| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1299 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 76.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1299 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "scanned" | | 1 | "measured" | | 2 | "flicked" | | 3 | "etched" | | 4 | "wavered" |
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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 | 108 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 147 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1299 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 13.08% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 986 | | uniqueNames | 10 | | maxNameDensity | 2.74 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | High | 1 | | Street | 1 | | Tube | 1 | | Kowalski | 1 | | Patel | 11 | | Quinn | 27 | | Eva | 11 | | Morris | 1 | | Aldgate | 1 |
| | persons | | 0 | "Kowalski" | | 1 | "Patel" | | 2 | "Quinn" | | 3 | "Eva" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.131 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 85 | | 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 | 1299 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 147 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 27.64 | | std | 16.95 | | cv | 0.613 | | sampleLengths | | 0 | 16 | | 1 | 36 | | 2 | 27 | | 3 | 32 | | 4 | 19 | | 5 | 46 | | 6 | 8 | | 7 | 55 | | 8 | 14 | | 9 | 23 | | 10 | 41 | | 11 | 38 | | 12 | 21 | | 13 | 42 | | 14 | 7 | | 15 | 17 | | 16 | 42 | | 17 | 16 | | 18 | 11 | | 19 | 25 | | 20 | 9 | | 21 | 16 | | 22 | 24 | | 23 | 4 | | 24 | 15 | | 25 | 38 | | 26 | 8 | | 27 | 16 | | 28 | 47 | | 29 | 10 | | 30 | 31 | | 31 | 21 | | 32 | 30 | | 33 | 14 | | 34 | 39 | | 35 | 63 | | 36 | 52 | | 37 | 9 | | 38 | 66 | | 39 | 18 | | 40 | 32 | | 41 | 24 | | 42 | 43 | | 43 | 9 | | 44 | 13 | | 45 | 75 | | 46 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 164 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 147 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 993 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.00906344410876133 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0010070493454179255 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 147 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 147 | | mean | 8.84 | | std | 5.45 | | cv | 0.616 | | sampleLengths | | 0 | 16 | | 1 | 11 | | 2 | 10 | | 3 | 15 | | 4 | 5 | | 5 | 13 | | 6 | 9 | | 7 | 5 | | 8 | 9 | | 9 | 4 | | 10 | 14 | | 11 | 7 | | 12 | 12 | | 13 | 4 | | 14 | 8 | | 15 | 16 | | 16 | 8 | | 17 | 10 | | 18 | 8 | | 19 | 13 | | 20 | 12 | | 21 | 2 | | 22 | 2 | | 23 | 7 | | 24 | 6 | | 25 | 13 | | 26 | 3 | | 27 | 7 | | 28 | 4 | | 29 | 1 | | 30 | 13 | | 31 | 9 | | 32 | 10 | | 33 | 2 | | 34 | 3 | | 35 | 2 | | 36 | 2 | | 37 | 22 | | 38 | 8 | | 39 | 13 | | 40 | 9 | | 41 | 8 | | 42 | 6 | | 43 | 15 | | 44 | 11 | | 45 | 9 | | 46 | 6 | | 47 | 5 | | 48 | 2 | | 49 | 2 |
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| 53.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3673469387755102 | | totalSentences | 147 | | uniqueOpeners | 54 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 101 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 101 | | matches | | 0 | "Her boots struck concrete slick" | | 1 | "She squared her shoulders and" | | 2 | "Her torch cut a white" | | 3 | "His shoes were new and" | | 4 | "Her sharp jaw set." | | 5 | "She tucked a curl behind" | | 6 | "Her cropped salt-and-pepper hair dripped" | | 7 | "She ignored the temple wound" | | 8 | "She watched Eva thumb the" | | 9 | "Her shadow fell across the" | | 10 | "Her hand shook and the" | | 11 | "She pressed her palm near" | | 12 | "Her hand tightened on the" | | 13 | "Her boots left sharp prints" | | 14 | "She knelt and turned the" |
| | ratio | 0.149 | |
| 19.41% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 101 | | matches | | 0 | "Quinn ducked under the tape" | | 1 | "Her boots struck concrete slick" | | 2 | "The air turned cold three" | | 3 | "Patel stood at the bottom" | | 4 | "Water beaded on his high-vis" | | 5 | "Quinn checked the worn leather" | | 6 | "The face read 02:14." | | 7 | "She squared her shoulders and" | | 8 | "Patel jerked his chin toward" | | 9 | "Quinn pushed past him." | | 10 | "Her torch cut a white" | | 11 | "The abandoned Tube station opened" | | 12 | "A dead ticket hall yawned" | | 13 | "A body lay mid-platform under" | | 14 | "Quinn stopped at the edge" | | 15 | "The dead man sprawled on" | | 16 | "Both hands curled at his" | | 17 | "His shoes were new and" | | 18 | "Quinn crouched and her brown" | | 19 | "Her sharp jaw set." |
| | ratio | 0.881 | |
| 49.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 101 | | matches | | 0 | "To the right the platform" |
| | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 2 | | matches | | 0 | "The lining bore a stamped mark, a small eye inside a circle, inked in violet that glistened though the wool stayed dry." | | 1 | "Quinn lifted her eyes to the arch and the compass needle that pinned it." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |