| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.18 | | leniency | 0.361 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1730 | | totalAiIsmAdverbs | 1 | | 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) | |
| 76.88% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1730 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "scanned" | | 1 | "navigating" | | 2 | "flicked" | | 3 | "comfortable" | | 4 | "silk" | | 5 | "flicker" | | 6 | "footsteps" | | 7 | "measured" |
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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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 155 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1730 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1052 | | uniqueNames | 11 | | maxNameDensity | 1.52 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Kowalski" | | discoveredNames | | Quinn | 16 | | Hargreaves | 3 | | Victorian | 2 | | Town | 1 | | Rotherhithe | 1 | | Morris | 1 | | Italian | 1 | | Kowalski | 12 | | Moleskine | 1 | | Northern | 1 | | Line | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Hargreaves" | | 2 | "Morris" | | 3 | "Kowalski" |
| | places | | | globalScore | 0.74 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | 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 | 1730 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 155 | | matches | | 0 | "pushed that thought" | | 1 | "filed that detail" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 22.18 | | std | 21.96 | | cv | 0.99 | | sampleLengths | | 0 | 5 | | 1 | 76 | | 2 | 24 | | 3 | 44 | | 4 | 90 | | 5 | 14 | | 6 | 41 | | 7 | 3 | | 8 | 26 | | 9 | 4 | | 10 | 11 | | 11 | 91 | | 12 | 9 | | 13 | 14 | | 14 | 47 | | 15 | 2 | | 16 | 36 | | 17 | 5 | | 18 | 11 | | 19 | 54 | | 20 | 19 | | 21 | 8 | | 22 | 6 | | 23 | 21 | | 24 | 7 | | 25 | 34 | | 26 | 2 | | 27 | 1 | | 28 | 32 | | 29 | 7 | | 30 | 37 | | 31 | 32 | | 32 | 2 | | 33 | 13 | | 34 | 1 | | 35 | 26 | | 36 | 6 | | 37 | 40 | | 38 | 3 | | 39 | 30 | | 40 | 13 | | 41 | 6 | | 42 | 26 | | 43 | 42 | | 44 | 5 | | 45 | 21 | | 46 | 23 | | 47 | 18 | | 48 | 2 | | 49 | 82 |
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| 95.24% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 105 | | matches | | 0 | "been was" | | 1 | "been swept" | | 2 | "been carried" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 168 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 155 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1055 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.025592417061611375 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0037914691943127963 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 155 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 155 | | mean | 11.16 | | std | 10.01 | | cv | 0.897 | | sampleLengths | | 0 | 5 | | 1 | 21 | | 2 | 16 | | 3 | 17 | | 4 | 22 | | 5 | 12 | | 6 | 12 | | 7 | 3 | | 8 | 14 | | 9 | 2 | | 10 | 3 | | 11 | 22 | | 12 | 5 | | 13 | 18 | | 14 | 17 | | 15 | 23 | | 16 | 9 | | 17 | 18 | | 18 | 14 | | 19 | 3 | | 20 | 6 | | 21 | 3 | | 22 | 6 | | 23 | 6 | | 24 | 3 | | 25 | 14 | | 26 | 3 | | 27 | 26 | | 28 | 4 | | 29 | 11 | | 30 | 6 | | 31 | 18 | | 32 | 18 | | 33 | 4 | | 34 | 14 | | 35 | 2 | | 36 | 2 | | 37 | 27 | | 38 | 9 | | 39 | 4 | | 40 | 10 | | 41 | 10 | | 42 | 14 | | 43 | 15 | | 44 | 2 | | 45 | 4 | | 46 | 2 | | 47 | 2 | | 48 | 7 | | 49 | 3 |
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| 77.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.49032258064516127 | | totalSentences | 155 | | uniqueOpeners | 76 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 92 | | matches | | 0 | "Somewhere deeper in the tunnel" | | 1 | "Too uniform, too intentional." | | 2 | "Just for a moment, just" | | 3 | "Somewhere above them, the last" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 92 | | matches | | 0 | "She crouched beside the corpse" | | 1 | "She tilted her head, studying" | | 2 | "She pushed that thought aside" | | 3 | "Her worn leather watch caught" | | 4 | "He checked his notes." | | 5 | "She'd clocked the newcomer three" | | 6 | "She tucked a strand of" | | 7 | "She moved with the careful" | | 8 | "She knelt beside the nearest" | | 9 | "Her hand moved fast, sketching" | | 10 | "Her pencil hovered above a" | | 11 | "She pointed at the symbol" | | 12 | "She indicated where the white" | | 13 | "She'd missed it." | | 14 | "She did not enjoy missing" | | 15 | "She glanced at DC Hargreaves," | | 16 | "She'd checked it already, found" | | 17 | "She pulled a sterile swab" | | 18 | "She held up her thumb" | | 19 | "She stepped closer" |
| | ratio | 0.272 | |
| 90.43% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 92 | | matches | | 0 | "The body had no face." | | 1 | "The skin where features should" | | 2 | "She crouched beside the corpse" | | 3 | "The first pair felt thin" | | 4 | "DC Hargreaves said from somewhere" | | 5 | "Quinn said nothing." | | 6 | "She tilted her head, studying" | | 7 | "The flesh had the same" | | 8 | "The abandoned station swallowed sound." | | 9 | "Camden Town's living station hummed" | | 10 | "Something Quinn's tongue couldn't name" | | 11 | "The same taste she'd noticed" | | 12 | "She pushed that thought aside" | | 13 | "Charcoal overcoat, tailored." | | 14 | "Hands uncallused and clean, nails" | | 15 | "A professional, then." | | 16 | "Somebody who worked behind a" | | 17 | "Quinn stood and scanned the" | | 18 | "Her worn leather watch caught" | | 19 | "Dust lay thick on the" |
| | ratio | 0.739 | |
| 54.35% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 92 | | matches | | | ratio | 0.011 | |
| 29.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 7 | | matches | | 0 | "The first pair felt thin down here, insufficient, as though the cold rising from the disused platform tiles could seep through latex." | | 1 | "The flesh had the same pore pattern as the victim's forehead, continuous and unblemished, as if the face had simply never existed." | | 2 | "Somewhere deeper in the tunnel network, water dripped in a slow, metronomic rhythm that bounced off Victorian brickwork." | | 3 | "Dust lay thick on the tiles, the kind of settled grey blanket that took years to accumulate undisturbed." | | 4 | "Something shifted behind her glasses, a recognition Quinn had seen before in witnesses who knew more than they volunteered." | | 5 | "She knelt beside the nearest wall marking and opened her satchel, producing a battered Moleskine and a pencil stub." | | 6 | "She glanced at DC Hargreaves, who was cataloguing something near the tunnel entrance, then lowered her voice." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 61 | | tagDensity | 0.066 | | leniency | 0.131 | | rawRatio | 0 | | effectiveRatio | 0 | |