| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 1 | | adverbTags | | 0 | "Carter gestured vaguely [vaguely]" |
| | dialogueSentences | 15 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.333 | | effectiveRatio | 0.133 | |
| 92.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 638 | | 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) | |
| 29.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 638 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "gloom" | | 1 | "fluttered" | | 2 | "stomach" | | 3 | "pulse" | | 4 | "chill" | | 5 | "glinting" | | 6 | "etched" | | 7 | "unreadable" | | 8 | "whisper" |
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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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 7 | | totalWords | 629 | | ratio | 0.011 | | matches | | 0 | "Camden Road" | | 1 | "wrong" | | 2 | "surgical" | | 3 | "dried" | | 4 | "them" | | 5 | "inside" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 45.64% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 527 | | uniqueNames | 6 | | maxNameDensity | 2.09 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Harlow" | | discoveredNames | | Tube | 1 | | Harlow | 11 | | Quinn | 1 | | Carter | 9 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Carter" |
| | places | | | globalScore | 0.456 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 41.02% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.59 | | wordCount | 629 | | matches | | 0 | "not at the exit, but deeper into the station" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 73 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 20.29 | | std | 16.69 | | cv | 0.823 | | sampleLengths | | 0 | 52 | | 1 | 20 | | 2 | 47 | | 3 | 4 | | 4 | 2 | | 5 | 59 | | 6 | 17 | | 7 | 34 | | 8 | 5 | | 9 | 44 | | 10 | 7 | | 11 | 40 | | 12 | 6 | | 13 | 10 | | 14 | 13 | | 15 | 15 | | 16 | 15 | | 17 | 6 | | 18 | 18 | | 19 | 23 | | 20 | 59 | | 21 | 18 | | 22 | 9 | | 23 | 24 | | 24 | 13 | | 25 | 18 | | 26 | 27 | | 27 | 4 | | 28 | 2 | | 29 | 12 | | 30 | 6 |
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| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 61 | | matches | | 0 | "was draped" | | 1 | "been soaked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 86 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 73 | | ratio | 0.082 | | matches | | 0 | "The air smelled of damp concrete and something sharper—ozone, maybe, or the faint metallic tang of blood." | | 1 | "The station’s name—*Camden Road*—was peeling off the walls, the letters like a warning half-erased by time." | | 2 | "The coat smelled of burnt sugar and something older—something *wrong*." | | 3 | "And the blood—if it was blood—hadn’t pooled." | | 4 | "Then she noted the victim’s pockets—empty except for a single bone token, its surface smooth and unmarked." | | 5 | "Harlow’s flashlight caught something glinting on the ground—a brass compass, its casing etched with strange sigils." |
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| 97.38% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 535 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.04299065420560748 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009345794392523364 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 8.62 | | std | 5.45 | | cv | 0.632 | | sampleLengths | | 0 | 18 | | 1 | 17 | | 2 | 17 | | 3 | 13 | | 4 | 7 | | 5 | 3 | | 6 | 11 | | 7 | 17 | | 8 | 16 | | 9 | 4 | | 10 | 2 | | 11 | 4 | | 12 | 15 | | 13 | 27 | | 14 | 3 | | 15 | 10 | | 16 | 7 | | 17 | 10 | | 18 | 5 | | 19 | 9 | | 20 | 2 | | 21 | 2 | | 22 | 16 | | 23 | 5 | | 24 | 16 | | 25 | 7 | | 26 | 7 | | 27 | 14 | | 28 | 3 | | 29 | 4 | | 30 | 3 | | 31 | 11 | | 32 | 9 | | 33 | 17 | | 34 | 6 | | 35 | 6 | | 36 | 4 | | 37 | 7 | | 38 | 6 | | 39 | 4 | | 40 | 11 | | 41 | 12 | | 42 | 3 | | 43 | 5 | | 44 | 1 | | 45 | 7 | | 46 | 11 | | 47 | 7 | | 48 | 16 | | 49 | 19 |
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| 41.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.2876712328767123 | | totalSentences | 73 | | uniqueOpeners | 21 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 57 | | matches | | 0 | "Then she saw it." | | 1 | "Just the faintest chill radiating" | | 2 | "Then she saw the wound." | | 3 | "Then she noted the victim’s" | | 4 | "Then she heard it." |
| | ratio | 0.088 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 8 | | totalSentences | 57 | | matches | | 0 | "She was already moving, her" | | 1 | "She knelt, her gloved fingers" | | 2 | "It had *dried* in strange," | | 3 | "She was already reaching into" | | 4 | "Her fingers tightened around the" | | 5 | "She hadn’t expected this." | | 6 | "She didn’t answer." | | 7 | "She was already walking, the" |
| | ratio | 0.14 | |
| 65.26% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 57 | | matches | | 0 | "The rain drummed against the" | | 1 | "Detective Harlow Quinn crouched in" | | 2 | "The air smelled of damp" | | 3 | "Harlow didn’t answer." | | 4 | "She was already moving, her" | | 5 | "The crime scene tape fluttered" | | 6 | "The station’s name—*Camden Road*—was peeling" | | 7 | "This one was draped over" | | 8 | "The victim wore a long" | | 9 | "Harlow’s stomach twisted." | | 10 | "The coat smelled of burnt" | | 11 | "Carter crouched beside her, his" | | 12 | "Harlow didn’t look at him." | | 13 | "She knelt, her gloved fingers" | | 14 | "A neat, precise slash across" | | 15 | "The edges were too clean," | | 16 | "It had *dried* in strange," | | 17 | "Carter exhaled sharply." | | 18 | "Harlow didn’t answer." | | 19 | "She was already reaching into" |
| | ratio | 0.789 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "She was already reaching into her coat, pulling out her notebook." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 2 | | matches | | 0 | "muttered DS Carter beside her, his flashlight beam cutting through the gloom" | | 1 | "Carter said, his voice low" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "muttered DS Carter beside her (mutter)" |
| | dialogueSentences | 15 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 0.5 | | effectiveRatio | 0.133 | |