| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | 0 | "her knuckles whitened around [around]" |
| | dialogueSentences | 39 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.083 | | effectiveRatio | 0.051 | |
| 89.59% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1441 | | totalAiIsmAdverbs | 3 | | 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) | |
| 72.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1441 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "chill" | | 1 | "flicker" | | 2 | "stomach" | | 3 | "trembled" | | 4 | "charged" | | 5 | "weight" | | 6 | "porcelain" | | 7 | "marble" |
| |
| 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 | 1 | | narrationSentences | 80 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 77 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1434 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 789 | | uniqueNames | 17 | | maxNameDensity | 0.51 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Ptolemy" | | discoveredNames | | Ptolemy | 2 | | Moreau | 1 | | Middle | 1 | | East | 1 | | Syriac | 1 | | Rory | 1 | | Frenchman | 1 | | Aurora | 4 | | Golden | 1 | | Empress | 1 | | Cardiff | 1 | | Greenwich | 1 | | London | 1 | | Mayfair | 1 | | Tube | 1 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Ptolemy" | | 1 | "Moreau" | | 2 | "East" | | 3 | "Rory" | | 4 | "Aurora" |
| | places | | 0 | "Middle" | | 1 | "Cardiff" | | 2 | "Greenwich" | | 3 | "London" | | 4 | "Brick" | | 5 | "Lane" |
| | globalScore | 1 | | windowScore | 1 | |
| 16.07% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 3 | | matches | | 0 | "something like expensive leather and dry, co" | | 1 | "felt like something more before it all" | | 2 | "seemed distant irrelevant" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.697 | | wordCount | 1434 | | matches | | 0 | "not for her, but for the collar of her uniform jacket" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 107 | | matches | | 0 | "heard that name" | | 1 | "burned that part" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 34.98 | | std | 24.49 | | cv | 0.7 | | sampleLengths | | 0 | 48 | | 1 | 33 | | 2 | 12 | | 3 | 82 | | 4 | 12 | | 5 | 49 | | 6 | 65 | | 7 | 5 | | 8 | 40 | | 9 | 58 | | 10 | 19 | | 11 | 6 | | 12 | 101 | | 13 | 48 | | 14 | 8 | | 15 | 44 | | 16 | 25 | | 17 | 52 | | 18 | 35 | | 19 | 1 | | 20 | 33 | | 21 | 13 | | 22 | 69 | | 23 | 17 | | 24 | 4 | | 25 | 49 | | 26 | 49 | | 27 | 7 | | 28 | 88 | | 29 | 22 | | 30 | 2 | | 31 | 23 | | 32 | 49 | | 33 | 18 | | 34 | 65 | | 35 | 38 | | 36 | 28 | | 37 | 46 | | 38 | 10 | | 39 | 24 | | 40 | 37 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 80 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 129 | | matches | (empty) | |
| 9.35% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 107 | | ratio | 0.047 | | matches | | 0 | "It carried a scent beneath the usual aroma of old paper and Ptolemy’s fur—something like expensive leather and dry, cold stone, like a cellar in winter." | | 1 | "Lucien Moreau looked exactly as out of place here as he had the last time he’d sat in that chair, his charcoal suit refusing to wrinkle, his heterochromatic eyes—one amber, one black—tracking her every move." | | 2 | "The Golden Empress uniform—a red and gold polyester jacket—felt cheap and out of place under his gaze." | | 3 | "The scent of him grew stronger—cold air, old money, and something else, something metallic and buried." | | 4 | "The space between them charged, filled with the weight of their history—the arguments in his Mayfair office, the night he’d helped her escape the thing in the Tube tunnels, the coffee they’d shared that had felt like something more before it all went wrong." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 799 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.026282853566958697 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.006257822277847309 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 13.4 | | std | 12.29 | | cv | 0.917 | | sampleLengths | | 0 | 5 | | 1 | 15 | | 2 | 3 | | 3 | 3 | | 4 | 11 | | 5 | 11 | | 6 | 7 | | 7 | 26 | | 8 | 12 | | 9 | 16 | | 10 | 3 | | 11 | 16 | | 12 | 35 | | 13 | 12 | | 14 | 5 | | 15 | 7 | | 16 | 14 | | 17 | 35 | | 18 | 7 | | 19 | 8 | | 20 | 7 | | 21 | 10 | | 22 | 24 | | 23 | 9 | | 24 | 5 | | 25 | 16 | | 26 | 9 | | 27 | 15 | | 28 | 31 | | 29 | 14 | | 30 | 13 | | 31 | 19 | | 32 | 6 | | 33 | 6 | | 34 | 76 | | 35 | 19 | | 36 | 12 | | 37 | 10 | | 38 | 17 | | 39 | 9 | | 40 | 8 | | 41 | 5 | | 42 | 13 | | 43 | 14 | | 44 | 12 | | 45 | 6 | | 46 | 16 | | 47 | 2 | | 48 | 1 | | 49 | 9 |
| |
| 45.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.35514018691588783 | | totalSentences | 107 | | uniqueOpeners | 38 | |
| 45.66% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 73 | | matches | | 0 | "All that existed was this" |
| | ratio | 0.014 | |
| 11.78% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 73 | | matches | | 0 | "She’d double-checked them." | | 1 | "She always did." | | 2 | "She pushed the door open," | | 3 | "It carried a scent beneath" | | 4 | "He didn’t rise." | | 5 | "She kicked the door shut" | | 6 | "She hadn’t mentioned leaving it" | | 7 | "He uncrossed his legs, the" | | 8 | "Her voice was steady, but" | | 9 | "He sighed, a quiet, practiced" | | 10 | "He leaned forward, the light" | | 11 | "She dropped her keys on" | | 12 | "She poured a glass of" | | 13 | "He moved like a shadow" | | 14 | "He was taller than she" | | 15 | "He stopped a few feet" | | 16 | "She hadn’t heard that name" | | 17 | "He let that hang in" | | 18 | "Her heart hammered against her" | | 19 | "She’d done her own research." |
| | ratio | 0.521 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 73 | | matches | | 0 | "The deadbolts were still unlocked." | | 1 | "Aurora’s hand froze on the" | | 2 | "She’d double-checked them." | | 3 | "She always did." | | 4 | "A flicker of unease coiled" | | 5 | "She pushed the door open," | | 6 | "The air in the flat" | | 7 | "It carried a scent beneath" | | 8 | "The voice came from the" | | 9 | "He didn’t rise." | | 10 | "Lucien Moreau looked exactly as" | | 11 | "Ptolemy, the traitor, was curled" | | 12 | "Aurora didn’t lower her keys." | | 13 | "A ghost of a smile" | | 14 | "She kicked the door shut" | | 15 | "The sound was flat, swallowed" | | 16 | "Books formed precarious towers on" | | 17 | "Scrolls tied with faded ribbon" | | 18 | "Eva was somewhere in the" | | 19 | "She hadn’t mentioned leaving it" |
| | ratio | 0.945 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 3 | | matches | | 0 | "He uncrossed, the movement fluid, precise" | | 1 | "He leaned, the light catching the sharp angle of his jaw" | | 2 | "she asked, the word barely audible" |
| |
| 98.72% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "he murmured (murmur)" |
| | dialogueSentences | 39 | | tagDensity | 0.103 | | leniency | 0.205 | | rawRatio | 0.5 | | effectiveRatio | 0.103 | |