| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stepped aside [aside]" |
| | dialogueSentences | 48 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.063 | | effectiveRatio | 0.042 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1228 | | 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) | |
| 55.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1228 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "perfect" | | 1 | "warmth" | | 2 | "flicked" | | 3 | "remarkable" | | 4 | "weight" | | 5 | "electric" | | 6 | "flickered" | | 7 | "porcelain" | | 8 | "shattered" | | 9 | "echoed" |
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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 | 106 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 106 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 138 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 10 | | markdownWords | 57 | | totalWords | 1228 | | ratio | 0.046 | | matches | | 0 | "Got you." | | 1 | "In or out?" | | 2 | "So much for subtle." | | 3 | "This is where it gets real." | | 4 | "A cavern." | | 5 | "This is what Morris was investigating." | | 6 | "Morris. The case. The unexplained circumstances." | | 7 | "Three years. Three years of questions with no answers." | | 8 | "This is the decision." | | 9 | "Morris's voice echoed in her memory: \"Sometimes the smartest move is knowing when to fold.\"" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 69.87% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 936 | | uniqueNames | 10 | | maxNameDensity | 1.6 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Spitalfields | 1 | | Market | 2 | | Quinn | 15 | | Morris | 4 | | Tube | 1 | | Marwan | 4 | | Veil | 1 | | Follow | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Market" | | 3 | "Quinn" | | 4 | "Morris" | | 5 | "Marwan" |
| | places | | | globalScore | 0.699 | | windowScore | 0.833 | |
| 38.06% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 3 | | matches | | 0 | "weapons that seemed to hum with their own heartbeat, books bound in materials she didn't want to identify" | | 1 | "looked like liquid starlight" | | 2 | "quite sound" |
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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 | 1228 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 138 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 70 | | mean | 17.54 | | std | 16.28 | | cv | 0.928 | | sampleLengths | | 0 | 53 | | 1 | 2 | | 2 | 61 | | 3 | 16 | | 4 | 18 | | 5 | 57 | | 6 | 3 | | 7 | 44 | | 8 | 2 | | 9 | 7 | | 10 | 13 | | 11 | 16 | | 12 | 54 | | 13 | 18 | | 14 | 3 | | 15 | 22 | | 16 | 2 | | 17 | 5 | | 18 | 27 | | 19 | 43 | | 20 | 12 | | 21 | 6 | | 22 | 19 | | 23 | 42 | | 24 | 6 | | 25 | 20 | | 26 | 25 | | 27 | 10 | | 28 | 59 | | 29 | 9 | | 30 | 2 | | 31 | 62 | | 32 | 9 | | 33 | 30 | | 34 | 6 | | 35 | 18 | | 36 | 24 | | 37 | 1 | | 38 | 9 | | 39 | 5 | | 40 | 29 | | 41 | 32 | | 42 | 3 | | 43 | 11 | | 44 | 29 | | 45 | 2 | | 46 | 20 | | 47 | 5 | | 48 | 13 | | 49 | 4 |
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| 95.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 106 | | matches | | 0 | "was gone" | | 1 | "been dusted" | | 2 | "been dropped" |
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| 46.74% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 174 | | matches | | 0 | "was investigating" | | 1 | "was running" | | 2 | "was laughing" | | 3 | "was waking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 138 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 940 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.026595744680851064 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005319148936170213 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 138 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 138 | | mean | 8.9 | | std | 5.98 | | cv | 0.672 | | sampleLengths | | 0 | 18 | | 1 | 16 | | 2 | 19 | | 3 | 2 | | 4 | 3 | | 5 | 7 | | 6 | 22 | | 7 | 12 | | 8 | 9 | | 9 | 8 | | 10 | 16 | | 11 | 5 | | 12 | 6 | | 13 | 7 | | 14 | 21 | | 15 | 22 | | 16 | 14 | | 17 | 3 | | 18 | 8 | | 19 | 12 | | 20 | 1 | | 21 | 3 | | 22 | 20 | | 23 | 2 | | 24 | 3 | | 25 | 4 | | 26 | 13 | | 27 | 12 | | 28 | 4 | | 29 | 16 | | 30 | 9 | | 31 | 12 | | 32 | 17 | | 33 | 12 | | 34 | 6 | | 35 | 3 | | 36 | 11 | | 37 | 11 | | 38 | 2 | | 39 | 5 | | 40 | 14 | | 41 | 5 | | 42 | 3 | | 43 | 5 | | 44 | 10 | | 45 | 11 | | 46 | 4 | | 47 | 18 | | 48 | 10 | | 49 | 2 |
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| 66.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.43478260869565216 | | totalSentences | 138 | | uniqueOpeners | 60 | |
| 34.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 98 | | matches | | 0 | "Too careful for a simple" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 98 | | matches | | 0 | "He'd been careful." | | 1 | "He glanced over his shoulder." | | 2 | "She pushed off the brick" | | 3 | "He stepped aside, gestured inside" | | 4 | "He leaned against the counter," | | 5 | "She knew better." | | 6 | "He pushed off the counter" | | 7 | "He pressed against a particular" | | 8 | "His voice followed her down" | | 9 | "She ignored them all, eyes" | | 10 | "His face was a mask" | | 11 | "He backed away, knocking over" | | 12 | "They shattered, releasing a scream" | | 13 | "His voice cracked" | | 14 | "She ran after Marwan." |
| | ratio | 0.153 | |
| 62.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 98 | | matches | | 0 | "The green neon of The" | | 1 | "Quinn pressed her back against" | | 2 | "The silhouette she'd been tracking" | | 3 | "He'd been careful." | | 4 | "The way he checked his" | | 5 | "The nervous thumb rubbing against" | | 6 | "The same thumb that had" | | 7 | "He glanced over his shoulder." | | 8 | "Quinn flattened herself against the" | | 9 | "She pushed off the brick" | | 10 | "The Raven's Nest's entrance was" | | 11 | "The sign above buzzed faintly," | | 12 | "The door swung open before" | | 13 | "A man stood in the" | | 14 | "Silver streaked through his dark" | | 15 | "Quinn's jaw tightened." | | 16 | "He stepped aside, gestured inside" | | 17 | "The warmth of the place" | | 18 | "Maps covered the walls, their" | | 19 | "A handful of patrons nursed" |
| | ratio | 0.796 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 8.93% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 6 | | matches | | 0 | "The same thumb that had left a perfect print on a witness's windowsill two nights ago." | | 1 | "The Raven's Nest's entrance was a black door sandwiched between a closed bookshop and a kebab joint that had seen better decades." | | 2 | "Silver streaked through his dark hair, and his eyes had that look of someone who'd seen things they couldn't unsee." | | 3 | "The space stretched in all directions, stalls and tents crammed together like a medieval market that had been dropped into an abandoned Tube station." | | 4 | "Gas lamps flickered, their light catching on strange merchandise: jars filled with iridescent smoke, weapons that seemed to hum with their own heartbeat, books …" | | 5 | "Marwan's jacket caught her eye, disappearing behind a stall selling vials of something that looked like liquid starlight." |
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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 | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 48 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0.333 | | effectiveRatio | 0.042 | |