| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 126 | | tagDensity | 0.175 | | leniency | 0.349 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.40% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1923 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 58.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1923 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "scanned" | | 1 | "structure" | | 2 | "warmth" | | 3 | "silence" | | 4 | "tension" | | 5 | "rhythmic" | | 6 | "vibrated" | | 7 | "traced" | | 8 | "weight" | | 9 | "throbbed" | | 10 | "echoed" | | 11 | "flickered" |
| |
| 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 | 278 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 278 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 382 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1923 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 98 | | wordCount | 1528 | | uniqueNames | 13 | | maxNameDensity | 2.49 | | worstName | "Aurora" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Eva" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Blackwood | 1 | | Prague | 3 | | Aurora | 38 | | Eva | 21 | | Berlin | 1 | | Silas | 25 | | Cardiff | 3 | | Manchester | 1 | | Evan | 1 |
| | persons | | 0 | "Carter" | | 1 | "Blackwood" | | 2 | "Aurora" | | 3 | "Eva" | | 4 | "Silas" | | 5 | "Evan" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Prague" | | 3 | "Berlin" | | 4 | "Cardiff" | | 5 | "Manchester" |
| | globalScore | 0.257 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 105 | | 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 | 1923 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 382 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 161 | | mean | 11.94 | | std | 13.13 | | cv | 1.099 | | sampleLengths | | 0 | 84 | | 1 | 43 | | 2 | 39 | | 3 | 6 | | 4 | 27 | | 5 | 16 | | 6 | 8 | | 7 | 4 | | 8 | 1 | | 9 | 1 | | 10 | 21 | | 11 | 14 | | 12 | 3 | | 13 | 16 | | 14 | 14 | | 15 | 23 | | 16 | 7 | | 17 | 2 | | 18 | 2 | | 19 | 2 | | 20 | 17 | | 21 | 6 | | 22 | 4 | | 23 | 1 | | 24 | 18 | | 25 | 1 | | 26 | 7 | | 27 | 20 | | 28 | 10 | | 29 | 1 | | 30 | 2 | | 31 | 22 | | 32 | 21 | | 33 | 5 | | 34 | 7 | | 35 | 6 | | 36 | 23 | | 37 | 9 | | 38 | 1 | | 39 | 4 | | 40 | 9 | | 41 | 18 | | 42 | 2 | | 43 | 1 | | 44 | 13 | | 45 | 2 | | 46 | 4 | | 47 | 20 | | 48 | 15 | | 49 | 2 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 278 | | matches | | 0 | "was yellowed" | | 1 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 299 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 382 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1531 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 19 | | adverbRatio | 0.012410189418680601 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.001959503592423253 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 382 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 382 | | mean | 5.03 | | std | 2.72 | | cv | 0.54 | | sampleLengths | | 0 | 22 | | 1 | 13 | | 2 | 11 | | 3 | 8 | | 4 | 14 | | 5 | 12 | | 6 | 4 | | 7 | 8 | | 8 | 9 | | 9 | 18 | | 10 | 8 | | 11 | 6 | | 12 | 4 | | 13 | 11 | | 14 | 9 | | 15 | 9 | | 16 | 2 | | 17 | 4 | | 18 | 5 | | 19 | 5 | | 20 | 12 | | 21 | 5 | | 22 | 7 | | 23 | 9 | | 24 | 5 | | 25 | 3 | | 26 | 4 | | 27 | 1 | | 28 | 1 | | 29 | 7 | | 30 | 10 | | 31 | 4 | | 32 | 8 | | 33 | 6 | | 34 | 3 | | 35 | 12 | | 36 | 4 | | 37 | 7 | | 38 | 7 | | 39 | 10 | | 40 | 8 | | 41 | 5 | | 42 | 7 | | 43 | 2 | | 44 | 2 | | 45 | 2 | | 46 | 10 | | 47 | 6 | | 48 | 1 | | 49 | 3 |
| |
| 25.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 102 | | diversityRatio | 0.14136125654450263 | | totalSentences | 382 | | uniqueOpeners | 54 | |
| 13.12% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 254 | | matches | | 0 | "Only the streetlights outside cast" |
| | ratio | 0.004 | |
| 5.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 136 | | totalSentences | 254 | | matches | | 0 | "She watched the door." | | 1 | "His silver signet ring glinted" | | 2 | "He moved with a slight" | | 3 | "He did not look up" | | 4 | "She wore a coat that" | | 5 | "Her hair was cut short," | | 6 | "She scanned the room, her" | | 7 | "She stopped two feet away." | | 8 | "Her face held the same" | | 9 | "Her voice sounded rough, like" | | 10 | "He watched the exchange over" | | 11 | "He did not interrupt." | | 12 | "He slid it across the" | | 13 | "She did not touch it." | | 14 | "She took a sip." | | 15 | "Her bright blue eyes locked" | | 16 | "He stood still, his hazel" | | 17 | "He waited for them to" | | 18 | "She pulled out a small" | | 19 | "She placed it on the" |
| | ratio | 0.535 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 249 | | totalSentences | 254 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora Carter leaned against the" | | 2 | "The small crescent-shaped scar caught" | | 3 | "She watched the door." | | 4 | "Silas Blackwood polished a glass" | | 5 | "His silver signet ring glinted" | | 6 | "He moved with a slight" | | 7 | "He did not look up" | | 8 | "The bell above the door" | | 9 | "A woman stepped inside." | | 10 | "She wore a coat that" | | 11 | "Her hair was cut short," | | 12 | "She scanned the room, her" | | 13 | "The movement felt stiff." | | 14 | "The woman approached the counter." | | 15 | "She stopped two feet away." | | 16 | "Her face held the same" | | 17 | "the woman said" | | 18 | "Her voice sounded rough, like" | | 19 | "Aurora pushed off the counter." |
| | ratio | 0.98 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 254 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 126 | | tagDensity | 0.135 | | leniency | 0.27 | | rawRatio | 0 | | effectiveRatio | 0 | |