| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "Whitfield crouched again [again]" |
| | dialogueSentences | 33 | | tagDensity | 0.242 | | leniency | 0.485 | | rawRatio | 0.125 | | effectiveRatio | 0.061 | |
| 95.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1083 | | 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) | |
| 90.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1083 | | 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 | 52 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 52 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1083 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 829 | | uniqueNames | 7 | | maxNameDensity | 0.97 | | worstName | "Whitfield" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 6 | | Whitfield | 8 | | Lane | 1 | | Fifteen | 1 | | Morris | 3 | | November | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Whitfield" | | 3 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 37 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.923 | | wordCount | 1083 | | matches | | 0 | "not in rigor, but tight, deliberate, like the man had been clutching something" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 27.77 | | std | 23.45 | | cv | 0.844 | | sampleLengths | | 0 | 46 | | 1 | 22 | | 2 | 68 | | 3 | 3 | | 4 | 31 | | 5 | 61 | | 6 | 3 | | 7 | 39 | | 8 | 12 | | 9 | 2 | | 10 | 43 | | 11 | 9 | | 12 | 9 | | 13 | 5 | | 14 | 60 | | 15 | 2 | | 16 | 6 | | 17 | 88 | | 18 | 29 | | 19 | 1 | | 20 | 2 | | 21 | 28 | | 22 | 7 | | 23 | 52 | | 24 | 61 | | 25 | 2 | | 26 | 20 | | 27 | 36 | | 28 | 7 | | 29 | 7 | | 30 | 39 | | 31 | 26 | | 32 | 9 | | 33 | 57 | | 34 | 48 | | 35 | 51 | | 36 | 25 | | 37 | 59 | | 38 | 8 |
| |
| 91.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 52 | | matches | | 0 | "been laid" | | 1 | "been drawn" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 125 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 77 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 830 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.03855421686746988 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008433734939759036 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 14.06 | | std | 12.03 | | cv | 0.856 | | sampleLengths | | 0 | 14 | | 1 | 32 | | 2 | 12 | | 3 | 10 | | 4 | 13 | | 5 | 10 | | 6 | 45 | | 7 | 3 | | 8 | 19 | | 9 | 12 | | 10 | 2 | | 11 | 18 | | 12 | 41 | | 13 | 3 | | 14 | 25 | | 15 | 14 | | 16 | 12 | | 17 | 2 | | 18 | 5 | | 19 | 38 | | 20 | 9 | | 21 | 9 | | 22 | 5 | | 23 | 17 | | 24 | 43 | | 25 | 2 | | 26 | 6 | | 27 | 13 | | 28 | 26 | | 29 | 3 | | 30 | 18 | | 31 | 28 | | 32 | 22 | | 33 | 7 | | 34 | 1 | | 35 | 2 | | 36 | 21 | | 37 | 7 | | 38 | 7 | | 39 | 27 | | 40 | 19 | | 41 | 4 | | 42 | 2 | | 43 | 22 | | 44 | 34 | | 45 | 2 | | 46 | 1 | | 47 | 1 | | 48 | 1 | | 49 | 2 |
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| 92.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.6233766233766234 | | totalSentences | 77 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 45 | | matches | | 0 | "His shirt collar had darkened" | | 1 | "She leaned closer to the" | | 2 | "She crouched by the mark," | | 3 | "She rubbed a pinch between" | | 4 | "She looked up at Whitfield" | | 5 | "She didn't believe it, and" | | 6 | "She'd been that once." | | 7 | "She turned toward the tunnel" | | 8 | "She crouched by the body" | | 9 | "He obliged, lifting one gloved" | | 10 | "She stood, joints protesting the" | | 11 | "She crouched, careful of her" | | 12 | "She had seen verdigris crust" | | 13 | "She didn't answer right away." | | 14 | "Her thumb found the hinge," |
| | ratio | 0.333 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 45 | | matches | | 0 | "The tape read POLICE LINE" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "DS Whitfield called from somewhere" | | 3 | "Quinn's torch beam found him" | | 4 | "Wolcott Lane station had closed" | | 5 | "Whitfield straightened, notebook already in" | | 6 | "The man lay on his" | | 7 | "His shirt collar had darkened" | | 8 | "Whitfield crouched again, tracing a" | | 9 | "Quinn didn't answer straight away." | | 10 | "She leaned closer to the" | | 11 | "Whitfield shrugged, the kind of" | | 12 | "Quinn stood and swept her" | | 13 | "Chalk marks, thin and precise," | | 14 | "These lines had been drawn" | | 15 | "She crouched by the mark," | | 16 | "She rubbed a pinch between" | | 17 | "She looked up at Whitfield" | | 18 | "She didn't believe it, and" | | 19 | "She'd been that once." |
| | ratio | 0.8 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 45 | | matches | (empty) | | ratio | 0 | |
| 37.04% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 27 | | technicalSentenceCount | 4 | | matches | | 0 | "His shirt collar had darkened to rust at the throat, a clean line from ear to ear, and yet the tile beneath him held only a thin, dried ring, no spray, no pooli…" | | 1 | "Whitfield shrugged, the kind of shrug that had closed a hundred cases with the easiest explanation available." | | 2 | "Beneath each one sat a thin rim of the same pale green dust that had gathered by the chalk circle." | | 3 | "In an evidence bag she'd sealed with her own hands three years ago, the last physical trace of DS Morris that anyone had ever recovered, filed and forgotten bec…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "She crouched, refusing to give the shadow a second glance" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.03 | | leniency | 0.061 | | rawRatio | 0 | | effectiveRatio | 0 | |