| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn walked around [around]" | | 1 | "Eva said quietly [quietly]" |
| | dialogueSentences | 52 | | tagDensity | 0.404 | | leniency | 0.808 | | rawRatio | 0.095 | | effectiveRatio | 0.077 | |
| 93.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1656 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 66.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1656 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "gloom" | | 1 | "glint" | | 2 | "etched" | | 3 | "furrowing" | | 4 | "traced" | | 5 | "navigate" | | 6 | "scanning" | | 7 | "echoing" | | 8 | "silence" | | 9 | "tracing" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 116 | | matches | (empty) | |
| 81.28% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 148 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1645 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1004 | | uniqueNames | 7 | | maxNameDensity | 2.19 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Harlow | 1 | | Quinn | 22 | | Kowalski | 1 | | Eva | 15 | | Veil | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0.404 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 1 | | matches | | 0 | "lines that seemed to move if she stared too long" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.608 | | wordCount | 1645 | | matches | | 0 | "not ripped, but cut, cleanly, along a line from collarbone to navel" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 148 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 29.91 | | std | 19.78 | | cv | 0.661 | | sampleLengths | | 0 | 52 | | 1 | 57 | | 2 | 5 | | 3 | 27 | | 4 | 46 | | 5 | 50 | | 6 | 79 | | 7 | 8 | | 8 | 24 | | 9 | 11 | | 10 | 7 | | 11 | 69 | | 12 | 5 | | 13 | 53 | | 14 | 5 | | 15 | 52 | | 16 | 6 | | 17 | 38 | | 18 | 34 | | 19 | 9 | | 20 | 32 | | 21 | 35 | | 22 | 72 | | 23 | 51 | | 24 | 8 | | 25 | 39 | | 26 | 54 | | 27 | 2 | | 28 | 26 | | 29 | 7 | | 30 | 42 | | 31 | 9 | | 32 | 34 | | 33 | 41 | | 34 | 15 | | 35 | 13 | | 36 | 23 | | 37 | 43 | | 38 | 5 | | 39 | 35 | | 40 | 36 | | 41 | 28 | | 42 | 24 | | 43 | 60 | | 44 | 16 | | 45 | 53 | | 46 | 19 | | 47 | 24 | | 48 | 34 | | 49 | 37 |
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| 87.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 116 | | matches | | 0 | "been rigged" | | 1 | "was unbuttoned" | | 2 | "been torn" | | 3 | "been branded" | | 4 | "was littered" | | 5 | "was etched" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 166 | | matches | | 0 | "were escaping" | | 1 | "was tucking" | | 2 | "was lying" | | 3 | "was spinning" | | 4 | "was still missing" | | 5 | "was getting" |
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| 7.72% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 148 | | ratio | 0.047 | | matches | | 0 | "Emergency lighting had been rigged along the tunnel—portable floods on tripods that cast hard shadows and made everything look like a crime scene photograph." | | 1 | "She walked past him, her boots crunching on debris—broken tile, a crushed polystyrene cup, something that might have been a bone token but she didn’t stoop to check." | | 2 | "She was tucking a strand of hair behind her left ear—the nervous habit Quinn had catalogued the first time they’d met, eighteen months ago, at a briefing that should never have included a museum research assistant." | | 3 | "Beneath it, his shirt had been torn open—not ripped, but cut, cleanly, along a line from collarbone to navel." | | 4 | "The platform was littered with the detritus of a pop-up market—collapsible tables, empty crates, a few stray tarpaulins." | | 5 | "The casing was verdigris-green with age, and the face was etched with symbols that matched the sigil on the dead man’s chest—similar, but not identical." | | 6 | "The way his head was turned—not the natural slump of unconsciousness." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 941 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.018065887353878853 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007438894792773645 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 148 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 148 | | mean | 11.11 | | std | 8.97 | | cv | 0.807 | | sampleLengths | | 0 | 6 | | 1 | 17 | | 2 | 29 | | 3 | 24 | | 4 | 4 | | 5 | 29 | | 6 | 5 | | 7 | 18 | | 8 | 9 | | 9 | 5 | | 10 | 13 | | 11 | 28 | | 12 | 9 | | 13 | 20 | | 14 | 8 | | 15 | 8 | | 16 | 5 | | 17 | 18 | | 18 | 25 | | 19 | 36 | | 20 | 8 | | 21 | 3 | | 22 | 9 | | 23 | 12 | | 24 | 11 | | 25 | 7 | | 26 | 12 | | 27 | 16 | | 28 | 17 | | 29 | 3 | | 30 | 2 | | 31 | 19 | | 32 | 5 | | 33 | 4 | | 34 | 19 | | 35 | 22 | | 36 | 8 | | 37 | 5 | | 38 | 9 | | 39 | 43 | | 40 | 6 | | 41 | 38 | | 42 | 3 | | 43 | 18 | | 44 | 7 | | 45 | 3 | | 46 | 3 | | 47 | 4 | | 48 | 5 | | 49 | 14 |
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| 40.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.31756756756756754 | | totalSentences | 148 | | uniqueOpeners | 47 | |
| 32.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 104 | | matches | | 0 | "Then she nodded, tucking her" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 104 | | matches | | 0 | "She stepped over a coil" | | 1 | "She walked past him, her" | | 2 | "Her red curls were escaping" | | 3 | "She was tucking a strand" | | 4 | "Her green eyes were sharp" | | 5 | "It was a man, mid-forties," | | 6 | "He was lying on his" | | 7 | "His face was slack, almost" | | 8 | "She pointed at the grey" | | 9 | "She walked over, nudged the" | | 10 | "It was old." | | 11 | "It seemed to be pointing" | | 12 | "She turned it over in" | | 13 | "Her fingers traced the edge" | | 14 | "She looked up, her eyes" | | 15 | "It was too clean." | | 16 | "She looked at the body" | | 17 | "She crouched again, closer this" | | 18 | "She reached out and gently" | | 19 | "She let the eyelid fall" |
| | ratio | 0.26 | |
| 46.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 104 | | matches | | 0 | "The air down here tasted" | | 1 | "Detective Harlow Quinn paused at" | | 2 | "Emergency lighting had been rigged" | | 3 | "She stepped over a coil" | | 4 | "The constable gestured with his" | | 5 | "Quinn didn’t bother asking who." | | 6 | "She walked past him, her" | | 7 | "The platform opened out before" | | 8 | "The old advertising boards along" | | 9 | "A train hadn’t run through" | | 10 | "Someone had died down here." | | 11 | "Eva Kowalski stood near the" | | 12 | "Her red curls were escaping" | | 13 | "She was tucking a strand" | | 14 | "Quinn’s voice carried in the" | | 15 | "Eva looked up." | | 16 | "Her green eyes were sharp" | | 17 | "Quinn stopped a few feet" | | 18 | "It was a man, mid-forties," | | 19 | "He was lying on his" |
| | ratio | 0.827 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 4.61% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 6 | | matches | | 0 | "Emergency lighting had been rigged along the tunnel—portable floods on tripods that cast hard shadows and made everything look like a crime scene photograph." | | 1 | "She walked past him, her boots crunching on debris—broken tile, a crushed polystyrene cup, something that might have been a bone token but she didn’t stoop to c…" | | 2 | "It was a man, mid-forties, dressed in a beige raincoat that looked expensive despite the grime." | | 3 | "Inside it, interlocking lines that seemed to move if she stared too long." | | 4 | "The casing was verdigris-green with age, and the face was etched with symbols that matched the sigil on the dead man’s chest—similar, but not identical." | | 5 | "She just kept walking, the Veil Compass heavy in her pocket, the dead man’s face burning in her memory." |
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| 5.95% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 5 | | matches | | 0 | "She looked up, her eyes sharp" | | 1 | "Quinn walked around, her eyes scanning the floor" | | 2 | "Quinn said, the pieces clicking into place" | | 3 | "She turned, her voice flat" | | 4 | "Quinn turned, her boots echoing in the hollow space" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 52 | | tagDensity | 0.115 | | leniency | 0.231 | | rawRatio | 0 | | effectiveRatio | 0 | |