| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said quietly [quietly]" |
| | dialogueSentences | 76 | | tagDensity | 0.342 | | leniency | 0.684 | | rawRatio | 0.038 | | effectiveRatio | 0.026 | |
| 73.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1903 | | totalAiIsmAdverbs | 10 | | found | | | highlights | | 0 | "slightly" | | 1 | "carefully" | | 2 | "sharply" | | 3 | "slowly" | | 4 | "quickly" | | 5 | "really" | | 6 | "very" | | 7 | "perfectly" |
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| 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) | |
| 60.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1903 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "fluttered" | | 1 | "chill" | | 2 | "perfect" | | 3 | "weight" | | 4 | "etched" | | 5 | "pulse" | | 6 | "traced" | | 7 | "raced" | | 8 | "echoed" | | 9 | "mechanical" | | 10 | "vibrated" | | 11 | "flickered" | | 12 | "whisper" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | 0 | "eyes widened" | | 1 | "eyes narrowed" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 171 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 171 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 220 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1903 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 65 | | wordCount | 1288 | | uniqueNames | 11 | | maxNameDensity | 2.02 | | worstName | "Quinn" | | maxWindowNameDensity | 5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 26 | | Tube | 2 | | Patel | 15 | | Copper | 1 | | Protective | 1 | | Morris | 4 | | Knowledge | 1 | | Oxford | 1 | | Eva | 12 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Patel" | | 3 | "Copper" | | 4 | "Morris" | | 5 | "Eva" |
| | places | | | globalScore | 0.491 | | windowScore | 0 | |
| 77.88% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 104 | | glossingSentenceCount | 3 | | matches | | 0 | "as though reaching for the tracks" | | 1 | "as if descending in a plane" | | 2 | "Something like fear flickered across her fre" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1903 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 220 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 101 | | mean | 18.84 | | std | 13.56 | | cv | 0.72 | | sampleLengths | | 0 | 35 | | 1 | 15 | | 2 | 46 | | 3 | 7 | | 4 | 18 | | 5 | 53 | | 6 | 32 | | 7 | 57 | | 8 | 12 | | 9 | 38 | | 10 | 43 | | 11 | 6 | | 12 | 12 | | 13 | 39 | | 14 | 28 | | 15 | 20 | | 16 | 5 | | 17 | 23 | | 18 | 17 | | 19 | 5 | | 20 | 13 | | 21 | 43 | | 22 | 26 | | 23 | 4 | | 24 | 20 | | 25 | 9 | | 26 | 65 | | 27 | 15 | | 28 | 41 | | 29 | 2 | | 30 | 3 | | 31 | 15 | | 32 | 31 | | 33 | 11 | | 34 | 7 | | 35 | 4 | | 36 | 2 | | 37 | 24 | | 38 | 7 | | 39 | 64 | | 40 | 14 | | 41 | 5 | | 42 | 2 | | 43 | 4 | | 44 | 13 | | 45 | 25 | | 46 | 5 | | 47 | 8 | | 48 | 28 | | 49 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 171 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 226 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 220 | | ratio | 0 | | matches | (empty) | |
| 99.88% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1291 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 51 | | adverbRatio | 0.039504260263361735 | | lyAdverbCount | 26 | | lyAdverbRatio | 0.020139426800929512 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 220 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 220 | | mean | 8.65 | | std | 5.71 | | cv | 0.66 | | sampleLengths | | 0 | 11 | | 1 | 16 | | 2 | 8 | | 3 | 15 | | 4 | 15 | | 5 | 8 | | 6 | 23 | | 7 | 5 | | 8 | 2 | | 9 | 14 | | 10 | 4 | | 11 | 20 | | 12 | 1 | | 13 | 2 | | 14 | 15 | | 15 | 5 | | 16 | 4 | | 17 | 6 | | 18 | 10 | | 19 | 22 | | 20 | 12 | | 21 | 4 | | 22 | 1 | | 23 | 2 | | 24 | 13 | | 25 | 25 | | 26 | 4 | | 27 | 8 | | 28 | 16 | | 29 | 13 | | 30 | 3 | | 31 | 2 | | 32 | 3 | | 33 | 1 | | 34 | 8 | | 35 | 20 | | 36 | 5 | | 37 | 10 | | 38 | 6 | | 39 | 6 | | 40 | 6 | | 41 | 13 | | 42 | 2 | | 43 | 16 | | 44 | 5 | | 45 | 1 | | 46 | 2 | | 47 | 7 | | 48 | 21 | | 49 | 9 |
