| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 172 | | tagDensity | 0.07 | | leniency | 0.14 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2656 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 81.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2656 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "silk" | | 1 | "traced" | | 2 | "weight" | | 3 | "silence" | | 4 | "quivered" | | 5 | "flicked" | | 6 | "could feel" |
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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 | 216 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 216 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 376 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2656 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 43.49% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 81 | | wordCount | 1690 | | uniqueNames | 10 | | maxNameDensity | 2.13 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 36 | | Tube | 1 | | Camden | 1 | | Sergeant | 1 | | Ash | 1 | | Mercer | 28 | | Morris | 2 | | One | 4 | | Malik | 6 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Mercer" | | 4 | "Morris" | | 5 | "One" | | 6 | "Malik" |
| | places | (empty) | | globalScore | 0.435 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 129 | | 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 | 2656 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 376 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 262 | | mean | 10.14 | | std | 10.96 | | cv | 1.082 | | sampleLengths | | 0 | 30 | | 1 | 57 | | 2 | 14 | | 3 | 51 | | 4 | 14 | | 5 | 29 | | 6 | 2 | | 7 | 14 | | 8 | 6 | | 9 | 4 | | 10 | 3 | | 11 | 8 | | 12 | 5 | | 13 | 50 | | 14 | 10 | | 15 | 11 | | 16 | 5 | | 17 | 6 | | 18 | 2 | | 19 | 15 | | 20 | 4 | | 21 | 7 | | 22 | 14 | | 23 | 4 | | 24 | 35 | | 25 | 5 | | 26 | 4 | | 27 | 5 | | 28 | 4 | | 29 | 2 | | 30 | 4 | | 31 | 2 | | 32 | 4 | | 33 | 1 | | 34 | 26 | | 35 | 5 | | 36 | 37 | | 37 | 7 | | 38 | 7 | | 39 | 5 | | 40 | 7 | | 41 | 24 | | 42 | 3 | | 43 | 4 | | 44 | 3 | | 45 | 8 | | 46 | 10 | | 47 | 6 | | 48 | 2 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 216 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 288 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 376 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1691 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.013601419278533412 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0029568302779420462 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 376 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 376 | | mean | 7.06 | | std | 5.98 | | cv | 0.846 | | sampleLengths | | 0 | 30 | | 1 | 15 | | 2 | 7 | | 3 | 22 | | 4 | 3 | | 5 | 10 | | 6 | 14 | | 7 | 12 | | 8 | 22 | | 9 | 5 | | 10 | 12 | | 11 | 14 | | 12 | 12 | | 13 | 17 | | 14 | 2 | | 15 | 6 | | 16 | 8 | | 17 | 6 | | 18 | 4 | | 19 | 3 | | 20 | 8 | | 21 | 5 | | 22 | 6 | | 23 | 2 | | 24 | 2 | | 25 | 19 | | 26 | 8 | | 27 | 7 | | 28 | 6 | | 29 | 10 | | 30 | 11 | | 31 | 5 | | 32 | 6 | | 33 | 2 | | 34 | 3 | | 35 | 12 | | 36 | 4 | | 37 | 7 | | 38 | 6 | | 39 | 8 | | 40 | 4 | | 41 | 8 | | 42 | 12 | | 43 | 9 | | 44 | 3 | | 45 | 3 | | 46 | 5 | | 47 | 4 | | 48 | 5 | | 49 | 4 |
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| 58.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3723404255319149 | | totalSentences | 376 | | uniqueOpeners | 140 | |
| 53.48% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 187 | | matches | | 0 | "Only three remained visible." | | 1 | "Only blood in a locked" | | 2 | "Then she saw what had" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 187 | | matches | | 0 | "She wanted to see how" | | 1 | "His scene suit strained across" | | 2 | "He crouched without crossing the" | | 3 | "Their lamps flashed over empty" | | 4 | "Her movement carried military precision," | | 5 | "She returned to the body." | | 6 | "Her lips had cracked at" | | 7 | "Her right hand rested open" | | 8 | "Her left curled against her" | | 9 | "She pointed with her torch." | | 10 | "Her answer cut harder than" | | 11 | "She drew closer." | | 12 | "Her cheeks showed pale grooves" | | 13 | "He gave the compass another" | | 14 | "She shifted the bag left." | | 15 | "His jaw tightened." | | 16 | "She handed the evidence bag" | | 17 | "She pointed to the grime" | | 18 | "Its feet had left four" | | 19 | "They took opposite ends and" |
| | ratio | 0.16 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 153 | | totalSentences | 187 | | matches | | 0 | "Detective Harlow Quinn descended through" | | 1 | "The official entrance stood behind" | | 2 | "Nobody had used that route" | | 3 | "The crime scene team had" | | 4 | "Quinn had refused." | | 5 | "She wanted to see how" | | 6 | "The wound in the wall" | | 7 | "Canvas market awnings crowded beneath" | | 8 | "Stalls filled the platform from" | | 9 | "Wax dripped from antler chandeliers." | | 10 | "The candles had gone out," | | 11 | "Detective Sergeant Ash Mercer waited" | | 12 | "His scene suit strained across" | | 13 | "Quinn checked her worn leather" | | 14 | "The cracked face showed twelve" | | 15 | "Quinn ducked beneath the tape." | | 16 | "A woman lay behind the" | | 17 | "A circle of grey powder" | | 18 | "Each wick leaned towards the" | | 19 | "Mercer pointed at the silver" |
| | ratio | 0.818 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 187 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 2 | | matches | | 0 | "Dark hair spread across the tiles in careful strands, as though someone had combed it after placing her there." | | 1 | "A small oval token lay against his skin, polished smooth and carved with the same hooked sigil that appeared at the top of the compass face." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 6 | | fancyTags | | 0 | "he continued (continue)" | | 1 | "Mercer muttered (mutter)" | | 2 | "Mercer noted (note)" | | 3 | "Quinn ordered (order)" | | 4 | "Mercer murmured (murmur)" | | 5 | "Malik pressed (press)" |
| | dialogueSentences | 172 | | tagDensity | 0.064 | | leniency | 0.128 | | rawRatio | 0.545 | | effectiveRatio | 0.07 | |