| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.625 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.89% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 703 | | totalAiIsmAdverbs | 1 | | 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) | |
| 7.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 703 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "echoing" | | 1 | "chill" | | 2 | "could feel" | | 3 | "scanning" | | 4 | "glinting" | | 5 | "measured" | | 6 | "etched" | | 7 | "intricate" | | 8 | "pulsed" | | 9 | "racing" | | 10 | "reminder" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "heart pounded in chest" | | count | 1 |
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| | highlights | | 0 | "heart pounded in her chest" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 65 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 705 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 98.19% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 579 | | uniqueNames | 10 | | maxNameDensity | 1.04 | | worstName | "Thompson" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 5 | | Quinn | 1 | | Tube | 2 | | Detective | 2 | | Sergeant | 1 | | Thompson | 6 | | Eva | 2 | | Morris | 1 | | Veil | 1 | | Compass | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Thompson" | | 4 | "Eva" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.982 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 705 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 39.17 | | std | 19.99 | | cv | 0.51 | | sampleLengths | | 0 | 58 | | 1 | 45 | | 2 | 72 | | 3 | 15 | | 4 | 58 | | 5 | 25 | | 6 | 54 | | 7 | 40 | | 8 | 8 | | 9 | 17 | | 10 | 71 | | 11 | 17 | | 12 | 58 | | 13 | 11 | | 14 | 39 | | 15 | 27 | | 16 | 41 | | 17 | 49 |
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| 99.21% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 58 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 97 | | matches | (empty) | |
| 10.99% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 65 | | ratio | 0.046 | | matches | | 0 | "The air was damp, heavy with the scent of decay and something else - an acrid tang that pricked her nostrils." | | 1 | "A worn leather satchel lay beside her, its contents spilled - books, a notepad, a round pair of glasses." | | 2 | "A small, intricate tattoo on Eva's wrist - a symbol she'd seen before." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 414 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.021739130434782608 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.00966183574879227 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 65 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 65 | | mean | 10.85 | | std | 6.05 | | cv | 0.557 | | sampleLengths | | 0 | 17 | | 1 | 21 | | 2 | 12 | | 3 | 8 | | 4 | 15 | | 5 | 17 | | 6 | 13 | | 7 | 8 | | 8 | 18 | | 9 | 10 | | 10 | 19 | | 11 | 7 | | 12 | 10 | | 13 | 2 | | 14 | 13 | | 15 | 7 | | 16 | 3 | | 17 | 13 | | 18 | 13 | | 19 | 7 | | 20 | 4 | | 21 | 11 | | 22 | 8 | | 23 | 17 | | 24 | 4 | | 25 | 29 | | 26 | 9 | | 27 | 12 | | 28 | 13 | | 29 | 9 | | 30 | 11 | | 31 | 7 | | 32 | 5 | | 33 | 3 | | 34 | 10 | | 35 | 7 | | 36 | 14 | | 37 | 13 | | 38 | 6 | | 39 | 18 | | 40 | 20 | | 41 | 6 | | 42 | 6 | | 43 | 5 | | 44 | 8 | | 45 | 5 | | 46 | 10 | | 47 | 11 | | 48 | 10 | | 49 | 6 |
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| 53.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.36923076923076925 | | totalSentences | 65 | | uniqueOpeners | 24 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 57 | | matches | | | ratio | 0.018 | |
| 16.49% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 57 | | matches | | 0 | "She glanced at the peeling" | | 1 | "Her partner, Detective Sergeant Thompson," | | 2 | "He looked up as she" | | 3 | "he acknowledged, rubbing his gloved" | | 4 | "Her eyes were open, wide" | | 5 | "she murmured, recognition flickering in" | | 6 | "She could feel it, like" | | 7 | "She walked to the edge" | | 8 | "She turned, her eyes scanning" | | 9 | "Her gaze snagged on something" | | 10 | "She stepped towards it, her" | | 11 | "It was a compass, small" | | 12 | "She picked it up, turned" | | 13 | "She frowned, tucked it into" | | 14 | "she said, her voice low" | | 15 | "She turned back to the" | | 16 | "She crouched down, examined it" | | 17 | "It was a sigil, one" | | 18 | "Her heart pounded in her" | | 19 | "She stood, her eyes scanning" |
| | ratio | 0.509 | |
| 3.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 57 | | matches | | 0 | "Detective Harlow Quinn stepped onto" | | 1 | "The air was damp, heavy" | | 2 | "She glanced at the peeling" | | 3 | "Camden's forgotten underbelly, now a" | | 4 | "Her partner, Detective Sergeant Thompson," | | 5 | "He looked up as she" | | 6 | "he acknowledged, rubbing his gloved" | | 7 | "Harlow crouched beside him, her" | | 8 | "The victim was a young" | | 9 | "Her eyes were open, wide" | | 10 | "A worn leather satchel lay" | | 11 | "Harlow picked up the glasses," | | 12 | "she murmured, recognition flickering in" | | 13 | "Harlow stood, her gaze sweeping" | | 14 | "Something was off." | | 15 | "She could feel it, like" | | 16 | "She walked to the edge" | | 17 | "Thompson suggested, following her gaze" | | 18 | "Harlow shook her head." | | 19 | "She turned, her eyes scanning" |
| | ratio | 0.912 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 2 | | matches | | 0 | "The air was damp, heavy with the scent of decay and something else - an acrid tang that pricked her nostrils." | | 1 | "The station fell silent, the only sound the distant rumble of the Tube, a reminder of the world above, a world that knew nothing of the darkness lurking beneath…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 5 | | matches | | 0 | "she murmured, recognition flickering in her brown eyes" | | 1 | "She turned, her eyes scanning the station again" | | 2 | "she said, her voice low" | | 3 | "she said, her voice steady despite the adrenaline coursing through her veins" | | 4 | "She paused, her gaze flicking back to the rift" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 3 | | fancyTags | | 0 | "he acknowledged (acknowledge)" | | 1 | "she murmured (murmur)" | | 2 | "Thompson suggested (suggest)" |
| | dialogueSentences | 16 | | tagDensity | 0.438 | | leniency | 0.875 | | rawRatio | 0.429 | | effectiveRatio | 0.375 | |