| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1225 | | 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) | |
| 75.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1225 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "echoed" | | 1 | "stark" | | 2 | "flicked" | | 3 | "etched" | | 4 | "traced" | | 5 | "scanned" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 90 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 90 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1227 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 30.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 709 | | uniqueNames | 6 | | maxNameDensity | 2.4 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Northern | 1 | | Quinn | 17 | | Camden | 1 | | Tube | 1 | | Pryce | 9 | | Eva | 6 |
| | persons | | | places | | | globalScore | 0.301 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1227 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 122 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 17.78 | | std | 12.59 | | cv | 0.708 | | sampleLengths | | 0 | 28 | | 1 | 39 | | 2 | 35 | | 3 | 23 | | 4 | 8 | | 5 | 27 | | 6 | 14 | | 7 | 32 | | 8 | 5 | | 9 | 9 | | 10 | 14 | | 11 | 36 | | 12 | 16 | | 13 | 7 | | 14 | 19 | | 15 | 23 | | 16 | 19 | | 17 | 7 | | 18 | 59 | | 19 | 12 | | 20 | 4 | | 21 | 1 | | 22 | 23 | | 23 | 6 | | 24 | 23 | | 25 | 5 | | 26 | 29 | | 27 | 9 | | 28 | 2 | | 29 | 7 | | 30 | 17 | | 31 | 10 | | 32 | 30 | | 33 | 33 | | 34 | 30 | | 35 | 3 | | 36 | 10 | | 37 | 26 | | 38 | 15 | | 39 | 5 | | 40 | 3 | | 41 | 4 | | 42 | 27 | | 43 | 13 | | 44 | 32 | | 45 | 46 | | 46 | 5 | | 47 | 14 | | 48 | 9 | | 49 | 12 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 121 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 122 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 711 | | adjectiveStacks | 1 | | stackExamples | | 0 | "stark against pale skin." |
| | adverbCount | 12 | | adverbRatio | 0.016877637130801686 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0014064697609001407 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 10.06 | | std | 8.04 | | cv | 0.799 | | sampleLengths | | 0 | 11 | | 1 | 17 | | 2 | 5 | | 3 | 12 | | 4 | 9 | | 5 | 13 | | 6 | 10 | | 7 | 1 | | 8 | 2 | | 9 | 3 | | 10 | 12 | | 11 | 7 | | 12 | 9 | | 13 | 14 | | 14 | 8 | | 15 | 14 | | 16 | 13 | | 17 | 14 | | 18 | 7 | | 19 | 25 | | 20 | 5 | | 21 | 9 | | 22 | 14 | | 23 | 2 | | 24 | 3 | | 25 | 11 | | 26 | 4 | | 27 | 5 | | 28 | 6 | | 29 | 5 | | 30 | 16 | | 31 | 7 | | 32 | 19 | | 33 | 8 | | 34 | 7 | | 35 | 8 | | 36 | 7 | | 37 | 2 | | 38 | 10 | | 39 | 7 | | 40 | 7 | | 41 | 22 | | 42 | 7 | | 43 | 6 | | 44 | 10 | | 45 | 7 | | 46 | 12 | | 47 | 4 | | 48 | 1 | | 49 | 23 |
| |
| 64.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4098360655737705 | | totalSentences | 122 | | uniqueOpeners | 50 | |
| 40.65% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 82 | | matches | | 0 | "Instead fine lines etched concentric" |
| | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 82 | | matches | | 0 | "It smelled of wet concrete," | | 1 | "Her torch cut a white" | | 2 | "His throat showed a split" | | 3 | "She rolled her left wrist" | | 4 | "He shone his torch across" | | 5 | "Her knees cracked." | | 6 | "Her sharp jaw tightened as" | | 7 | "She gloved up and eased" | | 8 | "She tucked hair behind her" | | 9 | "She patted the victim's coat." | | 10 | "She held it under her" | | 11 | "Her breath fogged." | | 12 | "Her boots left sharp prints" | | 13 | "She traced the line to" | | 14 | "Her torch found scuffs on" | | 15 | "She called back without looking." | | 16 | "She tucked hair behind her" | | 17 | "She paced three steps toward" | | 18 | "She crouched again by the" | | 19 | "She peered over her glasses." |
| | ratio | 0.244 | |
| 33.17% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 82 | | matches | | 0 | "The Northern line rattled overhead" | | 1 | "Harlow Quinn ducked under the" | | 2 | "It smelled of wet concrete," | | 3 | "Her torch cut a white" | | 4 | "The abandoned Tube station opened" | | 5 | "A man lay on his" | | 6 | "His throat showed a split" | | 7 | "The platform around him held" | | 8 | "Quinn stopped at the edge" | | 9 | "She rolled her left wrist" | | 10 | "DC Pryce stood over the" | | 11 | "He shone his torch across" | | 12 | "Quinn swept her beam along" | | 13 | "Dust lay thick across the" | | 14 | "Pryce frowned and tapped his" | | 15 | "Her knees cracked." | | 16 | "Her sharp jaw tightened as" | | 17 | "The edges gaped clean." | | 18 | "Pryce swung his torch toward" | | 19 | "Quinn ran her light over" |
| | ratio | 0.854 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |