| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 2 | | adverbTags | | 0 | "She stepped back [back]" | | 1 | "She gestured back [back]" |
| | dialogueSentences | 47 | | tagDensity | 0.383 | | leniency | 0.766 | | rawRatio | 0.111 | | effectiveRatio | 0.085 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1088 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 86.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1088 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "stomach" | | 1 | "footsteps" | | 2 | "echoed" |
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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 | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 91 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1088 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.20% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 692 | | uniqueNames | 6 | | maxNameDensity | 1.16 | | worstName | "Aldridge" | | maxWindowNameDensity | 2 | | worstWindowName | "Aldridge" | | discoveredNames | | Tube | 1 | | Town | 1 | | Aldridge | 8 | | Quinn | 7 | | Deptford | 1 | | Morris | 2 |
| | persons | | 0 | "Aldridge" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.922 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1088 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 120 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 20.92 | | std | 17.99 | | cv | 0.86 | | sampleLengths | | 0 | 25 | | 1 | 43 | | 2 | 27 | | 3 | 4 | | 4 | 35 | | 5 | 10 | | 6 | 17 | | 7 | 34 | | 8 | 6 | | 9 | 3 | | 10 | 1 | | 11 | 33 | | 12 | 12 | | 13 | 36 | | 14 | 4 | | 15 | 9 | | 16 | 59 | | 17 | 24 | | 18 | 4 | | 19 | 4 | | 20 | 4 | | 21 | 3 | | 22 | 45 | | 23 | 11 | | 24 | 11 | | 25 | 31 | | 26 | 41 | | 27 | 4 | | 28 | 44 | | 29 | 6 | | 30 | 4 | | 31 | 52 | | 32 | 5 | | 33 | 58 | | 34 | 9 | | 35 | 22 | | 36 | 3 | | 37 | 33 | | 38 | 2 | | 39 | 61 | | 40 | 13 | | 41 | 12 | | 42 | 63 | | 43 | 2 | | 44 | 29 | | 45 | 25 | | 46 | 15 | | 47 | 40 | | 48 | 6 | | 49 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 91 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 117 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 120 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 692 | | adjectiveStacks | 1 | | stackExamples | | 0 | "long, wet, deliberate sound." |
| | adverbCount | 18 | | adverbRatio | 0.02601156069364162 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004335260115606936 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 9.07 | | std | 7.26 | | cv | 0.801 | | sampleLengths | | 0 | 25 | | 1 | 11 | | 2 | 11 | | 3 | 13 | | 4 | 8 | | 5 | 16 | | 6 | 11 | | 7 | 4 | | 8 | 8 | | 9 | 27 | | 10 | 10 | | 11 | 6 | | 12 | 11 | | 13 | 3 | | 14 | 13 | | 15 | 10 | | 16 | 2 | | 17 | 6 | | 18 | 1 | | 19 | 1 | | 20 | 4 | | 21 | 3 | | 22 | 1 | | 23 | 7 | | 24 | 26 | | 25 | 4 | | 26 | 8 | | 27 | 9 | | 28 | 27 | | 29 | 3 | | 30 | 1 | | 31 | 9 | | 32 | 18 | | 33 | 2 | | 34 | 6 | | 35 | 7 | | 36 | 5 | | 37 | 3 | | 38 | 18 | | 39 | 7 | | 40 | 5 | | 41 | 6 | | 42 | 6 | | 43 | 4 | | 44 | 4 | | 45 | 4 | | 46 | 3 | | 47 | 6 | | 48 | 26 | | 49 | 13 |
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| 78.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.5166666666666667 | | totalSentences | 120 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 80 | | matches | | 0 | "Everywhere else dripped, the tunnels" | | 1 | "Somewhere deep in the tunnels," | | 2 | "Then the lamps went out." |
| | ratio | 0.038 | |
| 95.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 80 | | matches | | 0 | "He tucked the clipboard tighter" | | 1 | "She walked the length of" | | 2 | "She tapped the seam" | | 3 | "She straightened, knees protesting" | | 4 | "His eyes were shut, his" | | 5 | "She'd seen enough to know." | | 6 | "They left scratches in the" | | 7 | "They tore their own fingernails" | | 8 | "It took the team forty" | | 9 | "She crouched before the dead" | | 10 | "She lifted his right hand" | | 11 | "She turned the hand over" | | 12 | "She'd seen that mark before." | | 13 | "Her stomach tightened." | | 14 | "She kept her voice flat" | | 15 | "She let the hand down" | | 16 | "She nodded at the door," | | 17 | "He just stared at her," | | 18 | "She stepped back onto the" | | 19 | "Her own footsteps echoed wrong" |
| | ratio | 0.313 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 80 | | matches | | 0 | "The body sat upright in" | | 1 | "Quinn ducked under the tape" | | 2 | "Camden Town, the old eastern" | | 3 | "Forensics had rigged work lamps" | | 4 | "The air tasted of rust" | | 5 | "DC Aldridge fell into step" | | 6 | "He tucked the clipboard tighter" | | 7 | "Quinn said nothing." | | 8 | "She walked the length of" | | 9 | "The welds along the door" | | 10 | "She tapped the seam" | | 11 | "Aldridge flipped a page." | | 12 | "She straightened, knees protesting" | | 13 | "Aldridge's mouth opened." | | 14 | "Quinn pressed her face to" | | 15 | "The man inside wore a" | | 16 | "Skin the colour of candle" | | 17 | "His eyes were shut, his" | | 18 | "People who suffocated did not" | | 19 | "She'd seen enough to know." |
| | ratio | 0.8 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 1 | | matches | | 0 | "No bulging veins or clawed hands that came with a body fighting for breath in a sealed box." |
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| 97.22% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 1 | | matches | | 0 | "She straightened, knees protesting" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 47 | | tagDensity | 0.064 | | leniency | 0.128 | | rawRatio | 0.333 | | effectiveRatio | 0.043 | |