| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 59 | | tagDensity | 0.22 | | leniency | 0.441 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1470 | | 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) | |
| 48.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1470 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "flicked" | | 1 | "weight" | | 2 | "shattered" | | 3 | "navigate" | | 4 | "tension" | | 5 | "could feel" | | 6 | "charged" | | 7 | "throbbed" | | 8 | "silence" | | 9 | "pulse" | | 10 | "footsteps" | | 11 | "chaotic" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "knuckles turned white" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 151 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 151 | | filterMatches | (empty) | | hedgeMatches | | |
| 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 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1470 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1109 | | uniqueNames | 6 | | maxNameDensity | 1.53 | | worstName | "Lucien" | | maxWindowNameDensity | 3 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | Lucien | 17 | | Aurora | 13 | | Eva | 2 | | Brick | 1 | | Lane | 1 |
| | persons | | 0 | "Moreau" | | 1 | "Lucien" | | 2 | "Aurora" | | 3 | "Eva" |
| | places | | | globalScore | 0.734 | | windowScore | 0.667 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 5 | | matches | | 0 | "smelled like stale beer and rain whenever" | | 1 | "felt like a shield" | | 2 | "smelled like danger and old money" | | 3 | "felt like a lifetime" | | 4 | "smelled like old wood and dust" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1470 | | 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 | 88 | | mean | 16.7 | | std | 14.28 | | cv | 0.855 | | sampleLengths | | 0 | 52 | | 1 | 16 | | 2 | 54 | | 3 | 12 | | 4 | 48 | | 5 | 22 | | 6 | 8 | | 7 | 40 | | 8 | 14 | | 9 | 7 | | 10 | 25 | | 11 | 21 | | 12 | 4 | | 13 | 10 | | 14 | 38 | | 15 | 29 | | 16 | 25 | | 17 | 5 | | 18 | 53 | | 19 | 4 | | 20 | 5 | | 21 | 6 | | 22 | 29 | | 23 | 7 | | 24 | 12 | | 25 | 39 | | 26 | 16 | | 27 | 16 | | 28 | 16 | | 29 | 27 | | 30 | 2 | | 31 | 42 | | 32 | 4 | | 33 | 5 | | 34 | 3 | | 35 | 22 | | 36 | 3 | | 37 | 24 | | 38 | 34 | | 39 | 3 | | 40 | 3 | | 41 | 4 | | 42 | 54 | | 43 | 22 | | 44 | 6 | | 45 | 7 | | 46 | 29 | | 47 | 10 | | 48 | 2 | | 49 | 4 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 151 | | matches | | 0 | "was smashed" | | 1 | "was scrawled" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 205 | | 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 | 234 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.03418803418803419 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.008547008547008548 | |
| 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 | 7.46 | | std | 4.54 | | cv | 0.609 | | sampleLengths | | 0 | 16 | | 1 | 7 | | 2 | 8 | | 3 | 1 | | 4 | 4 | | 5 | 16 | | 6 | 5 | | 7 | 11 | | 8 | 13 | | 9 | 6 | | 10 | 5 | | 11 | 30 | | 12 | 4 | | 13 | 3 | | 14 | 5 | | 15 | 15 | | 16 | 18 | | 17 | 15 | | 18 | 10 | | 19 | 12 | | 20 | 8 | | 21 | 8 | | 22 | 16 | | 23 | 16 | | 24 | 6 | | 25 | 8 | | 26 | 7 | | 27 | 4 | | 28 | 15 | | 29 | 6 | | 30 | 12 | | 31 | 6 | | 32 | 3 | | 33 | 4 | | 34 | 10 | | 35 | 11 | | 36 | 7 | | 37 | 20 | | 38 | 3 | | 39 | 6 | | 40 | 11 | | 41 | 9 | | 42 | 10 | | 43 | 6 | | 44 | 3 | | 45 | 6 | | 46 | 5 | | 47 | 11 | | 48 | 4 | | 49 | 21 |
| |
| 33.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 32 | | diversityRatio | 0.16751269035532995 | | totalSentences | 197 | | uniqueOpeners | 33 | |
| 23.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 141 | | matches | | 0 | "Only a cold, hard determination." |
| | ratio | 0.007 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 88 | | totalSentences | 141 | | matches | | 0 | "She froze, hand hovering over" | | 1 | "She knew the rhythm." | | 2 | "She set the mug down." | | 3 | "She didn't look through the" | | 4 | "She knew who it was." | | 5 | "She turned the lock." | | 6 | "She pulled the door open." | | 7 | "He held his ivory-handled cane" | | 8 | "He crossed the threshold, bringing" | | 9 | "He stopped just inside the" | | 10 | "His voice was low, smooth" | | 11 | "She crossed her arms." | | 12 | "She pulled her sleeve down" | | 13 | "He didn't comment on the" | | 14 | "He never did." | | 15 | "He shifted his weight" | | 16 | "She held the door open" | | 17 | "He turned and leaned against" | | 18 | "She moved to the kitchen" | | 19 | "He pushed off the door" |
| | ratio | 0.624 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 138 | | totalSentences | 141 | | matches | | 0 | "The bass from" | | 1 | "She froze, hand hovering over" | | 2 | "Another knock rattled the door," | | 3 | "She knew the rhythm." | | 4 | "She set the mug down." | | 5 | "The ceramic clinked against the" | | 6 | "Aurora walked to the door," | | 7 | "She didn't look through the" | | 8 | "She knew who it was." | | 9 | "The air in the hallway" | | 10 | "She turned the lock." | | 11 | "The metal clicked." | | 12 | "She pulled the door open." | | 13 | "Lucien Moreau stood on the" | | 14 | "The streetlamp outside cast a" | | 15 | "He held his ivory-handled cane" | | 16 | "The other remained a void," | | 17 | "Lucien stepped forward without waiting" | | 18 | "He crossed the threshold, bringing" | | 19 | "He stopped just inside the" |
| | ratio | 0.979 | |
| 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 | 40 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 59 | | tagDensity | 0.119 | | leniency | 0.237 | | rawRatio | 0 | | effectiveRatio | 0 | |