
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| 63.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.391304347826087 | | totalSentences | 184 | | uniqueOpeners | 72 | |
| 71.94% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 139 | | matches | | 0 | "Just her and a man" | | 1 | "No longer running, but not" | | 2 | "Instead he pulled a small" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 139 | | matches | | 0 | "She kept her breath steady," | | 1 | "she shouted, the words cutting" | | 2 | "He didn't slow." | | 3 | "She had spotted that medallion" | | 4 | "His curly hair plastered flat" | | 5 | "He veered suddenly toward Camden," | | 6 | "she called out, voice raw" | | 7 | "He said nothing, just pushed" | | 8 | "Her shoes squelched on the" | | 9 | "she warned, drawing her baton" | | 10 | "He stood near a stall" | | 11 | "His scar stood out stark" | | 12 | "She advanced, scanning the crowd." | | 13 | "His fingers traced the saint's" | | 14 | "She felt eyes on her" | | 15 | "His Spanish accent thickened with" | | 16 | "He gestured to the market" | | 17 | "His scar seemed to itch." | | 18 | "He scratched at it absently," | | 19 | "He glanced around, noting how" |
| | ratio | 0.273 | |
| 28.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 120 | | totalSentences | 139 | | matches | | 0 | "The suspect's coat flapped like" | | 1 | "Harlow Quinn pounded after him," | | 2 | "She kept her breath steady," | | 3 | "she shouted, the words cutting" | | 4 | "He didn't slow." | | 5 | "Tomás Herrera, the off-the-books medic" | | 6 | "The one with the Saint" | | 7 | "She had spotted that medallion" | | 8 | "Herrera cut left onto Old" | | 9 | "His curly hair plastered flat" | | 10 | "Quinn's lungs burned but she" | | 11 | "The green neon sign of" | | 12 | "He veered suddenly toward Camden," | | 13 | "Quinn followed without hesitation, her" | | 14 | "Rain lashed her face, blurring" | | 15 | "she called out, voice raw" | | 16 | "Herrera glanced back, warm brown" | | 17 | "He said nothing, just pushed" | | 18 | "Quinn's mind raced." | | 19 | "This wasn't standard procedure." |
| | ratio | 0.863 | |
| 71.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 139 | | matches | | 0 | "Now she chased him for" | | 1 | "Now she stood in the" |
| | ratio | 0.014 | |
| 67.10% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 7 | | matches | | 0 | "Harlow Quinn pounded after him, boots slapping through puddles that soaked her socks within seconds." | | 1 | "Merchants with too-sharp smiles peddled wares that glowed and whispered." | | 2 | "For a moment, the paramedic facade cracked, revealing the man beneath who had lost his NHS license for saving things that shouldn't breathe." | | 3 | "He turned toward a bookshelf against the far wall, the kind that looked too ordinary for this place." | | 4 | "Moving with purpose that made Quinn's military-trained instincts flare." | | 5 | "The flickering light revealed walls covered in maps similar to those in the Raven's Nest above, but these showed streets that didn't exist on any official Londo…" | | 6 | "The liquid burned going down, spreading fire through her veins that settled into a strange coolness." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 5 | | matches | | 0 | "she shouted, the words cutting through the downpour" | | 1 | "she called out, voice raw" | | 2 | "he finally said, voice low" | | 3 | "he said, voice tight" | | 4 | "she asked, voice steadier than she felt" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 7 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "she called out (call out)" | | 2 | "she warned (warn)" | | 3 | "she demanded (demand)" | | 4 | "Quinn repeated (repeat)" | | 5 | "he whispered (whisper)" | | 6 | "Herrera urged (urge)" |
| | dialogueSentences | 44 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0.583 | | effectiveRatio | 0.318 | |