| 62.07% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 2 | | adverbTags | | 0 | "The words came automatically [automatically]" | | 1 | "He stepped back [back]" |
| | dialogueSentences | 29 | | tagDensity | 0.414 | | leniency | 0.828 | | rawRatio | 0.167 | | effectiveRatio | 0.138 | |
| 95.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1161 | | 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) | |
| 78.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1161 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "streaming" | | 1 | "echoed" | | 2 | "footsteps" | | 3 | "resolved" | | 4 | "pulsed" |
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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 | 147 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 147 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 164 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 16 | | totalWords | 1157 | | ratio | 0.014 | | matches | | 0 | "They took me down there, Quinn. Under Camden. Sold me to something with too many eyes." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.06% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 971 | | uniqueNames | 20 | | maxNameDensity | 1.34 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Neal | 1 | | Street | 1 | | Quinn | 2 | | Covent | 1 | | Garden | 1 | | Herrera | 2 | | Morris | 5 | | Vietnamese | 1 | | Essex | 1 | | Cocky | 1 | | Camden | 2 | | Veil | 1 | | Market | 3 | | London | 1 | | Christopher | 1 | | Several | 1 | | Tomás | 3 | | Harlow | 13 | | Three | 3 | | Lost | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "Christopher" | | 4 | "Tomás" | | 5 | "Harlow" |
| | places | | 0 | "Neal" | | 1 | "Street" | | 2 | "Covent" | | 3 | "Garden" | | 4 | "Essex" | | 5 | "Market" | | 6 | "London" |
| | globalScore | 0.831 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 1 | | matches | | 0 | "robes that seemed to be made of smoke" |
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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 | 1157 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 164 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 19.61 | | std | 15.25 | | cv | 0.778 | | sampleLengths | | 0 | 15 | | 1 | 54 | | 2 | 31 | | 3 | 39 | | 4 | 3 | | 5 | 6 | | 6 | 38 | | 7 | 42 | | 8 | 20 | | 9 | 18 | | 10 | 5 | | 11 | 7 | | 12 | 26 | | 13 | 3 | | 14 | 43 | | 15 | 16 | | 16 | 9 | | 17 | 22 | | 18 | 39 | | 19 | 6 | | 20 | 2 | | 21 | 43 | | 22 | 2 | | 23 | 5 | | 24 | 50 | | 25 | 6 | | 26 | 25 | | 27 | 55 | | 28 | 24 | | 29 | 27 | | 30 | 48 | | 31 | 28 | | 32 | 23 | | 33 | 6 | | 34 | 11 | | 35 | 24 | | 36 | 19 | | 37 | 4 | | 38 | 13 | | 39 | 14 | | 40 | 15 | | 41 | 26 | | 42 | 2 | | 43 | 31 | | 44 | 2 | | 45 | 35 | | 46 | 18 | | 47 | 9 | | 48 | 2 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 147 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 175 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 164 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 975 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.029743589743589743 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0071794871794871795 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 164 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 164 | | mean | 7.05 | | std | 5.19 | | cv | 0.736 | | sampleLengths | | 0 | 15 | | 1 | 17 | | 2 | 10 | | 3 | 3 | | 4 | 16 | | 5 | 8 | | 6 | 10 | | 7 | 8 | | 8 | 13 | | 9 | 6 | | 10 | 16 | | 11 | 17 | | 12 | 3 | | 13 | 3 | | 14 | 3 | | 15 | 13 | | 16 | 7 | | 17 | 12 | | 18 | 2 | | 19 | 2 | | 20 | 2 | | 21 | 14 | | 22 | 1 | | 23 | 1 | | 24 | 12 | | 25 | 14 | | 26 | 8 | | 27 | 12 | | 28 | 11 | | 29 | 2 | | 30 | 5 | | 31 | 5 | | 32 | 6 | | 33 | 1 | | 34 | 5 | | 35 | 1 | | 36 | 1 | | 37 | 2 | | 38 | 17 | | 39 | 3 | | 40 | 5 | | 41 | 10 | | 42 | 6 | | 43 | 12 | | 44 | 1 | | 45 | 1 | | 46 | 8 | | 47 | 8 | | 48 | 8 | | 49 | 4 |
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| 82.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.5487804878048781 | | totalSentences | 164 | | uniqueOpeners | 90 | |
| 29.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 114 | | matches | | 0 | "Too cocky for someone cornered." |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 114 | | matches | | 0 | "He didn't stop." | | 1 | "They never did." | | 2 | "He cut left through an" | | 3 | "Her watch pressed cold against" | | 4 | "His accent placed him somewhere" | | 5 | "He reached into his pocket." | | 6 | "He pulled out something small." | | 7 | "He held it up like" | | 8 | "He backed down the first" | | 9 | "*They took me down there," | | 10 | "She'd found his body three" | | 11 | "She'd heard whispers." | | 12 | "She descended, one hand trailing" | | 13 | "She jerked her hand away." | | 14 | "She focused on the suspect" | | 15 | "Her worn leather watch ticked" | | 16 | "She checked it out of" | | 17 | "She started walking forward." | | 18 | "He didn't let go" | | 19 | "He glanced over his shoulder" |
| | ratio | 0.202 | |
| 65.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 114 | | matches | | 0 | "The suspect's leather jacket disappeared" | | 1 | "Harlow Quinn pushed harder, her" | | 2 | "This one did." | | 3 | "Tommy Herrera's medical records, the" | | 4 | "Proof he'd been treating something" | | 5 | "The suspect vaulted a newspaper" | | 6 | "Harlow followed, her knee protesting," | | 7 | "He didn't stop." | | 8 | "They never did." | | 9 | "He cut left through an" | | 10 | "Harlow's hand went to her" | | 11 | "The alley opened onto a" | | 12 | "The suspect stood in the" | | 13 | "Tattoos crawling up his neck," | | 14 | "The ones the department psychiatrist" | | 15 | "Harlow said, catching her breath" | | 16 | "Her watch pressed cold against" | | 17 | "His accent placed him somewhere" | | 18 | "He reached into his pocket." | | 19 | "Harlow's hand moved to her" |
| | ratio | 0.789 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 114 | | matches | (empty) | | ratio | 0 | |
| 63.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 4 | | matches | | 0 | "Harlow Quinn pushed harder, her boots slapping through puddles that reflected the neon chaos of Covent Garden." | | 1 | "Harlow followed, her knee protesting, reminding her she was forty-one and chasing someone half her age." | | 2 | "The music grew louder, resolved into something with stringed instruments that shouldn't exist and vocals in languages she couldn't place." | | 3 | "Professional detachment, the kind that kept you sane at crime scenes, settled over her like armor." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.103 | | leniency | 0.207 | | rawRatio | 0 | | effectiveRatio | 0 | |