| 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 | 2050 | | 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) | |
| 24.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2050 | | totalAiIsms | 31 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "calloused fingers" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | |
| | highlights | | 0 | "pulsed" | | 1 | "silence" | | 2 | "weight" | | 3 | "echoed" | | 4 | "calloused fingers" | | 5 | "traced" | | 6 | "pulse" | | 7 | "calculated" | | 8 | "warmth" | | 9 | "aligned" | | 10 | "could feel" | | 11 | "fractured" | | 12 | "flicker" | | 13 | "silk" | | 14 | "electric" | | 15 | "tension" | | 16 | "vibrated" |
| |
| 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 | 340 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 340 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 340 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 17 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2050 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 2050 | | uniqueNames | 12 | | maxNameDensity | 0.59 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | East | 1 | | London | 1 | | Moreau | 1 | | Rotherhithe | 1 | | Avaros | 1 | | Marseille | 1 | | Shoreditch | 1 | | Rory | 12 | | You | 10 | | Waiting | 4 | | Pulled | 3 | | Let | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Avaros" | | 2 | "Rory" | | 3 | "You" | | 4 | "Pulled" | | 5 | "Let" |
| | places | | 0 | "East" | | 1 | "London" | | 2 | "Marseille" | | 3 | "Shoreditch" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 166 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a physical blow" | | 1 | "tasted like surrender" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2050 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 340 | | matches | (empty) | |
| 22.55% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 85.42 | | std | 19.55 | | cv | 0.229 | | sampleLengths | | 0 | 87 | | 1 | 48 | | 2 | 64 | | 3 | 67 | | 4 | 61 | | 5 | 82 | | 6 | 62 | | 7 | 81 | | 8 | 95 | | 9 | 65 | | 10 | 73 | | 11 | 78 | | 12 | 109 | | 13 | 82 | | 14 | 74 | | 15 | 79 | | 16 | 120 | | 17 | 116 | | 18 | 91 | | 19 | 84 | | 20 | 100 | | 21 | 115 | | 22 | 105 | | 23 | 112 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 340 | | matches | | 0 | "were supposed" | | 1 | "was built" | | 2 | "was left" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 379 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 340 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2051 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 50 | | adverbRatio | 0.02437835202340322 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0034129692832764505 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 340 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 340 | | mean | 6.03 | | std | 2.95 | | cv | 0.489 | | sampleLengths | | 0 | 10 | | 1 | 5 | | 2 | 9 | | 3 | 6 | | 4 | 8 | | 5 | 11 | | 6 | 8 | | 7 | 14 | | 8 | 7 | | 9 | 3 | | 10 | 5 | | 11 | 1 | | 12 | 6 | | 13 | 3 | | 14 | 12 | | 15 | 5 | | 16 | 2 | | 17 | 6 | | 18 | 14 | | 19 | 3 | | 20 | 5 | | 21 | 6 | | 22 | 7 | | 23 | 9 | | 24 | 11 | | 25 | 13 | | 26 | 10 | | 27 | 5 | | 28 | 4 | | 29 | 8 | | 30 | 8 | | 31 | 9 | | 32 | 15 | | 33 | 8 | | 34 | 10 | | 35 | 5 | | 36 | 2 | | 37 | 4 | | 38 | 8 | | 39 | 14 | | 40 | 10 | | 41 | 5 | | 42 | 6 | | 43 | 7 | | 44 | 6 | | 45 | 8 | | 46 | 7 | | 47 | 9 | | 48 | 9 | | 49 | 6 |
| |
| 37.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 41 | | diversityRatio | 0.25 | | totalSentences | 340 | | uniqueOpeners | 85 | |
| 64.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 309 | | matches | | 0 | "Always found the angle that" | | 1 | "Then back to her eyes." | | 2 | "Then walked out into the" | | 3 | "Just enough to feel the" | | 4 | "Just enough to watch him" | | 5 | "Always waiting for her to" |
| | ratio | 0.019 | |
| 33.59% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 144 | | totalSentences | 309 | | matches | | 0 | "He held his ivory-handled cane" | | 1 | "His left eye caught the" | | 2 | "She had not expected him." | | 3 | "You forgot something." | | 4 | "He stepped past her shoulder." | | 5 | "He did not wait for" | | 6 | "His boots tracked muddy water" | | 7 | "He set the cane against" | | 8 | "I have nothing for you." | | 9 | "She watched him move toward" | | 10 | "He ran a gloved finger" | | 11 | "She had left them open" | | 12 | "You always keep your receipts." | | 13 | "He unbuttoned his suit jacket" | | 14 | "He did not remove his" | | 15 | "He never did until he" | | 16 | "She stepped over a rolled" | | 17 | "He weighed it in his" | | 18 | "He had broken it during" | | 19 | "It is a retrieval." |
| | ratio | 0.466 | |
| 32.82% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 264 | | totalSentences | 309 | | matches | | 0 | "The third deadbolt slid back" | | 1 | "Rory pulled the door inward." | | 2 | "The hinges groaned against the" | | 3 | "Lucien Moreau stood on the" | | 4 | "Rain streaked the shoulders of" | | 5 | "A water bead clung to" | | 6 | "He held his ivory-handled cane" | | 7 | "Platinum hair plastered to his" | | 8 | "His left eye caught the" | | 9 | "Amber burned there." | | 10 | "The right swallowed it whole." | | 11 | "Rory’s grip tightened on the" | | 12 | "Knuckles bleached white." | | 13 | "The crescent scar on her" | | 14 | "She had not expected him." | | 15 | "You forgot something." | | 16 | "He stepped past her shoulder." | | 17 | "The door swung shut behind" | | 18 | "He did not wait for" | | 19 | "His boots tracked muddy water" |
| | ratio | 0.854 | |
| 16.18% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 309 | | matches | | 0 | "Now her mouth watered at" |
| | ratio | 0.003 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |