| 49.06% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 4 | | adverbTags | | 0 | "Harlow stepped back [back]" | | 1 | "Harlow crouched again [again]" | | 2 | "Harlow turned back [back]" | | 3 | "Harlow walked back [back]" |
| | dialogueSentences | 53 | | tagDensity | 0.321 | | leniency | 0.642 | | rawRatio | 0.235 | | effectiveRatio | 0.151 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1289 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 61.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1289 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "shattered" | | 1 | "gloom" | | 2 | "scanning" | | 3 | "chill" | | 4 | "weight" | | 5 | "etched" | | 6 | "traced" | | 7 | "echoing" |
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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 | 53 | | matches | (empty) | |
| 88.95% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 53 | | filterMatches | | | hedgeMatches | (empty) | |
| 95.70% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 1 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0.011 | | matches | | 0 | "\"Monsters do not have bank accounts. Monsters do not leave fingerprints. Monsters do not inherit Thorne's alchemical supply chain.\"" |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1289 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 526 | | uniqueNames | 8 | | maxNameDensity | 3.42 | | worstName | "Harlow" | | maxWindowNameDensity | 5 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Veil | 2 | | Market | 1 | | Kowalski | 1 | | Harlow | 18 | | Eva | 12 | | Compass | 1 |
| | persons | | 0 | "Market" | | 1 | "Kowalski" | | 2 | "Harlow" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 1289 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 26.85 | | std | 19.96 | | cv | 0.743 | | sampleLengths | | 0 | 52 | | 1 | 44 | | 2 | 5 | | 3 | 10 | | 4 | 19 | | 5 | 35 | | 6 | 50 | | 7 | 46 | | 8 | 28 | | 9 | 6 | | 10 | 7 | | 11 | 25 | | 12 | 13 | | 13 | 1 | | 14 | 34 | | 15 | 4 | | 16 | 55 | | 17 | 12 | | 18 | 9 | | 19 | 64 | | 20 | 37 | | 21 | 30 | | 22 | 9 | | 23 | 43 | | 24 | 12 | | 25 | 39 | | 26 | 9 | | 27 | 14 | | 28 | 43 | | 29 | 4 | | 30 | 57 | | 31 | 5 | | 32 | 6 | | 33 | 70 | | 34 | 29 | | 35 | 47 | | 36 | 18 | | 37 | 14 | | 38 | 35 | | 39 | 7 | | 40 | 44 | | 41 | 9 | | 42 | 66 | | 43 | 13 | | 44 | 8 | | 45 | 65 | | 46 | 16 | | 47 | 21 |
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| 78.78% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 53 | | matches | | 0 | "was shredded" | | 1 | "were blackened" | | 2 | "were blistered" | | 3 | "was etched" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 93 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 89 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 526 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.015209125475285171 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0038022813688212928 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 14.48 | | std | 9.6 | | cv | 0.663 | | sampleLengths | | 0 | 6 | | 1 | 12 | | 2 | 13 | | 3 | 9 | | 4 | 12 | | 5 | 13 | | 6 | 11 | | 7 | 20 | | 8 | 5 | | 9 | 10 | | 10 | 19 | | 11 | 19 | | 12 | 16 | | 13 | 11 | | 14 | 12 | | 15 | 6 | | 16 | 9 | | 17 | 12 | | 18 | 10 | | 19 | 36 | | 20 | 2 | | 21 | 10 | | 22 | 6 | | 23 | 10 | | 24 | 6 | | 25 | 7 | | 26 | 21 | | 27 | 4 | | 28 | 13 | | 29 | 1 | | 30 | 34 | | 31 | 4 | | 32 | 24 | | 33 | 6 | | 34 | 25 | | 35 | 12 | | 36 | 9 | | 37 | 51 | | 38 | 8 | | 39 | 5 | | 40 | 17 | | 41 | 7 | | 42 | 13 | | 43 | 4 | | 44 | 7 | | 45 | 19 | | 46 | 9 | | 47 | 19 | | 48 | 4 | | 49 | 14 |
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| 63.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.42696629213483145 | | totalSentences | 89 | | uniqueOpeners | 38 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 52 | | matches | | 0 | "Her worn leather satchel rested" | | 1 | "She pushed her round glasses" | | 2 | "She maintained a rigid posture," | | 3 | "His expensive wool coat was" | | 4 | "She leaned close to the" | | 5 | "She stared at the parallel" | | 6 | "It did not waver." | | 7 | "She traced the compass trajectory" | | 8 | "She ran her fingers over" |
| | ratio | 0.173 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 52 | | matches | | 0 | "Harlow stepped over the shattered" | | 1 | "The abandoned Camden Tube station" | | 2 | "Police tape sliced through the" | | 3 | "Eva Kowalski crouched beside a" | | 4 | "Her worn leather satchel rested" | | 5 | "She pushed her round glasses" | | 6 | "Harlow checked the worn leather" | | 7 | "Eva pointed a torch at" | | 8 | "Harlow approached, her boots crunching" | | 9 | "She maintained a rigid posture," | | 10 | "The victim lay on his" | | 11 | "His expensive wool coat was" | | 12 | "Eva shone the beam directly" | | 13 | "The damp chill of the" | | 14 | "She leaned close to the" | | 15 | "The edges of the torn" | | 16 | "Harlow stood and swept her" | | 17 | "Eva blinked, her freckled complexion" | | 18 | "Harlow stepped back, her sharp" | | 19 | "She stared at the parallel" |
| | ratio | 0.942 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 52 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 66.18% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 2 | | matches | | 0 | "Harlow stepped back, her sharp jaw tightening" | | 1 | "Harlow turned, her boots echoing against the vaulted ceiling" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 53 | | tagDensity | 0.019 | | leniency | 0.038 | | rawRatio | 1 | | effectiveRatio | 0.038 | |