| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.19 | | leniency | 0.381 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.66% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1498 | | 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) | |
| 93.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1498 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 79 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 79 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 113 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 130 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1498 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 861 | | uniqueNames | 10 | | maxNameDensity | 0.93 | | worstName | "Vickers" | | maxWindowNameDensity | 2 | | worstWindowName | "Vickers" | | discoveredNames | | Quinn | 4 | | Camden | 1 | | High | 1 | | Street | 1 | | Morris | 1 | | Ashgrove | 1 | | Victorian | 1 | | Vickers | 8 | | Okoye | 1 | | Easter | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Vickers" | | 3 | "Okoye" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Easter" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | 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 | 1498 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 113 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 25.83 | | std | 26.03 | | cv | 1.008 | | sampleLengths | | 0 | 29 | | 1 | 10 | | 2 | 59 | | 3 | 35 | | 4 | 38 | | 5 | 75 | | 6 | 14 | | 7 | 3 | | 8 | 16 | | 9 | 3 | | 10 | 67 | | 11 | 40 | | 12 | 5 | | 13 | 15 | | 14 | 6 | | 15 | 7 | | 16 | 4 | | 17 | 35 | | 18 | 23 | | 19 | 7 | | 20 | 11 | | 21 | 81 | | 22 | 27 | | 23 | 82 | | 24 | 19 | | 25 | 5 | | 26 | 17 | | 27 | 30 | | 28 | 3 | | 29 | 38 | | 30 | 3 | | 31 | 49 | | 32 | 46 | | 33 | 30 | | 34 | 6 | | 35 | 21 | | 36 | 7 | | 37 | 15 | | 38 | 3 | | 39 | 3 | | 40 | 26 | | 41 | 9 | | 42 | 16 | | 43 | 2 | | 44 | 88 | | 45 | 12 | | 46 | 14 | | 47 | 129 | | 48 | 6 | | 49 | 40 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 79 | | matches | (empty) | |
| 89.81% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 121 | | matches | | 0 | "were exhaling" | | 1 | "was breathing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 113 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 781 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.023047375160051217 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0012804097311139564 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 113 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 113 | | mean | 13.26 | | std | 14.58 | | cv | 1.1 | | sampleLengths | | 0 | 29 | | 1 | 10 | | 2 | 8 | | 3 | 28 | | 4 | 7 | | 5 | 16 | | 6 | 20 | | 7 | 15 | | 8 | 14 | | 9 | 10 | | 10 | 14 | | 11 | 3 | | 12 | 40 | | 13 | 17 | | 14 | 15 | | 15 | 14 | | 16 | 3 | | 17 | 16 | | 18 | 3 | | 19 | 38 | | 20 | 29 | | 21 | 8 | | 22 | 17 | | 23 | 3 | | 24 | 12 | | 25 | 5 | | 26 | 8 | | 27 | 7 | | 28 | 6 | | 29 | 7 | | 30 | 4 | | 31 | 8 | | 32 | 27 | | 33 | 23 | | 34 | 4 | | 35 | 3 | | 36 | 11 | | 37 | 15 | | 38 | 7 | | 39 | 17 | | 40 | 25 | | 41 | 4 | | 42 | 13 | | 43 | 5 | | 44 | 22 | | 45 | 23 | | 46 | 23 | | 47 | 36 | | 48 | 14 | | 49 | 5 |
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| 82.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5398230088495575 | | totalSentences | 113 | | uniqueOpeners | 61 | |
| 88.89% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 75 | | matches | | 0 | "More of them stood in" | | 1 | "Then, softer than before," |
| | ratio | 0.027 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 75 | | matches | | 0 | "She gave him a nod" | | 1 | "She filed that away and" | | 2 | "His right hand lay open" | | 3 | "He nodded toward the alcove" | | 4 | "She left him with that" | | 5 | "It thickened toward the third" | | 6 | "She toed a clean rectangle" | | 7 | "She pushed the glasses up" | | 8 | "She tucked a curl behind" | | 9 | "She turned the bag a" | | 10 | "She walked ten paces down" | | 11 | "She stared through the plastic." | | 12 | "She lifted the bag with" | | 13 | "She looked at the arch," | | 14 | "She set the bag down" | | 15 | "She turned to the bricked" | | 16 | "She borrowed Vickers's lighter and" | | 17 | "She rapped the brick with" | | 18 | "She checked her left wrist" | | 19 | "She wound that watch every" |
| | ratio | 0.267 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 75 | | matches | | 0 | "The service gate stood open" | | 1 | "She gave him a nod" | | 2 | "The stair unwound through brick" | | 3 | "The last time she'd felt" | | 4 | "She filed that away and" | | 5 | "The station had closed before" | | 6 | "Generator lamps on stands washed" | | 7 | "Halfway along, beneath the second" | | 8 | "Someone had opened his throat" | | 9 | "His right hand lay open" | | 10 | "DS Vickers stood over the" | | 11 | "He nodded toward the alcove" | | 12 | "Quinn crouched at the edge" | | 13 | "Dust lay a finger thick" | | 14 | "A SOCO lifted each boot" | | 15 | "Grit, edge to edge, toe" | | 16 | "Dr Okoye, the pathologist, knelt" | | 17 | "Vickers drank his coffee." | | 18 | "She left him with that" | | 19 | "The cold had a shape" |
| | ratio | 0.8 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 75 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "All of it, brick and behind it more brick, and still the flame leaned away as though the wall were exhaling." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 42 | | tagDensity | 0.024 | | leniency | 0.048 | | rawRatio | 0 | | effectiveRatio | 0 | |