| 78.79% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Harlow stepped right [right]" | | 1 | "Eva spoke fast [fast]" |
| | dialogueSentences | 33 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0.133 | | effectiveRatio | 0.121 | |
| 96.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1344 | | 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) | |
| 25.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1344 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "stark" | | 1 | "perfect" | | 2 | "etched" | | 3 | "scanned" | | 4 | "tracing" | | 5 | "glint" | | 6 | "shattered" | | 7 | "intricate" | | 8 | "crystal" | | 9 | "vibrated" | | 10 | "magnetic" | | 11 | "traced" | | 12 | "structure" | | 13 | "fragmented" | | 14 | "standard" |
| |
| 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 | 93 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 111 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1340 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 31.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 927 | | uniqueNames | 7 | | maxNameDensity | 2.37 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | Victorian | 1 | | Quinn | 1 | | London | 1 | | Kowalski | 1 | | Harlow | 22 | | Eva | 10 |
| | persons | | 0 | "Quinn" | | 1 | "Kowalski" | | 2 | "Harlow" | | 3 | "Eva" |
| | places | | | globalScore | 0.313 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | 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 | 1340 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 111 | | matches | (empty) | |
| 68.31% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 38 | | mean | 35.26 | | std | 13.72 | | cv | 0.389 | | sampleLengths | | 0 | 64 | | 1 | 43 | | 2 | 54 | | 3 | 47 | | 4 | 27 | | 5 | 50 | | 6 | 21 | | 7 | 41 | | 8 | 43 | | 9 | 46 | | 10 | 16 | | 11 | 46 | | 12 | 25 | | 13 | 58 | | 14 | 27 | | 15 | 35 | | 16 | 35 | | 17 | 22 | | 18 | 7 | | 19 | 15 | | 20 | 54 | | 21 | 32 | | 22 | 19 | | 23 | 35 | | 24 | 22 | | 25 | 22 | | 26 | 47 | | 27 | 27 | | 28 | 42 | | 29 | 38 | | 30 | 27 | | 31 | 22 | | 32 | 46 | | 33 | 42 | | 34 | 22 | | 35 | 20 | | 36 | 52 | | 37 | 49 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 153 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 111 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 930 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 17 | | adverbRatio | 0.01827956989247312 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.007526881720430108 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 111 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 111 | | mean | 12.07 | | std | 6.74 | | cv | 0.559 | | sampleLengths | | 0 | 17 | | 1 | 19 | | 2 | 11 | | 3 | 1 | | 4 | 9 | | 5 | 7 | | 6 | 13 | | 7 | 7 | | 8 | 10 | | 9 | 13 | | 10 | 8 | | 11 | 8 | | 12 | 17 | | 13 | 21 | | 14 | 10 | | 15 | 37 | | 16 | 9 | | 17 | 6 | | 18 | 12 | | 19 | 28 | | 20 | 22 | | 21 | 9 | | 22 | 12 | | 23 | 13 | | 24 | 28 | | 25 | 12 | | 26 | 15 | | 27 | 5 | | 28 | 4 | | 29 | 7 | | 30 | 14 | | 31 | 32 | | 32 | 6 | | 33 | 10 | | 34 | 15 | | 35 | 31 | | 36 | 7 | | 37 | 11 | | 38 | 7 | | 39 | 9 | | 40 | 11 | | 41 | 12 | | 42 | 26 | | 43 | 16 | | 44 | 11 | | 45 | 14 | | 46 | 8 | | 47 | 13 | | 48 | 12 | | 49 | 23 |
| |
| 41.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2818181818181818 | | totalSentences | 110 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 92.53% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 91 | | matches | | 0 | "She dropped her arm and" | | 1 | "Her spine snapped into perfect" | | 2 | "She gripped the strap of" | | 3 | "She pushed her round glasses" | | 4 | "Her boots crunched over pulverized" | | 5 | "She stopped next to a" | | 6 | "She ran a gloved finger" | | 7 | "She wiped her fingertip." | | 8 | "She retrieved a pocket tape" | | 9 | "She extended the metal strip," | | 10 | "She moved from one drop" | | 11 | "Her green eyes darted toward" | | 12 | "She swept her flashlight beam" | | 13 | "She reached beneath a shattered" | | 14 | "It was a compact brass" | | 15 | "She turned it over in" | | 16 | "Her leather satchel bumped against" | | 17 | "She held the brass instrument" | | 18 | "It spun past the symbols," | | 19 | "She stepped backward, increasing her" |
| | ratio | 0.319 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 91 | | matches | | 0 | "Water dripped from the vaulted" | | 1 | "Harlow Quinn checked the worn" | | 2 | "She dropped her arm and" | | 3 | "Her spine snapped into perfect" | | 4 | "The cavernous space beneath London" | | 5 | "Eva Kowalski stood near the" | | 6 | "The harsh light washed out" | | 7 | "She gripped the strap of" | | 8 | "She pushed her round glasses" | | 9 | "Eva swept a hand toward" | | 10 | "Harlow paced the outer edge" | | 11 | "Her boots crunched over pulverized" | | 12 | "She stopped next to a" | | 13 | "Harlow pointed to the thick" | | 14 | "Eva shifted the heavy satchel" | | 15 | "Harlow kept her brown eyes" | | 16 | "Harlow crouched beside the crumpled" | | 17 | "She ran a gloved finger" | | 18 | "The groove felt freezing cold." | | 19 | "She wiped her fingertip." |
| | ratio | 0.934 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 91 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Eva spoke fast (speak)" |
| | dialogueSentences | 33 | | tagDensity | 0.03 | | leniency | 0.061 | | rawRatio | 1 | | effectiveRatio | 0.061 | |