| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 61.83% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 524 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "softly" | | 1 | "really" | | 2 | "slightly" | | 3 | "slowly" |
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| 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) | |
| 42.75% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 524 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "footsteps" | | 1 | "pulse" | | 2 | "reminder" | | 3 | "glinting" | | 4 | "echoed" | | 5 | "looming" |
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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 | 59 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 59 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 64 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 519 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.50% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 480 | | uniqueNames | 12 | | maxNameDensity | 1.25 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Harlow" | | discoveredNames | | Quinn | 1 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Morris | 2 | | Harlow | 6 | | Tomás | 3 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Saint" | | 3 | "Christopher" | | 4 | "Herrera" | | 5 | "Market" | | 6 | "Morris" | | 7 | "Harlow" | | 8 | "Tomás" |
| | places | (empty) | | globalScore | 0.875 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | 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 | 519 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 32 | | mean | 16.22 | | std | 15.99 | | cv | 0.986 | | sampleLengths | | 0 | 57 | | 1 | 46 | | 2 | 45 | | 3 | 9 | | 4 | 59 | | 5 | 5 | | 6 | 34 | | 7 | 7 | | 8 | 9 | | 9 | 11 | | 10 | 13 | | 11 | 13 | | 12 | 12 | | 13 | 10 | | 14 | 4 | | 15 | 31 | | 16 | 6 | | 17 | 38 | | 18 | 21 | | 19 | 11 | | 20 | 10 | | 21 | 8 | | 22 | 3 | | 23 | 10 | | 24 | 8 | | 25 | 6 | | 26 | 12 | | 27 | 4 | | 28 | 6 | | 29 | 3 | | 30 | 4 | | 31 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 59 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 91 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 64 | | ratio | 0.063 | | matches | | 0 | "Ahead, the figure in the dark hoodie darted around a corner—too fast for an ordinary civilian." | | 1 | "Military training kicked in—she gauged the distance, planted a foot on the wet wood, and hauled herself over." | | 2 | "The hooded figure bolted left, toward the flickering green glow of a neon sign—The Raven’s Nest." | | 3 | "Voices echoed up from below—hushed, urgent." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 485 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.0288659793814433 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.008247422680412371 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 64 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 64 | | mean | 8.11 | | std | 4.8 | | cv | 0.591 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 16 | | 3 | 8 | | 4 | 16 | | 5 | 12 | | 6 | 18 | | 7 | 11 | | 8 | 16 | | 9 | 3 | | 10 | 15 | | 11 | 5 | | 12 | 4 | | 13 | 10 | | 14 | 7 | | 15 | 15 | | 16 | 16 | | 17 | 11 | | 18 | 5 | | 19 | 12 | | 20 | 16 | | 21 | 2 | | 22 | 2 | | 23 | 2 | | 24 | 7 | | 25 | 9 | | 26 | 5 | | 27 | 6 | | 28 | 11 | | 29 | 2 | | 30 | 9 | | 31 | 4 | | 32 | 6 | | 33 | 6 | | 34 | 2 | | 35 | 8 | | 36 | 4 | | 37 | 9 | | 38 | 14 | | 39 | 8 | | 40 | 6 | | 41 | 7 | | 42 | 17 | | 43 | 11 | | 44 | 3 | | 45 | 7 | | 46 | 14 | | 47 | 11 | | 48 | 2 | | 49 | 4 |
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| 76.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.484375 | | totalSentences | 64 | | uniqueOpeners | 31 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 54 | | matches | | 0 | "Too fast for someone who" | | 1 | "Slowly, they turned." |
| | ratio | 0.037 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 54 | | matches | | 0 | "She skidded around the bend," | | 1 | "She pushed harder, lungs burning." | | 2 | "She caught it with her" | | 3 | "His dark curls were damp" | | 4 | "He didn’t look up" | | 5 | "His fingers tapped the glass." | | 6 | "She stepped closer, rain dripping" | | 7 | "She was already moving." | | 8 | "Her target was halfway across" | | 9 | "She stepped forward." | | 10 | "She didn’t look back." | | 11 | "Her breath caught." | | 12 | "It wasn’t a suspect." | | 13 | "It was DS Morris." |
| | ratio | 0.259 | |
| 34.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 46 | | totalSentences | 54 | | matches | | 0 | "The rain hammered against the" | | 1 | "Harlow Quinn sprinted down the" | | 2 | "She skidded around the bend," | | 3 | "The hooded figure vaulted over" | | 4 | "Military training kicked in—she gauged" | | 5 | "The alley opened onto a" | | 6 | "The hooded figure bolted left," | | 7 | "Harlow’s pulse spiked." | | 8 | "That bar had come up" | | 9 | "She pushed harder, lungs burning." | | 10 | "The suspect ducked inside." | | 11 | "The door swung shut behind" | | 12 | "She caught it with her" | | 13 | "The worn leather watch on" | | 14 | "Maps and photographs covered the" | | 15 | "A man leaned against the" | | 16 | "His dark curls were damp" | | 17 | "He didn’t look up" | | 18 | "His fingers tapped the glass." | | 19 | "She stepped closer, rain dripping" |
| | ratio | 0.852 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 1 | | matches | | 0 | "Harlow Quinn sprinted down the alley, her boots splashing through puddles that swallowed the sound of her footsteps." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "a voice murmured (murmur)" |
| | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 1 | | effectiveRatio | 0.286 | |