| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "She stepped fully [fully]" |
| | dialogueSentences | 21 | | tagDensity | 0.524 | | leniency | 1 | | rawRatio | 0.091 | | effectiveRatio | 0.091 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1071 | | 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) | |
| 25.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1071 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "fractured" | | 1 | "echo" | | 2 | "pulse" | | 3 | "navigated" | | 4 | "footsteps" | | 5 | "structure" | | 6 | "traced" | | 7 | "rhythmic" | | 8 | "vibrated" | | 9 | "wavering" | | 10 | "echoed" | | 11 | "velvet" | | 12 | "etched" | | 13 | "measured" | | 14 | "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 | 0 | | narrationSentences | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 96 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1071 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 885 | | uniqueNames | 10 | | maxNameDensity | 1.36 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Harlow | 1 | | Quinn | 12 | | Edison | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Edison" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.822 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | 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 | 1071 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 44.63 | | std | 25.35 | | cv | 0.568 | | sampleLengths | | 0 | 94 | | 1 | 62 | | 2 | 12 | | 3 | 29 | | 4 | 77 | | 5 | 82 | | 6 | 52 | | 7 | 6 | | 8 | 78 | | 9 | 60 | | 10 | 5 | | 11 | 33 | | 12 | 24 | | 13 | 52 | | 14 | 63 | | 15 | 13 | | 16 | 54 | | 17 | 34 | | 18 | 38 | | 19 | 72 | | 20 | 39 | | 21 | 7 | | 22 | 37 | | 23 | 48 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 154 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 106 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 891 | | adjectiveStacks | 2 | | stackExamples | | 0 | "unknown pressing against her" | | 1 | "heavy, lead-lined bags." |
| | adverbCount | 20 | | adverbRatio | 0.02244668911335578 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007856341189674524 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 10.1 | | std | 6.61 | | cv | 0.654 | | sampleLengths | | 0 | 14 | | 1 | 22 | | 2 | 16 | | 3 | 8 | | 4 | 5 | | 5 | 13 | | 6 | 16 | | 7 | 14 | | 8 | 24 | | 9 | 4 | | 10 | 20 | | 11 | 9 | | 12 | 3 | | 13 | 5 | | 14 | 24 | | 15 | 7 | | 16 | 18 | | 17 | 4 | | 18 | 8 | | 19 | 15 | | 20 | 14 | | 21 | 10 | | 22 | 1 | | 23 | 2 | | 24 | 10 | | 25 | 8 | | 26 | 15 | | 27 | 16 | | 28 | 2 | | 29 | 20 | | 30 | 9 | | 31 | 16 | | 32 | 4 | | 33 | 9 | | 34 | 8 | | 35 | 2 | | 36 | 4 | | 37 | 9 | | 38 | 2 | | 39 | 4 | | 40 | 15 | | 41 | 16 | | 42 | 20 | | 43 | 16 | | 44 | 8 | | 45 | 3 | | 46 | 17 | | 47 | 4 | | 48 | 10 | | 49 | 12 |
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| 60.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3867924528301887 | | totalSentences | 106 | | uniqueOpeners | 41 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 88 | | matches | | 0 | "Then at the man." | | 1 | "Then the other." |
| | ratio | 0.023 | |
| 79.09% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 88 | | matches | | 0 | "She kept her left hand" | | 1 | "Her lungs burned, but the" | | 2 | "She moved with military precision," | | 3 | "He navigated the obstacles with" | | 4 | "She pivoted around a parked" | | 5 | "she barked, voice cutting through" | | 6 | "He vaulted a low brick" | | 7 | "She hauled herself over, gravel" | | 8 | "She pulled a torch from" | | 9 | "She traced the outline of" | | 10 | "She hadn’t come this far" | | 11 | "He finally looked up." | | 12 | "His eyes caught the light," | | 13 | "She stepped fully into the" | | 14 | "He tapped the carved object" | | 15 | "Her eyes tracked the items" | | 16 | "He leaned forward, resting his" | | 17 | "He gestured to the stalls" | | 18 | "Her hand hovered near her" | | 19 | "He slid the bone token" |
| | ratio | 0.352 | |
| 11.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 88 | | matches | | 0 | "Detective Harlow Quinn matched her" | | 1 | "She kept her left hand" | | 2 | "The metal ticked in time" | | 3 | "Her lungs burned, but the" | | 4 | "She moved with military precision," | | 5 | "The suspect darted past a" | | 6 | "He navigated the obstacles with" | | 7 | "Quinn didn’t break step." | | 8 | "She pivoted around a parked" | | 9 | "she barked, voice cutting through" | | 10 | "The man didn’t glance back." | | 11 | "He vaulted a low brick" | | 12 | "Quinn reached the wall a" | | 13 | "She hauled herself over, gravel" | | 14 | "The air shifted instantly." | | 15 | "The drumming rain faded into" | | 16 | "She pulled a torch from" | | 17 | "A faded sign hung crookedly" | | 18 | "Each step carried her deeper" | | 19 | "The damp air clung to" |
| | ratio | 0.898 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 2 | | matches | | 0 | "Detective Harlow Quinn matched her stride to the drumming water, boots splashing through deep puddles that swallowed the echo of her pursuit." | | 1 | "He navigated the obstacles with practiced efficiency, weaving through alleyways and narrow footpaths with the familiarity of someone who knew which doors stayed…" |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "she barked, voice cutting through the downpour" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 21 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.333 | | effectiveRatio | 0.095 | |