| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.588 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1337 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 43.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1337 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "pulse" | | 1 | "weight" | | 2 | "scanned" | | 3 | "velvet" | | 4 | "etched" | | 5 | "firmly" | | 6 | "flickered" | | 7 | "silence" | | 8 | "trembled" | | 9 | "pulsed" | | 10 | "shattered" | | 11 | "vibrated" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 194 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 194 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 196 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 55 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1337 | | ratio | 0 | | matches | (empty) | |
| 98.68% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 2 | | matches | | 0 | "Someone killed him with a weapon, Eva said. Her voice sounded tight. The throat wound is deep." | | 1 | "Asphyxiation without a bag, Eva whispered. She closed the notebook." |
| |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1285 | | uniqueNames | 6 | | maxNameDensity | 2.65 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Kowalski | 1 | | Eva | 16 | | Evans | 2 | | Quinn | 34 |
| | persons | | 0 | "Camden" | | 1 | "Kowalski" | | 2 | "Eva" | | 3 | "Evans" | | 4 | "Quinn" |
| | places | (empty) | | globalScore | 0.177 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | 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 | 1337 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 196 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 114 | | mean | 11.73 | | std | 11.12 | | cv | 0.948 | | sampleLengths | | 0 | 62 | | 1 | 52 | | 2 | 6 | | 3 | 11 | | 4 | 6 | | 5 | 42 | | 6 | 17 | | 7 | 39 | | 8 | 21 | | 9 | 10 | | 10 | 55 | | 11 | 5 | | 12 | 4 | | 13 | 20 | | 14 | 22 | | 15 | 6 | | 16 | 4 | | 17 | 36 | | 18 | 8 | | 19 | 37 | | 20 | 17 | | 21 | 8 | | 22 | 11 | | 23 | 6 | | 24 | 6 | | 25 | 6 | | 26 | 19 | | 27 | 29 | | 28 | 9 | | 29 | 2 | | 30 | 10 | | 31 | 13 | | 32 | 26 | | 33 | 14 | | 34 | 13 | | 35 | 15 | | 36 | 11 | | 37 | 19 | | 38 | 7 | | 39 | 3 | | 40 | 22 | | 41 | 28 | | 42 | 3 | | 43 | 10 | | 44 | 7 | | 45 | 27 | | 46 | 9 | | 47 | 19 | | 48 | 10 | | 49 | 14 |
| |
| 83.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 12 | | totalSentences | 194 | | matches | | 0 | "was gone" | | 1 | "were curled" | | 2 | "was singed" | | 3 | "were covered" | | 4 | "was torn" | | 5 | "was etched" | | 6 | "was gone" | | 7 | "was turned" | | 8 | "was stretched" | | 9 | "was gone" | | 10 | "were gone" | | 11 | "was gone" | | 12 | "was gone" |
| |
| 73.74% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 264 | | matches | | 0 | "wasn’t looking" | | 1 | "was pulling" | | 2 | "was feeding" | | 3 | "was bleeding" | | 4 | "was standing" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 196 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 919 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.01632208922742111 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.00544069640914037 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 196 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 196 | | mean | 6.82 | | std | 6.65 | | cv | 0.975 | | sampleLengths | | 0 | 12 | | 1 | 19 | | 2 | 17 | | 3 | 14 | | 4 | 12 | | 5 | 22 | | 6 | 18 | | 7 | 6 | | 8 | 11 | | 9 | 6 | | 10 | 42 | | 11 | 17 | | 12 | 39 | | 13 | 21 | | 14 | 10 | | 15 | 55 | | 16 | 5 | | 17 | 4 | | 18 | 20 | | 19 | 22 | | 20 | 6 | | 21 | 4 | | 22 | 8 | | 23 | 8 | | 24 | 10 | | 25 | 4 | | 26 | 6 | | 27 | 3 | | 28 | 3 | | 29 | 2 | | 30 | 3 | | 31 | 4 | | 32 | 4 | | 33 | 14 | | 34 | 12 | | 35 | 3 | | 36 | 2 | | 37 | 3 | | 38 | 9 | | 39 | 2 | | 40 | 4 | | 41 | 2 | | 42 | 4 | | 43 | 7 | | 44 | 6 | | 45 | 6 | | 46 | 6 | | 47 | 19 | | 48 | 29 | | 49 | 9 |
| |
| 33.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 33 | | diversityRatio | 0.18877551020408162 | | totalSentences | 196 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 170 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 170 | | matches | | 0 | "She pushed her round glasses" | | 1 | "He wasn’t looking" | | 2 | "It led to a crate" | | 3 | "She pulled the lid." | | 4 | "I’m the investigator." | | 5 | "It wasn’t brass like most," | | 6 | "Her eyes widened." | | 7 | "Her green glasses reflected the" | | 8 | "It jerked violently, searching for" | | 9 | "It points to the nearest" | | 10 | "It was already" | | 11 | "Her voice was steady in" | | 12 | "You could hear the hum" | | 13 | "It was wrong." | | 14 | "It wasn’t cold, it was" | | 15 | "It carried the smell of" | | 16 | "Her voice trembled." | | 17 | "It wasn’t a crack in" | | 18 | "It was a tear in" | | 19 | "His fingers twitched." |
| | ratio | 0.265 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 162 | | totalSentences | 170 | | matches | | 0 | "Quinn stepped over the police" | | 1 | "The abandoned Tube station beneath" | | 2 | "The track was dark, save" | | 3 | "The scent of ozone hung" | | 4 | "Eva Kowalski stood over the" | | 5 | "She pushed her round glasses" | | 6 | "The victim lay face down" | | 7 | "He wasn’t looking" | | 8 | "Eva didn’t look away from" | | 9 | "Pulse was gone. Three hours" | | 10 | "Quinn knelt down. She inspected" | | 11 | "Someone killed him with a" | | 12 | "The constable in the corner," | | 13 | "Asphyxiation without a bag, Eva" | | 14 | "Quinn ignored the constable. She" | | 15 | "This is a ritual site." | | 16 | "The man died here." | | 17 | "The body was just moved," | | 18 | "Eva looked at the floor" | | 19 | "Water carries blood" |
| | ratio | 0.953 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 170 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 1 | | matches | | 0 | "Quinn ignored the constable. She stood up. She scanned the stalls that lined the station walls. They were covered in heavy velvet drapes, obscuring the wares in…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 4 | | fancyTags | | 0 | "Quinn shouted (shout)" | | 1 | "Evans yelled (yell)" | | 2 | "Quinn shouted (shout)" | | 3 | "Quinn shouted (shout)" |
| | dialogueSentences | 17 | | tagDensity | 0.529 | | leniency | 1 | | rawRatio | 0.444 | | effectiveRatio | 0.444 | |