| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.242 | | leniency | 0.485 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 990 | | totalAiIsmAdverbs | 3 | | 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) | |
| 19.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 990 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "clandestine" | | 1 | "echoed" | | 2 | "silence" | | 3 | "glinting" | | 4 | "crystal" | | 5 | "shattered" | | 6 | "echoing" | | 7 | "eyebrow" | | 8 | "intricate" | | 9 | "racing" | | 10 | "pounding" | | 11 | "grave" | | 12 | "weight" |
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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 | 2 | | narrationSentences | 84 | | matches | | 0 | "d with fear" | | 1 | "e with terror" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 84 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 986 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 728 | | uniqueNames | 12 | | maxNameDensity | 2.47 | | worstName | "Harlow" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Harlow" | | discoveredNames | | London | 1 | | Tube | 1 | | Detective | 1 | | Harlow | 18 | | Quinn | 1 | | Veil | 2 | | Market | 1 | | Davies | 11 | | Compass | 1 | | Eva | 6 | | Kowalski | 1 | | Aurora | 4 |
| | persons | | 0 | "Tube" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Davies" | | 4 | "Eva" | | 5 | "Kowalski" | | 6 | "Aurora" |
| | places | | | globalScore | 0.264 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 986 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 26.65 | | std | 13.45 | | cv | 0.505 | | sampleLengths | | 0 | 45 | | 1 | 56 | | 2 | 37 | | 3 | 47 | | 4 | 48 | | 5 | 15 | | 6 | 31 | | 7 | 13 | | 8 | 21 | | 9 | 9 | | 10 | 40 | | 11 | 7 | | 12 | 42 | | 13 | 42 | | 14 | 13 | | 15 | 33 | | 16 | 6 | | 17 | 19 | | 18 | 7 | | 19 | 17 | | 20 | 46 | | 21 | 12 | | 22 | 35 | | 23 | 11 | | 24 | 22 | | 25 | 22 | | 26 | 35 | | 27 | 34 | | 28 | 25 | | 29 | 23 | | 30 | 25 | | 31 | 16 | | 32 | 32 | | 33 | 19 | | 34 | 13 | | 35 | 31 | | 36 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 84 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 109 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 732 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.03551912568306011 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.01092896174863388 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 9.05 | | std | 5.39 | | cv | 0.596 | | sampleLengths | | 0 | 24 | | 1 | 21 | | 2 | 12 | | 3 | 12 | | 4 | 19 | | 5 | 13 | | 6 | 17 | | 7 | 9 | | 8 | 11 | | 9 | 4 | | 10 | 9 | | 11 | 15 | | 12 | 14 | | 13 | 5 | | 14 | 6 | | 15 | 12 | | 16 | 13 | | 17 | 11 | | 18 | 5 | | 19 | 1 | | 20 | 9 | | 21 | 6 | | 22 | 8 | | 23 | 10 | | 24 | 1 | | 25 | 2 | | 26 | 7 | | 27 | 3 | | 28 | 13 | | 29 | 17 | | 30 | 4 | | 31 | 3 | | 32 | 6 | | 33 | 4 | | 34 | 24 | | 35 | 12 | | 36 | 2 | | 37 | 5 | | 38 | 9 | | 39 | 12 | | 40 | 14 | | 41 | 5 | | 42 | 1 | | 43 | 1 | | 44 | 9 | | 45 | 9 | | 46 | 7 | | 47 | 7 | | 48 | 10 | | 49 | 6 |
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| 61.77% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.4036697247706422 | | totalSentences | 109 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 71.28% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 78 | | matches | | 0 | "he said, attempting nonchalance" | | 1 | "His eyes darted to the" | | 2 | "She'd earned her reputation for" | | 3 | "She pulled out her Veil" | | 4 | "She nudged it with her" | | 5 | "She coughed, her eyes watering." | | 6 | "She touched the stain, rubbed" | | 7 | "She looked up, her brown" | | 8 | "She stood, her sharp jaw" | | 9 | "She held up the small," | | 10 | "It hummed softly in her" | | 11 | "She passed stalls selling everything" | | 12 | "She paused, sniffing the air." | | 13 | "She followed the scent to" | | 14 | "She picked it up, examined" | | 15 | "She tucked it into an" | | 16 | "She pointed to the altar" | | 17 | "She touched the stain, then" | | 18 | "She moved towards the sound," | | 19 | "They rounded a corner, found" |
| | ratio | 0.372 | |
| 11.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 78 | | matches | | 0 | "The Veil Market, a clandestine" | | 1 | "The market's exit, a rusted" | | 2 | "Harlow's boots crunched on bone" | | 3 | "The air hung heavy with" | | 4 | "PC Davies, a lanky youth" | | 5 | "he said, attempting nonchalance" | | 6 | "His eyes darted to the" | | 7 | "Harlow ignored the jibe." | | 8 | "She'd earned her reputation for" | | 9 | "She pulled out her Veil" | | 10 | "The needle spun, then pointed" | | 11 | "The market's wares lay scattered," | | 12 | "A crystal ball rolled towards" | | 13 | "She nudged it with her" | | 14 | "A potion bottle shattered underfoot," | | 15 | "She coughed, her eyes watering." | | 16 | "Davies pointed to a dark" | | 17 | "Harlow crouched, her salt-and-pepper hair" | | 18 | "She touched the stain, rubbed" | | 19 | "She looked up, her brown" |
| | ratio | 0.897 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 78 | | matches | | 0 | "If Aurora had been here..." | | 1 | "if something had taken her..." |
| | ratio | 0.026 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 2 | | matches | | 0 | "The Veil Market, a clandestine bazaar of the supernatural, had moved on, leaving behind a scene that didn't quite add up." | | 1 | "She nudged it with her boot, sending it spinning back into the shadows." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 2 | | matches | | 0 | "Davies asked, his voice echoing in the vast space" | | 1 | "she said, her voice steady" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.121 | | leniency | 0.242 | | rawRatio | 0 | | effectiveRatio | 0 | |