| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 97.20% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1788 | | 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) | |
| 63.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1788 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "footsteps" | | 1 | "weight" | | 2 | "stomach" | | 3 | "echoed" | | 4 | "efficient" | | 5 | "eyebrow" | | 6 | "flicked" | | 7 | "warmth" | | 8 | "pounding" | | 9 | "pulse" | | 10 | "silence" |
| |
| 33.33% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 3 | | maxInWindow | 3 | | found | | 0 | | label | "let out a breath" | | count | 1 |
| | 1 | | label | "stomach dropped/sank" | | count | 1 |
| | 2 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "let out a breath" | | 1 | "stomach dropped" | | 2 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 153 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 153 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 208 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1788 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 29.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 101 | | wordCount | 1493 | | uniqueNames | 15 | | maxNameDensity | 2.41 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Moreau | 1 | | Eva | 8 | | Rory | 36 | | Brick | 2 | | Lane | 2 | | Avaros | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Cardiff | 1 | | Welsh-English | 1 | | Marseille | 1 | | Lucien | 35 | | Water | 3 | | Ptolemy | 5 | | Tea | 3 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "Yu-Fei" | | 4 | "Cheung" | | 5 | "Lucien" | | 6 | "Water" | | 7 | "Ptolemy" | | 8 | "Tea" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Avaros" | | 3 | "Cardiff" | | 4 | "Marseille" |
| | globalScore | 0.294 | | windowScore | 0.5 | |
| 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 | 1788 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 208 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 124 | | mean | 14.42 | | std | 12.44 | | cv | 0.863 | | sampleLengths | | 0 | 11 | | 1 | 33 | | 2 | 56 | | 3 | 15 | | 4 | 4 | | 5 | 10 | | 6 | 3 | | 7 | 46 | | 8 | 4 | | 9 | 17 | | 10 | 3 | | 11 | 17 | | 12 | 5 | | 13 | 35 | | 14 | 5 | | 15 | 8 | | 16 | 4 | | 17 | 5 | | 18 | 2 | | 19 | 35 | | 20 | 17 | | 21 | 8 | | 22 | 8 | | 23 | 4 | | 24 | 30 | | 25 | 4 | | 26 | 14 | | 27 | 5 | | 28 | 37 | | 29 | 6 | | 30 | 20 | | 31 | 6 | | 32 | 13 | | 33 | 10 | | 34 | 24 | | 35 | 6 | | 36 | 10 | | 37 | 4 | | 38 | 5 | | 39 | 9 | | 40 | 16 | | 41 | 8 | | 42 | 9 | | 43 | 2 | | 44 | 32 | | 45 | 49 | | 46 | 34 | | 47 | 4 | | 48 | 5 | | 49 | 43 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 153 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 240 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 208 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1498 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.022696929238985315 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0020026702269692926 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 208 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 208 | | mean | 8.6 | | std | 5.69 | | cv | 0.662 | | sampleLengths | | 0 | 11 | | 1 | 15 | | 2 | 13 | | 3 | 5 | | 4 | 16 | | 5 | 14 | | 6 | 26 | | 7 | 7 | | 8 | 8 | | 9 | 4 | | 10 | 4 | | 11 | 6 | | 12 | 3 | | 13 | 7 | | 14 | 28 | | 15 | 11 | | 16 | 4 | | 17 | 14 | | 18 | 3 | | 19 | 3 | | 20 | 9 | | 21 | 8 | | 22 | 5 | | 23 | 14 | | 24 | 13 | | 25 | 8 | | 26 | 5 | | 27 | 8 | | 28 | 4 | | 29 | 5 | | 30 | 2 | | 31 | 11 | | 32 | 7 | | 33 | 17 | | 34 | 4 | | 35 | 13 | | 36 | 8 | | 37 | 8 | | 38 | 4 | | 39 | 3 | | 40 | 27 | | 41 | 4 | | 42 | 8 | | 43 | 6 | | 44 | 5 | | 45 | 7 | | 46 | 13 | | 47 | 17 | | 48 | 6 | | 49 | 4 |
| |
| 49.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.25961538461538464 | | totalSentences | 208 | | uniqueOpeners | 54 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 152 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 152 | | matches | | 0 | "His platinum hair lay slicked" | | 1 | "Her bare feet curled against" | | 2 | "She folded her arms to" | | 3 | "Her left wrist caught the" | | 4 | "His gaze lingered on the" | | 5 | "He shifted his weight and" | | 6 | "He looked too tall for" | | 7 | "Her black shoulder-length hair fell" | | 8 | "His sleeve brushed her shoulder." | | 9 | "Her bright blue eyes caught" | | 10 | "Their fingers brushed over paper." | | 11 | "His shoes left damp prints" | | 12 | "He draped the wet wool" | | 13 | "His shirt stuck to his" | | 14 | "Their knuckles knocked." | | 15 | "He never flinched." | | 16 | "He twisted the ivory handle." | | 17 | "His pulse hammered against her" | | 18 | "She pulled a heavy Welsh-English" | | 19 | "She welcomed the sting." |
| | ratio | 0.164 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 147 | | totalSentences | 152 | | matches | | 0 | "Rory thumbed the last deadbolt" | | 1 | "Paper dust and cumin hung" | | 2 | "Lucien Moreau filled the landing." | | 3 | "Rain beaded on the shoulders" | | 4 | "Water tracked down the ivory" | | 5 | "His platinum hair lay slicked" | | 6 | "Rory gripped the edge of" | | 7 | "Her bare feet curled against" | | 8 | "Lucien tilted his head." | | 9 | "A muscle jumped along his" | | 10 | "Rory leaned her shoulder into" | | 11 | "Stacks of Eva's books rose" | | 12 | "Ptolemy, Eva's tabby, wound between" | | 13 | "Lucien lifted his cane an" | | 14 | "The ferrule clicked." | | 15 | "A draught pulled at the" | | 16 | "She folded her arms to" | | 17 | "Lucien glanced past her into" | | 18 | "Neon from the shopfronts bled" | | 19 | "A bus rumbled past and" |
| | ratio | 0.967 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 152 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | 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 | |