| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 75.19% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 806 | | totalAiIsmAdverbs | 4 | | 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) | |
| 13.15% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 806 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "stark" | | 1 | "standard" | | 2 | "scanning" | | 3 | "oppressive" | | 4 | "silence" | | 5 | "tracing" | | 6 | "furrowed" | | 7 | "etched" | | 8 | "sinister" | | 9 | "warmth" | | 10 | "encounter" | | 11 | "racing" | | 12 | "determined" |
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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 | 33 | | matches | (empty) | |
| 99.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 33 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 41 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 85 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 800 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 495 | | uniqueNames | 9 | | maxNameDensity | 1.62 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Tubestation | 1 | | Harlow | 1 | | Quinn | 8 | | Veil | 2 | | Market | 2 | | Camden | 1 | | Detective | 4 | | Eva | 6 | | Kowalski | 1 |
| | persons | | 0 | "Tubestation" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Market" | | 4 | "Detective" | | 5 | "Eva" | | 6 | "Kowalski" |
| | places | (empty) | | globalScore | 0.692 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 2.5 | | wordCount | 800 | | matches | | 0 | "not north, but directly towards a spot near the edge of the pit" | | 1 | "Not just a human witness, but a supernatural one" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 41 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 12 | | mean | 66.67 | | std | 34.87 | | cv | 0.523 | | sampleLengths | | 0 | 130 | | 1 | 105 | | 2 | 69 | | 3 | 58 | | 4 | 33 | | 5 | 85 | | 6 | 24 | | 7 | 90 | | 8 | 18 | | 9 | 97 | | 10 | 23 | | 11 | 68 |
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| 62.73% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 33 | | matches | | 0 | "was known" | | 1 | "was etched" | | 2 | "was fixed" | | 3 | "was determined" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 76 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 41 | | ratio | 0.073 | | matches | | 0 | "The air in the abandoned Tubestation hung thick and cold, smelling of damp stone and something else—rotting earth, perhaps, or the faint, metallic tang of something ancient and hungry." | | 1 | "The only evidence was a single, discarded bone token—a small, polished rib bone—lying half-buried in the mud beside the body." | | 2 | "This pit, hidden beneath the Camden line, was one such entrance, accessible only by a bone token—a relic from some forgotten ritual." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 501 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.03592814371257485 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01996007984031936 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 41 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 41 | | mean | 19.51 | | std | 14.81 | | cv | 0.759 | | sampleLengths | | 0 | 29 | | 1 | 15 | | 2 | 17 | | 3 | 17 | | 4 | 22 | | 5 | 10 | | 6 | 20 | | 7 | 13 | | 8 | 6 | | 9 | 19 | | 10 | 18 | | 11 | 8 | | 12 | 19 | | 13 | 22 | | 14 | 20 | | 15 | 15 | | 16 | 16 | | 17 | 18 | | 18 | 18 | | 19 | 40 | | 20 | 10 | | 21 | 23 | | 22 | 3 | | 23 | 16 | | 24 | 18 | | 25 | 29 | | 26 | 19 | | 27 | 3 | | 28 | 21 | | 29 | 10 | | 30 | 14 | | 31 | 66 | | 32 | 8 | | 33 | 10 | | 34 | 12 | | 35 | 85 | | 36 | 11 | | 37 | 12 | | 38 | 14 | | 39 | 33 | | 40 | 21 |
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| 69.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.4146341463414634 | | totalSentences | 41 | | uniqueOpeners | 17 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 62.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 33 | | matches | | 0 | "Her worn leather watch ticked" | | 1 | "She stood at the edge" | | 2 | "Her military precision dictated every" | | 3 | "She ran a gloved hand" | | 4 | "She straightened, her eyes scanning" | | 5 | "Her partner, Detective Eva Kowalski," | | 6 | "She clutched a worn leather" | | 7 | "She adjusted her glasses, her" | | 8 | "she murmured, pulling the small" | | 9 | "Its face was etched with" | | 10 | "She flipped it open, the" | | 11 | "She ran a finger over" | | 12 | "She tucked the compass away," |
| | ratio | 0.394 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 32 | | totalSentences | 33 | | matches | | 0 | "The air in the abandoned" | | 1 | "Detective Harlow Quinn’s breath misted" | | 2 | "Her worn leather watch ticked" | | 3 | "She stood at the edge" | | 4 | "The victim, a young man" | | 5 | "The only evidence was a" | | 6 | "Detective Quinn crouched, her sharp" | | 7 | "Her military precision dictated every" | | 8 | "She ran a gloved hand" | | 9 | "The bullet, recovered from the" | | 10 | "She straightened, her eyes scanning" | | 11 | "The Veil Market was known" | | 12 | "This pit, hidden beneath the" | | 13 | "Her partner, Detective Eva Kowalski," | | 14 | "She clutched a worn leather" | | 15 | "Eva’s freckled complexion was pale," | | 16 | "She adjusted her glasses, her" | | 17 | "Quinn stated, her voice low" | | 18 | "Eva nodded, her fingers tracing" | | 19 | "Quinn’s brow furrowed." |
| | ratio | 0.97 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 33 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 25 | | technicalSentenceCount | 1 | | matches | | 0 | "The Veil Market was known for its secrets, its hidden entrances, and its clientele who dealt in the forbidden." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "Quinn stated, her voice low and controlled, cutting through the oppressive silence" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn stated (state)" | | 1 | "she murmured (murmur)" |
| | dialogueSentences | 11 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 1 | | effectiveRatio | 0.364 | |