| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 30 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said softly [softly]" |
| | dialogueSentences | 76 | | tagDensity | 0.395 | | leniency | 0.789 | | rawRatio | 0.033 | | effectiveRatio | 0.026 | |
| 91.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1243 | | totalAiIsmAdverbs | 2 | | 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) | |
| 91.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1243 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 163 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1243 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 42 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 92 | | wordCount | 834 | | uniqueNames | 12 | | maxNameDensity | 4.92 | | worstName | "Rory" | | maxWindowNameDensity | 7.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Golden | 2 | | Empress | 2 | | Silas | 9 | | Blackwood | 1 | | Rory | 41 | | Cardiff | 1 | | University | 1 | | Eva | 31 | | Prague | 1 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Blackwood" | | 3 | "Rory" | | 4 | "Eva" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "Prague" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 1243 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 163 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 90 | | mean | 13.81 | | std | 13.24 | | cv | 0.958 | | sampleLengths | | 0 | 59 | | 1 | 77 | | 2 | 17 | | 3 | 5 | | 4 | 16 | | 5 | 5 | | 6 | 43 | | 7 | 6 | | 8 | 35 | | 9 | 1 | | 10 | 46 | | 11 | 9 | | 12 | 15 | | 13 | 6 | | 14 | 20 | | 15 | 57 | | 16 | 6 | | 17 | 11 | | 18 | 4 | | 19 | 5 | | 20 | 27 | | 21 | 18 | | 22 | 5 | | 23 | 5 | | 24 | 11 | | 25 | 9 | | 26 | 13 | | 27 | 12 | | 28 | 12 | | 29 | 5 | | 30 | 10 | | 31 | 2 | | 32 | 9 | | 33 | 10 | | 34 | 6 | | 35 | 23 | | 36 | 2 | | 37 | 3 | | 38 | 3 | | 39 | 22 | | 40 | 17 | | 41 | 8 | | 42 | 20 | | 43 | 5 | | 44 | 10 | | 45 | 8 | | 46 | 9 | | 47 | 37 | | 48 | 18 | | 49 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 116 | | matches | | |
| 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 | 163 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 828 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 18 | | adverbRatio | 0.021739130434782608 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004830917874396135 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 163 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 163 | | mean | 7.63 | | std | 5.18 | | cv | 0.679 | | sampleLengths | | 0 | 23 | | 1 | 23 | | 2 | 13 | | 3 | 10 | | 4 | 18 | | 5 | 21 | | 6 | 14 | | 7 | 14 | | 8 | 11 | | 9 | 6 | | 10 | 5 | | 11 | 5 | | 12 | 7 | | 13 | 4 | | 14 | 5 | | 15 | 5 | | 16 | 12 | | 17 | 26 | | 18 | 6 | | 19 | 2 | | 20 | 20 | | 21 | 13 | | 22 | 1 | | 23 | 3 | | 24 | 10 | | 25 | 13 | | 26 | 20 | | 27 | 7 | | 28 | 2 | | 29 | 10 | | 30 | 5 | | 31 | 6 | | 32 | 12 | | 33 | 4 | | 34 | 4 | | 35 | 6 | | 36 | 4 | | 37 | 27 | | 38 | 8 | | 39 | 12 | | 40 | 6 | | 41 | 5 | | 42 | 6 | | 43 | 4 | | 44 | 5 | | 45 | 9 | | 46 | 14 | | 47 | 4 | | 48 | 8 | | 49 | 5 |
| |
| 40.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.18404907975460122 | | totalSentences | 163 | | uniqueOpeners | 30 | |
| 38.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 86 | | matches | | 0 | "Bright blue eyes swept the" |
| | ratio | 0.012 | |
| 85.12% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 86 | | matches | | 0 | "She had come down for" | | 1 | "His grey-streaked auburn hair sat" | | 2 | "He limped when he moved" | | 3 | "He lifted his chin a" | | 4 | "She set the bag on" | | 5 | "She peeled off her jacket." | | 6 | "She was taller than Rory" | | 7 | "Her coat was expensive, the" | | 8 | "She crossed the room in" | | 9 | "He did not pour." | | 10 | "He did not move." | | 11 | "Her eyes were tired in" | | 12 | "He limped to the booth" | | 13 | "He did not sit." | | 14 | "She kept her coat on." | | 15 | "She blinked quickly." | | 16 | "She thought about the flat" | | 17 | "Her voice stayed even." | | 18 | "She looked down at the" | | 19 | "It remained full." |
| | ratio | 0.337 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 86 | | matches | | 0 | "The green neon sign buzzed" | | 1 | "Rory ducked under it with" | | 2 | "She had come down for" | | 3 | "Maps yellowed at the edges" | | 4 | "The low light caught the" | | 5 | "His grey-streaked auburn hair sat" | | 6 | "He limped when he moved" | | 7 | "Rory lifted her head to" | | 8 | "He lifted his chin a" | | 9 | "She set the bag on" | | 10 | "She peeled off her jacket." | | 11 | "The booth by the window" | | 12 | "The woman looked up and" | | 13 | "The woman stood." | | 14 | "She was taller than Rory" | | 15 | "Her coat was expensive, the" | | 16 | "She crossed the room in" | | 17 | "Eva said into her hair" | | 18 | "Rory laughed, a short sound" | | 19 | "Silas watched from behind the" |
| | ratio | 0.965 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "Bright blue eyes swept the room out of habit, cataloguing exits, the bookshelf that did not sit flush with the wall, the door at the back." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 30 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 30 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 76 | | tagDensity | 0.395 | | leniency | 0.789 | | rawRatio | 0 | | effectiveRatio | 0 | |