| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 55 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2052 | | 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) | |
| 87.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2052 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "shattered" | | 1 | "scanned" | | 2 | "velvet" | | 3 | "chill" | | 4 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 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 | 1 | | hedgeCount | 1 | | narrationSentences | 171 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 210 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2052 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 52 | | wordCount | 1595 | | uniqueNames | 5 | | maxNameDensity | 1.82 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 1 | | Platform | 1 | | Eva | 20 | | Quinn | 29 |
| | persons | | | places | (empty) | | globalScore | 0.591 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | 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 | 2052 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 210 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 98 | | mean | 20.94 | | std | 19.26 | | cv | 0.92 | | sampleLengths | | 0 | 9 | | 1 | 59 | | 2 | 95 | | 3 | 9 | | 4 | 76 | | 5 | 4 | | 6 | 36 | | 7 | 21 | | 8 | 15 | | 9 | 3 | | 10 | 42 | | 11 | 52 | | 12 | 16 | | 13 | 8 | | 14 | 16 | | 15 | 9 | | 16 | 70 | | 17 | 19 | | 18 | 15 | | 19 | 25 | | 20 | 31 | | 21 | 5 | | 22 | 12 | | 23 | 59 | | 24 | 3 | | 25 | 7 | | 26 | 39 | | 27 | 13 | | 28 | 4 | | 29 | 31 | | 30 | 16 | | 31 | 44 | | 32 | 5 | | 33 | 3 | | 34 | 8 | | 35 | 17 | | 36 | 28 | | 37 | 8 | | 38 | 25 | | 39 | 7 | | 40 | 5 | | 41 | 6 | | 42 | 6 | | 43 | 48 | | 44 | 50 | | 45 | 3 | | 46 | 7 | | 47 | 5 | | 48 | 20 | | 49 | 10 |
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| 92.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 171 | | matches | | 0 | "been turned" | | 1 | "been yanked" | | 2 | "been left" | | 3 | "been centred" | | 4 | "been placed" | | 5 | "been opened" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 255 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 210 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1600 | | adjectiveStacks | 1 | | stackExamples | | 0 | "smooth over older damage." |
| | adverbCount | 39 | | adverbRatio | 0.024375 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0025 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 210 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 210 | | mean | 9.77 | | std | 7.26 | | cv | 0.743 | | sampleLengths | | 0 | 9 | | 1 | 19 | | 2 | 20 | | 3 | 10 | | 4 | 10 | | 5 | 18 | | 6 | 8 | | 7 | 20 | | 8 | 9 | | 9 | 14 | | 10 | 11 | | 11 | 15 | | 12 | 9 | | 13 | 28 | | 14 | 16 | | 15 | 16 | | 16 | 16 | | 17 | 4 | | 18 | 16 | | 19 | 5 | | 20 | 5 | | 21 | 4 | | 22 | 6 | | 23 | 10 | | 24 | 11 | | 25 | 15 | | 26 | 3 | | 27 | 6 | | 28 | 13 | | 29 | 9 | | 30 | 14 | | 31 | 10 | | 32 | 17 | | 33 | 9 | | 34 | 16 | | 35 | 16 | | 36 | 8 | | 37 | 16 | | 38 | 3 | | 39 | 6 | | 40 | 20 | | 41 | 21 | | 42 | 29 | | 43 | 13 | | 44 | 6 | | 45 | 4 | | 46 | 11 | | 47 | 9 | | 48 | 16 | | 49 | 13 |
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| 48.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.30952380952380953 | | totalSentences | 210 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 145 | | matches | | 0 | "Instead, it bit at her" | | 1 | "Too late for routine." | | 2 | "Too early for people to" | | 3 | "Instead, the tiles beneath his" | | 4 | "Just enough to show where" | | 5 | "Then she crouched again, this" |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 145 | | matches | | 0 | "Their torches cut pale cones" | | 1 | "His throat had a thin" | | 2 | "She stepped closer, lifted her" | | 3 | "She shifted her torch an" | | 4 | "She straightened and looked at" | | 5 | "Its shelf still held bottles" | | 6 | "She turned, and Eva emerged" | | 7 | "Her round glasses caught the" | | 8 | "She wore a coat too" | | 9 | "His cuff had a stain" | | 10 | "She stared a second longer," | | 11 | "She turned it over." | | 12 | "She held the shoe out." | | 13 | "Her eyes narrowed." | | 14 | "She crouched lower." | | 15 | "It carried the smell of" | | 16 | "She pressed two fingers into" | | 17 | "She pointed at the wall." | | 18 | "It stopped short of the" | | 19 | "Her eyes fixed on the" |
| | ratio | 0.193 | |
| 70.34% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 113 | | totalSentences | 145 | | matches | | 0 | "The station crouched under Camden" | | 1 | "Quinn ducked beneath the police" | | 2 | "The place should have smelled" | | 3 | "A cluster of uniforms stood" | | 4 | "Their torches cut pale cones" | | 5 | "A strip of fluorescent light" | | 6 | "Beads of wax and scraps" | | 7 | "Someone had tried to scrub" | | 8 | "Quinn stopped at the tape" | | 9 | "The body lay on its" | | 10 | "His throat had a thin" | | 11 | "Nothing about it fit." | | 12 | "She stepped closer, lifted her" | | 13 | "The second hand clicked on." | | 14 | "A forensics tech hovered near" | | 15 | "Another knelt by a smear" | | 16 | "Quinn crouched beside the dead" | | 17 | "She shifted her torch an" | | 18 | "The line at his throat" | | 19 | "A shallow arc of red" |
| | ratio | 0.779 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 145 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 1 | | matches | | 0 | "It carried the smell of rain on stone and a touch of ozone that made the hairs rise on her arms." |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "Eva said, eyes fixed on the platform" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "she muttered (mutter)" |
| | dialogueSentences | 55 | | tagDensity | 0.218 | | leniency | 0.436 | | rawRatio | 0.167 | | effectiveRatio | 0.073 | |