| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.121 | | leniency | 0.242 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 820 | | totalAiIsmAdverbs | 2 | | 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) | |
| 14.63% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 820 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "scanned" | | 1 | "familiar" | | 2 | "tinged" | | 3 | "measured" | | 4 | "flickered" | | 5 | "tension" | | 6 | "jaw clenched" | | 7 | "raced" | | 8 | "warmth" | | 9 | "pounding" | | 10 | "sense of" | | 11 | "resolve" |
| |
| 0.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 4 | | maxInWindow | 4 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
| | 1 | | label | "jaw/fists clenched" | | count | 1 |
| | 2 | | label | "flicker of emotion" | | count | 1 |
|
| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" | | 2 | "jaw clenched" | | 3 | "a spark of hope" |
| |
| 86.24% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 43 | | matches | | 0 | "g in surprise" | | 1 | "a spark of hope" |
| |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 43 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 72 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 818 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 516 | | uniqueNames | 5 | | maxNameDensity | 3.29 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 2 | | Moreau | 1 | | Lucien | 15 | | Rory | 17 | | Ptolemy | 2 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Rory" | | 4 | "Ptolemy" |
| | places | (empty) | | globalScore | 0 | | windowScore | 0.167 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 40 | | glossingSentenceCount | 3 | | matches | | 0 | "quite name" | | 1 | "quite reach his eyes" | | 2 | "not quite touching" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 818 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 24.06 | | std | 13.3 | | cv | 0.553 | | sampleLengths | | 0 | 67 | | 1 | 43 | | 2 | 18 | | 3 | 26 | | 4 | 13 | | 5 | 27 | | 6 | 14 | | 7 | 30 | | 8 | 13 | | 9 | 34 | | 10 | 9 | | 11 | 37 | | 12 | 27 | | 13 | 2 | | 14 | 31 | | 15 | 18 | | 16 | 30 | | 17 | 30 | | 18 | 20 | | 19 | 31 | | 20 | 23 | | 21 | 43 | | 22 | 30 | | 23 | 31 | | 24 | 40 | | 25 | 2 | | 26 | 35 | | 27 | 16 | | 28 | 18 | | 29 | 12 | | 30 | 15 | | 31 | 8 | | 32 | 10 | | 33 | 15 |
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| 97.10% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 43 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 92 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 72 | | ratio | 0 | | matches | (empty) | |
| 88.46% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 518 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 24 | | adverbRatio | 0.04633204633204633 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.009652509652509652 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 72 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 72 | | mean | 11.36 | | std | 6.41 | | cv | 0.564 | | sampleLengths | | 0 | 22 | | 1 | 20 | | 2 | 25 | | 3 | 15 | | 4 | 7 | | 5 | 21 | | 6 | 18 | | 7 | 14 | | 8 | 8 | | 9 | 4 | | 10 | 8 | | 11 | 5 | | 12 | 15 | | 13 | 10 | | 14 | 2 | | 15 | 7 | | 16 | 7 | | 17 | 20 | | 18 | 10 | | 19 | 9 | | 20 | 4 | | 21 | 8 | | 22 | 15 | | 23 | 11 | | 24 | 3 | | 25 | 6 | | 26 | 16 | | 27 | 21 | | 28 | 10 | | 29 | 17 | | 30 | 2 | | 31 | 8 | | 32 | 9 | | 33 | 14 | | 34 | 9 | | 35 | 9 | | 36 | 8 | | 37 | 22 | | 38 | 13 | | 39 | 17 | | 40 | 9 | | 41 | 11 | | 42 | 10 | | 43 | 21 | | 44 | 16 | | 45 | 7 | | 46 | 8 | | 47 | 35 | | 48 | 17 | | 49 | 13 |
| |
| 56.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3611111111111111 | | totalSentences | 72 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 43 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 43 | | matches | | 0 | "She had been expecting Eva," | | 1 | "Her fingers involuntarily twisted the" | | 2 | "she breathed, her voice tinged" | | 3 | "he said, his voice smooth" | | 4 | "He closed the door behind" | | 5 | "He stopped a few feet" | | 6 | "she repeated, her voice softer" |
| | ratio | 0.163 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 41 | | totalSentences | 43 | | matches | | 0 | "The door to Eva’s flat" | | 1 | "Lucien Moreau’s heterochromatic eyes, one" | | 2 | "The familiar scent of curry" | | 3 | "Rory stood in the middle" | | 4 | "She had been expecting Eva," | | 5 | "Her fingers involuntarily twisted the" | | 6 | "she breathed, her voice tinged" | | 7 | "Lucien’s lips curled into a" | | 8 | "he said, his voice smooth" | | 9 | "Rory’s throat felt dry, and" | | 10 | "Lucien replied, stepping inside without" | | 11 | "He closed the door behind" | | 12 | "Rory crossed her arms, her" | | 13 | "Lucien’s gaze flickered around the" | | 14 | "Rory sighed, the tension in" | | 15 | "Lucien approached her, his movements" | | 16 | "He stopped a few feet" | | 17 | "Rory’s eyes narrowed." | | 18 | "Lucien’s expression darkened, and he" | | 19 | "Rory’s cheeks flushed with a" |
| | ratio | 0.953 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 43 | | matches | | 0 | "Before she could finish, Ptolemy" |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, his voice smooth and measured" | | 1 | "she repeated, her voice softer this time" |
| |
| 89.39% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she breathed (breathe)" | | 1 | "she repeated (repeat)" |
| | dialogueSentences | 33 | | tagDensity | 0.121 | | leniency | 0.242 | | rawRatio | 0.5 | | effectiveRatio | 0.121 | |