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| 73.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4590909090909091 | | totalSentences | 220 | | uniqueOpeners | 101 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 150 | | matches | | 0 | "Just that impossible, contained crimson" | | 1 | "More like bone against bone." | | 2 | "Instead she shone the torch" | | 3 | "Instead it revealed stalls." | | 4 | "Only she could see it." | | 5 | "Somewhere in the distance, or" |
| | ratio | 0.04 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 150 | | matches | | 0 | "Her boots scraped against the" | | 1 | "she muttered, gloved fingers brushing" | | 2 | "She tilted her head, studying" | | 3 | "She rolled the body slightly" | | 4 | "Her gaze snagged on the" | | 5 | "She picked it up carefully," | | 6 | "Her thumb traced the markings." | | 7 | "She stood, slipping the compass" | | 8 | "She pointed without touching" | | 9 | "They both stared at the" | | 10 | "It hadn't spread at all," | | 11 | "He rubbed the back of" | | 12 | "She turned sharply, hand moving" | | 13 | "She moved along the platform" | | 14 | "Its presence tugged at her," | | 15 | "She'd found it in his" | | 16 | "She'd called it evidence." | | 17 | "She stopped at the tunnel" | | 18 | "She approached slowly, Patel close" | | 19 | "She picked it up." |
| | ratio | 0.253 | |
| 33.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 150 | | matches | | 0 | "The metal gate groaned as" | | 1 | "Her boots scraped against the" | | 2 | "The air tasted of rust" | | 3 | "she muttered, gloved fingers brushing" | | 4 | "A single bulb swung from" | | 5 | "DS Patel stood near the" | | 6 | "Patel didn't look up" | | 7 | "Quinn stepped over a puddle" | | 8 | "The victim lay sprawled near" | | 9 | "Patel said, voice clipped" | | 10 | "Quinn crouched beside the corpse" | | 11 | "Copper stung her nostrils." | | 12 | "She tilted her head, studying" | | 13 | "Patel shifted his weight." | | 14 | "She rolled the body slightly" | | 15 | "The dead man's face emerged," | | 16 | "Her gaze snagged on the" | | 17 | "A small brass compass lay" | | 18 | "Verdigris patina on the casing." | | 19 | "The needle spun wildly even" |
| | ratio | 0.853 | |
| 33.33% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 150 | | matches | | 0 | "Just as the rumours said." |
| | ratio | 0.007 | |
| 57.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 5 | | matches | | 0 | "DS Patel stood near the body, notepad in hand, his narrow shoulders hunched against the chill that had nothing to do with temperature." | | 1 | "The victim lay sprawled near the edge of the platform, face down, arms outstretched as though reaching for the tracks." | | 2 | "Expensive coat now ruined by blood that had pooled in a perfect circle beneath him." | | 3 | "A small brass compass lay half-crushed beneath his palm, its face etched with symbols that hurt to look at directly." | | 4 | "She clutched a worn leather satchel to her chest as though it might shield her." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 1 | | matches | | 0 | "Patel said, voice clipped" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she whispered (whisper)" | | 2 | "Quinn demanded (demand)" |
| | dialogueSentences | 76 | | tagDensity | 0.079 | | leniency | 0.158 | | rawRatio | 0.5 | | effectiveRatio | 0.079 | |