| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1617 | | 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) | |
| 65.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1617 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "perfect" | | 1 | "silence" | | 2 | "throbbed" | | 3 | "stomach" | | 4 | "pulsed" | | 5 | "weight" | | 6 | "pulse" | | 7 | "stark" |
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| 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 | 152 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 152 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 197 | | 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 | 1617 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 58.06% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 1142 | | uniqueNames | 7 | | maxNameDensity | 1.84 | | worstName | "Aurora" | | maxWindowNameDensity | 3 | | worstWindowName | "Aurora" | | discoveredNames | | Eva | 3 | | Bengali | 1 | | Ptolemy | 7 | | Aurora | 21 | | Lucien | 20 | | Carter | 1 | | French | 1 |
| | persons | | 0 | "Eva" | | 1 | "Ptolemy" | | 2 | "Aurora" | | 3 | "Lucien" | | 4 | "Carter" |
| | places | | | globalScore | 0.581 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | 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 | 1617 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 197 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 96 | | mean | 16.84 | | std | 14.2 | | cv | 0.843 | | sampleLengths | | 0 | 4 | | 1 | 33 | | 2 | 5 | | 3 | 4 | | 4 | 55 | | 5 | 10 | | 6 | 1 | | 7 | 9 | | 8 | 3 | | 9 | 5 | | 10 | 40 | | 11 | 13 | | 12 | 4 | | 13 | 11 | | 14 | 10 | | 15 | 9 | | 16 | 29 | | 17 | 4 | | 18 | 2 | | 19 | 25 | | 20 | 4 | | 21 | 15 | | 22 | 30 | | 23 | 54 | | 24 | 15 | | 25 | 3 | | 26 | 15 | | 27 | 8 | | 28 | 2 | | 29 | 50 | | 30 | 12 | | 31 | 7 | | 32 | 13 | | 33 | 28 | | 34 | 8 | | 35 | 13 | | 36 | 16 | | 37 | 26 | | 38 | 24 | | 39 | 19 | | 40 | 63 | | 41 | 11 | | 42 | 11 | | 43 | 7 | | 44 | 5 | | 45 | 17 | | 46 | 8 | | 47 | 15 | | 48 | 6 | | 49 | 21 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 152 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 192 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 197 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1144 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.01486013986013986 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 197 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 197 | | mean | 8.21 | | std | 6.22 | | cv | 0.758 | | sampleLengths | | 0 | 4 | | 1 | 5 | | 2 | 3 | | 3 | 18 | | 4 | 7 | | 5 | 5 | | 6 | 4 | | 7 | 13 | | 8 | 14 | | 9 | 11 | | 10 | 10 | | 11 | 7 | | 12 | 7 | | 13 | 3 | | 14 | 1 | | 15 | 3 | | 16 | 6 | | 17 | 3 | | 18 | 5 | | 19 | 6 | | 20 | 20 | | 21 | 9 | | 22 | 5 | | 23 | 7 | | 24 | 6 | | 25 | 4 | | 26 | 11 | | 27 | 4 | | 28 | 6 | | 29 | 9 | | 30 | 4 | | 31 | 7 | | 32 | 13 | | 33 | 5 | | 34 | 4 | | 35 | 2 | | 36 | 2 | | 37 | 6 | | 38 | 17 | | 39 | 4 | | 40 | 15 | | 41 | 20 | | 42 | 3 | | 43 | 7 | | 44 | 4 | | 45 | 19 | | 46 | 9 | | 47 | 22 | | 48 | 5 | | 49 | 5 |
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| 39.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2233502538071066 | | totalSentences | 197 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 141 | | matches | (empty) | | ratio | 0 | |
| 75.32% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 51 | | totalSentences | 141 | | matches | | 0 | "She pulled the door inward." | | 1 | "He wore the charcoal suit," | | 2 | "His platinum hair lay slicked" | | 3 | "Her knuckles whitened." | | 4 | "She tugged the cuff down." | | 5 | "She stepped aside." | | 6 | "Her bare feet caught on" | | 7 | "He brought the rain with" | | 8 | "He manoeuvred his cane around" | | 9 | "His gaze swept the flat," | | 10 | "He turned back to her." | | 11 | "She threw the deadbolts, one," | | 12 | "She left the chain off." | | 13 | "She snatched a tea towel" | | 14 | "He caught it single-handed, cane" | | 15 | "He dabbed at his hair." | | 16 | "He placed it on the" | | 17 | "His heterochromatic eyes held hers." | | 18 | "He caught the scroll before" | | 19 | "His fingers brushed Aurora's as" |
| | ratio | 0.362 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 134 | | totalSentences | 141 | | matches | | 0 | "The third deadbolt stuck." | | 1 | "Aurora wrenched at the lock." | | 2 | "The metal shrieked." | | 3 | "Curry fat and cumin rose" | | 4 | "Ptolemy wound between her ankles" | | 5 | "She pulled the door inward." | | 6 | "Lucien filled the hall." | | 7 | "He wore the charcoal suit," | | 8 | "His platinum hair lay slicked" | | 9 | "The ivory handle of his" | | 10 | "That stare pinned her to" | | 11 | "Aurora's hand stayed on the" | | 12 | "Her knuckles whitened." | | 13 | "Lucien's mouth curved." | | 14 | "The expression never reached his" | | 15 | "Aurora stepped back half a" | | 16 | "The flat crowded behind her," | | 17 | "The air tasted of paper" | | 18 | "Ptolemy bolted for the bedroom." | | 19 | "Lucien did not move from" |
| | ratio | 0.95 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 141 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "She smelled rain and citrus and the faint sulphur that clung to his demon blood." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0 | | effectiveRatio | 0 | |