| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 53 | | tagDensity | 0.019 | | leniency | 0.038 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1305 | | 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) | |
| 77.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1305 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "echoing" | | 1 | "navigated" | | 2 | "weight" | | 3 | "vibrated" | | 4 | "pulse" | | 5 | "silence" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 111 | | filterMatches | (empty) | | hedgeMatches | | |
| 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 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1303 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 41.30% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 966 | | uniqueNames | 7 | | maxNameDensity | 2.17 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Lucien" | | discoveredNames | | Carter | 1 | | Moreau | 1 | | Lucien | 21 | | Brick | 1 | | Lane | 1 | | Aurora | 14 | | Ptolemy | 3 |
| | persons | | 0 | "Carter" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Aurora" | | 4 | "Ptolemy" |
| | places | | | globalScore | 0.413 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | 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 | 1303 | | 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 | 83 | | mean | 15.7 | | std | 18.31 | | cv | 1.166 | | sampleLengths | | 0 | 77 | | 1 | 15 | | 2 | 17 | | 3 | 4 | | 4 | 3 | | 5 | 88 | | 6 | 29 | | 7 | 6 | | 8 | 4 | | 9 | 42 | | 10 | 3 | | 11 | 5 | | 12 | 25 | | 13 | 12 | | 14 | 8 | | 15 | 24 | | 16 | 22 | | 17 | 7 | | 18 | 2 | | 19 | 3 | | 20 | 54 | | 21 | 23 | | 22 | 3 | | 23 | 3 | | 24 | 31 | | 25 | 1 | | 26 | 2 | | 27 | 2 | | 28 | 38 | | 29 | 10 | | 30 | 5 | | 31 | 7 | | 32 | 22 | | 33 | 26 | | 34 | 4 | | 35 | 18 | | 36 | 4 | | 37 | 4 | | 38 | 34 | | 39 | 4 | | 40 | 7 | | 41 | 1 | | 42 | 1 | | 43 | 26 | | 44 | 20 | | 45 | 5 | | 46 | 22 | | 47 | 5 | | 48 | 5 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 111 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 166 | | 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) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 968 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.027892561983471075 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0030991735537190084 | |
| 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 | 7.99 | | std | 5.2 | | cv | 0.651 | | sampleLengths | | 0 | 15 | | 1 | 15 | | 2 | 19 | | 3 | 12 | | 4 | 16 | | 5 | 10 | | 6 | 5 | | 7 | 4 | | 8 | 13 | | 9 | 4 | | 10 | 3 | | 11 | 11 | | 12 | 2 | | 13 | 17 | | 14 | 5 | | 15 | 11 | | 16 | 14 | | 17 | 15 | | 18 | 13 | | 19 | 4 | | 20 | 11 | | 21 | 14 | | 22 | 6 | | 23 | 4 | | 24 | 12 | | 25 | 7 | | 26 | 12 | | 27 | 11 | | 28 | 3 | | 29 | 5 | | 30 | 12 | | 31 | 13 | | 32 | 12 | | 33 | 8 | | 34 | 4 | | 35 | 8 | | 36 | 12 | | 37 | 5 | | 38 | 5 | | 39 | 12 | | 40 | 7 | | 41 | 2 | | 42 | 3 | | 43 | 5 | | 44 | 4 | | 45 | 25 | | 46 | 20 | | 47 | 23 | | 48 | 3 | | 49 | 3 |
| |
| 38.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 18 | | diversityRatio | 0.2147239263803681 | | totalSentences | 163 | | uniqueOpeners | 35 | |
| 64.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 104 | | matches | | 0 | "Then the second." | | 1 | "Then the third." |
| | ratio | 0.019 | |
| 12.31% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 104 | | matches | | 0 | "His platinum hair stuck to" | | 1 | "He leaned on the ivory" | | 2 | "She did not step back." | | 3 | "He closed the door behind" | | 4 | "He navigated the clutter without" | | 5 | "He stopped in the centre" | | 6 | "She crossed her arms over" | | 7 | "He reached into his jacket" | | 8 | "He placed it on top" | | 9 | "His voice stayed low, smooth" | | 10 | "She did not open it." | | 11 | "She held it by the" | | 12 | "He stopped inches from her," | | 13 | "He towered over her, five" | | 14 | "His fingers hovered near her" | | 15 | "He did not touch her." | | 16 | "She pulled her arm back." | | 17 | "He turned away, walking toward" | | 18 | "He looked out at the" | | 19 | "She walked to the pile" |
| | ratio | 0.519 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 101 | | totalSentences | 104 | | matches | | 0 | "Aurora Carter pulled the door" | | 1 | "Lucien Moreau stood on the" | | 2 | "His platinum hair stuck to" | | 3 | "He leaned on the ivory" | | 4 | "Aurora gripped the edge of" | | 5 | "She did not step back." | | 6 | "Lucien lifted his head." | | 7 | "The amber eye caught the" | | 8 | "Aurora turned and walked into" | | 9 | "He closed the door behind" | | 10 | "The sound sealed them inside." | | 11 | "The flat smelled of old" | | 12 | "Stacks of books and scrolls" | | 13 | "Ptolemy, the tabby cat, sat" | | 14 | "The cat stared at Lucien," | | 15 | "Lucien ignored the animal." | | 16 | "He navigated the clutter without" | | 17 | "He stopped in the centre" | | 18 | "Aurora moved to the kitchen" | | 19 | "She crossed her arms over" |
| | ratio | 0.971 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Lucien corrected (correct)" |
| | dialogueSentences | 53 | | tagDensity | 0.019 | | leniency | 0.038 | | rawRatio | 1 | | effectiveRatio | 0.038 | |