| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.321 | | leniency | 0.643 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.62% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1481 | | 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) | |
| 66.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1481 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "pulsed" | | 3 | "weight" | | 4 | "familiar" | | 5 | "echoes" | | 6 | "complex" | | 7 | "pulse" | | 8 | "scanning" | | 9 | "firmly" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | 0 | "blood went cold" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 128 | | matches | (empty) | |
| 75.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 5 | | narrationSentences | 128 | | filterMatches | | | hedgeMatches | | 0 | "happened to" | | 1 | "began to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 145 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 13 | | totalWords | 1466 | | ratio | 0.009 | | matches | | 0 | "The Veil Market." | | 1 | "Suspect fled into a magical fairy market under Camden." | | 2 | "Don’t." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1233 | | uniqueNames | 9 | | maxNameDensity | 0.89 | | worstName | "Herrera" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Quinn | 5 | | Tomás | 4 | | Herrera | 11 | | Morris | 4 | | London | 1 | | Tube | 1 | | Saint | 1 | | Christopher | 1 | | Veil | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Tomás" | | 2 | "Herrera" | | 3 | "Morris" | | 4 | "Saint" | | 5 | "Christopher" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 1 | | matches | | 0 | "suit that seemed to drink the light" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.046 | | wordCount | 1466 | | matches | | 0 | "Not echoes, but a low babble of conversation" | | 1 | "not back towards the entrance, but deeper into the market, towards a curtained-off area at the" | | 2 | "Not fear, but a frantic, urgent surprise" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 145 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 49 | | mean | 29.92 | | std | 20.87 | | cv | 0.698 | | sampleLengths | | 0 | 70 | | 1 | 81 | | 2 | 3 | | 3 | 29 | | 4 | 55 | | 5 | 22 | | 6 | 3 | | 7 | 52 | | 8 | 56 | | 9 | 38 | | 10 | 28 | | 11 | 5 | | 12 | 11 | | 13 | 80 | | 14 | 49 | | 15 | 35 | | 16 | 8 | | 17 | 63 | | 18 | 31 | | 19 | 36 | | 20 | 48 | | 21 | 25 | | 22 | 25 | | 23 | 2 | | 24 | 15 | | 25 | 61 | | 26 | 25 | | 27 | 20 | | 28 | 28 | | 29 | 37 | | 30 | 7 | | 31 | 8 | | 32 | 49 | | 33 | 24 | | 34 | 6 | | 35 | 42 | | 36 | 4 | | 37 | 24 | | 38 | 5 | | 39 | 15 | | 40 | 7 | | 41 | 53 | | 42 | 19 | | 43 | 44 | | 44 | 6 | | 45 | 32 | | 46 | 33 | | 47 | 20 | | 48 | 27 |
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| 97.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 128 | | matches | | 0 | "been told" | | 1 | "was unarmed" | | 2 | "was fixed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 214 | | matches | | 0 | "was speaking" | | 1 | "was finishing" | | 2 | "were watching" |
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| 24.63% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 145 | | ratio | 0.041 | | matches | | 0 | "Ahead, a figure in a dark coat—Tomás Herrera—splashed through a flooded gutter and ducked into a narrow service alley between a shuttered record shop and a takeaway." | | 1 | "The clean, cold scent of rain gave way to damp concrete, mildew, and something else—ozone again, and a coppery tang, like old blood and hot wiring." | | 2 | "Her feet hit solid ground—a disused platform." | | 3 | "The smell grew more complex—spices, incense, the acrid bite of chemicals." | | 4 | "Figures moved through the aisles—some human, some decidedly not." | | 5 | "A hand shot out from a stall—a hand with too many knuckles." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1248 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faint, greenish light pulsed." |
