| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.97% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1241 | | 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) | |
| 43.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1241 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "calculated" | | 1 | "footsteps" | | 2 | "weight" | | 3 | "furrowed" | | 4 | "tracing" | | 5 | "chill" | | 6 | "stomach" | | 7 | "etched" | | 8 | "scanned" | | 9 | "gloom" | | 10 | "firmly" | | 11 | "velvet" | | 12 | "crystal" |
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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 | 1 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1239 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 64.02% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 756 | | uniqueNames | 8 | | maxNameDensity | 1.72 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Victorian | 1 | | Camden | 2 | | Quinn | 13 | | Constable | 1 | | Christopher | 1 | | Ward | 11 | | Morris | 1 | | Maglite | 1 |
| | persons | | | places | | 0 | "Constable" | | 1 | "Christopher" |
| | globalScore | 0.64 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1239 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 18.49 | | std | 14.06 | | cv | 0.76 | | sampleLengths | | 0 | 25 | | 1 | 52 | | 2 | 26 | | 3 | 10 | | 4 | 14 | | 5 | 30 | | 6 | 30 | | 7 | 14 | | 8 | 19 | | 9 | 48 | | 10 | 4 | | 11 | 5 | | 12 | 3 | | 13 | 3 | | 14 | 11 | | 15 | 39 | | 16 | 11 | | 17 | 11 | | 18 | 11 | | 19 | 23 | | 20 | 17 | | 21 | 21 | | 22 | 9 | | 23 | 26 | | 24 | 24 | | 25 | 21 | | 26 | 27 | | 27 | 20 | | 28 | 7 | | 29 | 7 | | 30 | 60 | | 31 | 12 | | 32 | 12 | | 33 | 11 | | 34 | 17 | | 35 | 43 | | 36 | 33 | | 37 | 14 | | 38 | 6 | | 39 | 4 | | 40 | 2 | | 41 | 44 | | 42 | 4 | | 43 | 2 | | 44 | 2 | | 45 | 32 | | 46 | 10 | | 47 | 32 | | 48 | 2 | | 49 | 35 |
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| 93.76% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 61 | | matches | | 0 | "was emptied" | | 1 | "been wiped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 109 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 95 | | ratio | 0.011 | | matches | | 0 | "Sigils—sharp, geometric incisions cut deep into the brass—ringed the glass face." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 769 | | adjectiveStacks | 2 | | stackExamples | | 0 | "same sterile, metallic ozone" | | 1 | "ancient, velvet-thick skin" |
| | adverbCount | 12 | | adverbRatio | 0.015604681404421327 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005201560468140442 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 13.04 | | std | 8.37 | | cv | 0.642 | | sampleLengths | | 0 | 13 | | 1 | 12 | | 2 | 19 | | 3 | 10 | | 4 | 7 | | 5 | 16 | | 6 | 19 | | 7 | 7 | | 8 | 10 | | 9 | 14 | | 10 | 30 | | 11 | 6 | | 12 | 14 | | 13 | 10 | | 14 | 14 | | 15 | 19 | | 16 | 5 | | 17 | 11 | | 18 | 25 | | 19 | 7 | | 20 | 4 | | 21 | 5 | | 22 | 3 | | 23 | 3 | | 24 | 11 | | 25 | 39 | | 26 | 11 | | 27 | 11 | | 28 | 11 | | 29 | 23 | | 30 | 17 | | 31 | 21 | | 32 | 9 | | 33 | 26 | | 34 | 18 | | 35 | 6 | | 36 | 21 | | 37 | 27 | | 38 | 3 | | 39 | 17 | | 40 | 7 | | 41 | 7 | | 42 | 19 | | 43 | 26 | | 44 | 2 | | 45 | 13 | | 46 | 4 | | 47 | 8 | | 48 | 12 | | 49 | 11 |
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| 57.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3684210526315789 | | totalSentences | 95 | | uniqueOpeners | 35 | |
| 58.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 57 | | matches | | 0 | "Just a three-foot span of" |
| | ratio | 0.018 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 57 | | matches | | 0 | "She adjusted the worn leather" | | 1 | "His breath plumed in the" | | 2 | "Her sharp jaw tightened as" | | 3 | "She snapped a pair of" | | 4 | "She shone her penlight across" | | 5 | "Her beam swept in a" | | 6 | "She checked the inner breast" | | 7 | "She withdrew a crisp stack" | | 8 | "He pinched the bridge of" | | 9 | "She touched the steel." | | 10 | "Her voice stayed flat, stripped" | | 11 | "Her fingers brushed against something" | | 12 | "She extracted it carefully." | | 13 | "She scanned the gloom beyond" | | 14 | "She walked toward the frost-slicked" | | 15 | "Her gloved fingers pried the" | | 16 | "It was a small brass" |
| | ratio | 0.298 | |
| 21.40% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 50 | | totalSentences | 57 | | matches | | 0 | "Halogen floodlights hummed against the" | | 1 | "The tunnel air tasted of" | | 2 | "Harlow Quinn descended the spiral" | | 3 | "She adjusted the worn leather" | | 4 | "Detective Constable Christopher Ward stood" | | 5 | "His breath plumed in the" | | 6 | "Ward nudged a rusted bolt" | | 7 | "Quinn bypassed him without breaking" | | 8 | "Her sharp jaw tightened as" | | 9 | "She snapped a pair of" | | 10 | "Quinn crouched beside the corpse." | | 11 | "The victim lay face-up, eyes" | | 12 | "The impact to the left" | | 13 | "She shone her penlight across" | | 14 | "Ward leaned over, eyebrows furrowed." | | 15 | "Her beam swept in a" | | 16 | "Ward pointed to the dark" | | 17 | "Quinn leaned closer, the beam" | | 18 | "The cream-colored ceramic behind the" | | 19 | "Ward shifted his weight, jaw" |
| | ratio | 0.877 | |
| 87.72% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 57 | | matches | | 0 | "While the ambient air hung" |
| | ratio | 0.018 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 1 | | matches | | 0 | "She scanned the gloom beyond the perimeter lamps, toward the tunnel mouth that curved north under the market stalls of Camden." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |