| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.318 | | leniency | 0.636 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 888 | | totalAiIsmAdverbs | 2 | | 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) | |
| 71.85% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 888 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "etched" | | 1 | "traced" | | 2 | "quivered" | | 3 | "pulse" |
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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 | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 888 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 43.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 515 | | uniqueNames | 8 | | maxNameDensity | 2.14 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Barnes" | | discoveredNames | | Camden | 1 | | Town | 1 | | Detective | 1 | | Sergeant | 1 | | Barnes | 10 | | Dry | 1 | | Harlow | 11 | | Graffiti | 1 |
| | persons | | 0 | "Sergeant" | | 1 | "Barnes" | | 2 | "Harlow" |
| | places | | | globalScore | 0.432 | | windowScore | 0.833 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "as if gripping something" |
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| 87.39% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.126 | | wordCount | 888 | | matches | | 0 | "not north, but directly at her" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 20.65 | | std | 15.06 | | cv | 0.729 | | sampleLengths | | 0 | 28 | | 1 | 41 | | 2 | 4 | | 3 | 16 | | 4 | 34 | | 5 | 8 | | 6 | 41 | | 7 | 19 | | 8 | 2 | | 9 | 42 | | 10 | 2 | | 11 | 28 | | 12 | 35 | | 13 | 23 | | 14 | 32 | | 15 | 1 | | 16 | 36 | | 17 | 11 | | 18 | 9 | | 19 | 37 | | 20 | 5 | | 21 | 10 | | 22 | 18 | | 23 | 64 | | 24 | 33 | | 25 | 21 | | 26 | 4 | | 27 | 32 | | 28 | 9 | | 29 | 6 | | 30 | 28 | | 31 | 5 | | 32 | 44 | | 33 | 3 | | 34 | 26 | | 35 | 13 | | 36 | 2 | | 37 | 28 | | 38 | 38 | | 39 | 23 | | 40 | 15 | | 41 | 5 | | 42 | 7 |
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| 96.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 77 | | matches | | 0 | "been called" | | 1 | "was closed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 80 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 107 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 520 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 11 | | adverbRatio | 0.021153846153846155 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.013461538461538462 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 8.3 | | std | 6.33 | | cv | 0.763 | | sampleLengths | | 0 | 16 | | 1 | 4 | | 2 | 8 | | 3 | 23 | | 4 | 12 | | 5 | 6 | | 6 | 4 | | 7 | 9 | | 8 | 7 | | 9 | 15 | | 10 | 1 | | 11 | 1 | | 12 | 17 | | 13 | 8 | | 14 | 9 | | 15 | 2 | | 16 | 2 | | 17 | 28 | | 18 | 7 | | 19 | 12 | | 20 | 2 | | 21 | 6 | | 22 | 14 | | 23 | 4 | | 24 | 18 | | 25 | 2 | | 26 | 18 | | 27 | 10 | | 28 | 9 | | 29 | 9 | | 30 | 9 | | 31 | 5 | | 32 | 3 | | 33 | 23 | | 34 | 12 | | 35 | 6 | | 36 | 8 | | 37 | 4 | | 38 | 2 | | 39 | 1 | | 40 | 14 | | 41 | 6 | | 42 | 9 | | 43 | 7 | | 44 | 11 | | 45 | 9 | | 46 | 16 | | 47 | 2 | | 48 | 11 | | 49 | 1 |
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| 89.72% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5607476635514018 | | totalSentences | 107 | | uniqueOpeners | 60 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 59 | | matches | | 0 | "She gestured to the open" | | 1 | "He held up an evidence" | | 2 | "She knew those marks." | | 3 | "She'd been on her feet" | | 4 | "She turned in a slow" | | 5 | "She pressed her palm to" | | 6 | "She traced the outline of" | | 7 | "She handed the bag back" | | 8 | "She looked at the wall" | | 9 | "She took a breath." |
| | ratio | 0.169 | |
| 87.12% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 59 | | matches | | 0 | "The body lay sprawled in" | | 1 | "The air tasted of rust" | | 2 | "Harlow squatted beside the victim," | | 3 | "Detective Sergeant Barnes hovered near" | | 4 | "Barnes stepped closer, his shoes" | | 5 | "Harlow pointed to the collar" | | 6 | "She gestured to the open" | | 7 | "Barnes flipped a page in" | | 8 | "He held up an evidence" | | 9 | "She knew those marks." | | 10 | "Barnes squinted at the victim's" | | 11 | "Harlow stood, her knees cracking" | | 12 | "She'd been on her feet" | | 13 | "The body had been called" | | 14 | "She turned in a slow" | | 15 | "Graffiti on the walls, mostly" | | 16 | "A pile of rusted cans" | | 17 | "A discarded sleeping bag." | | 18 | "The victim's right hand was" | | 19 | "Harlow crouched again, studying the" |
| | ratio | 0.746 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 59 | | matches | | 0 | "Now it was nearly two." | | 1 | "As if the victim had" |
| | ratio | 0.034 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 11 | | technicalSentenceCount | 1 | | matches | | 0 | "Inside, a finger-length piece of ivory, etched with symbols that made Harlow's eyes itch." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow stood, her knees cracking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.023 | | leniency | 0.045 | | rawRatio | 0 | | effectiveRatio | 0 | |