| | adverbCount | 30 | | adverbRatio | 0.02403846153846154 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.008814102564102564 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 145 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 145 | | mean | 10.11 | | std | 6.74 | | cv | 0.666 | | sampleLengths | | 0 | 20 | | 1 | 11 | | 2 | 12 | | 3 | 27 | | 4 | 4 | | 5 | 11 | | 6 | 11 | | 7 | 4 | | 8 | 20 | | 9 | 6 | | 10 | 15 | | 11 | 10 | | 12 | 3 | | 13 | 4 | | 14 | 17 | | 15 | 3 | | 16 | 5 | | 17 | 4 | | 18 | 12 | | 19 | 4 | | 20 | 24 | | 21 | 11 | | 22 | 5 | | 23 | 5 | | 24 | 8 | | 25 | 4 | | 26 | 3 | | 27 | 7 | | 28 | 3 | | 29 | 26 | | 30 | 10 | | 31 | 6 | | 32 | 7 | | 33 | 3 | | 34 | 1 | | 35 | 18 | | 36 | 13 | | 37 | 14 | | 38 | 11 | | 39 | 14 | | 40 | 13 | | 41 | 5 | | 42 | 8 | | 43 | 4 | | 44 | 11 | | 45 | 5 | | 46 | 7 | | 47 | 4 | | 48 | 29 | | 49 | 9 |
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| 51.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.3793103448275862 | | totalSentences | 145 | | uniqueOpeners | 55 | |
| 27.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 123 | | matches | | | ratio | 0.008 | |
| 73.66% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 123 | | matches | | 0 | "Her leather watch strap was" | | 1 | "Her shoes, built for pavement" | | 2 | "She caught herself against a" | | 3 | "Her shout was lost." | | 4 | "He was already at the" | | 5 | "He vanished into the dark." | | 6 | "She pulled a small torch" | | 7 | "She knew the city’s underbelly," | | 8 | "She went down." | | 9 | "Her feet hit solid ground—a" | | 10 | "She moved with military precision," | | 11 | "She unclipped her holster, her" | | 12 | "She peered around the curve." | | 13 | "It was a bazaar." | | 14 | "He was speaking urgently to" | | 15 | "Her pulse hammered against her" | | 16 | "He’d chased a lead into" | | 17 | "It was the one from" | | 18 | "He took a small, wrapped" | | 19 | "They passed over the tunnel" |
| | ratio | 0.366 | |
| 41.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 123 | | matches | | 0 | "The rain fell in sheets," | | 1 | "Harlow Quinn’s breath was a" | | 2 | "Her leather watch strap was" | | 3 | "Quinn didn’t break stride." | | 4 | "Her shoes, built for pavement" | | 5 | "She caught herself against a" | | 6 | "This man, Herrera, was a" | | 7 | "A thread that led to" | | 8 | "The ones who might know" | | 9 | "Her shout was lost." | | 10 | "He was already at the" | | 11 | "A maintenance hatch." | | 12 | "He vanished into the dark." | | 13 | "Quinn reached the hatch." | | 14 | "A square of deeper blackness," | | 15 | "Metal rungs led down." | | 16 | "She pulled a small torch" | | 17 | "The sound of footsteps echoed" | | 18 | "This wasn’t on any map." | | 19 | "This wasn’t a sewer access." |
| | ratio | 0.837 | |
| 81.30% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 123 | | matches | | 0 | "If she retreated now, called" | | 1 | "If she went in, she" |
| | ratio | 0.016 | |
| 79.08% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 5 | | matches | | 0 | "The rain fell in sheets, a relentless drumbeat on the asphalt that turned the city’s sodium-orange glow into a smear." | | 1 | "Three years of dead ends that smelled of ozone and burnt sugar, of case files that dissolved into bureaucratic mist." | | 2 | "Stalls lined the old platform, cobbled together from scrap wood and old shipping containers, lit by flickering lanterns that burned with unnatural colours: viol…" | | 3 | "She kept her bearing straight, her gaze locked on Herrera’s retreating back, and walked forward as if she had every right to be there." | | 4 | "Other market-goers were watching, their postures shifting from curiosity to threat." |
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| 69.44% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 1 | | matches | | 0 | "He looked, his anxiety spiking" |
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| 42.86% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 3 | | fancyTags | | 0 | "leaning forward saying (leaning forward saying)" | | 1 | "he hissed (hiss)" | | 2 | "he whispered (whisper)" |
| | dialogueSentences | 28 | | tagDensity | 0.107 | | leniency | 0.214 | | rawRatio | 1 | | effectiveRatio | 0.214 | |