| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1004 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 90.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1004 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 83 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 83 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1004 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 43.19% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 749 | | uniqueNames | 12 | | maxNameDensity | 2.14 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Veil | 2 | | Market | 2 | | Tube | 1 | | Kowalski | 1 | | Quinn | 16 | | Compass | 1 | | Metro | 1 | | Metropolitan | 1 | | Police | 1 | | Kell | 1 | | Eva | 9 |
| | persons | | 0 | "Market" | | 1 | "Kowalski" | | 2 | "Quinn" | | 3 | "Compass" | | 4 | "Eva" |
| | places | | | globalScore | 0.432 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1004 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 85.88% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 10 | | mean | 100.4 | | std | 45.24 | | cv | 0.451 | | sampleLengths | | 0 | 67 | | 1 | 43 | | 2 | 42 | | 3 | 73 | | 4 | 145 | | 5 | 168 | | 6 | 164 | | 7 | 130 | | 8 | 86 | | 9 | 86 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 111 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 109 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 749 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 5 | | adverbRatio | 0.006675567423230975 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 9.21 | | std | 5.48 | | cv | 0.595 | | sampleLengths | | 0 | 22 | | 1 | 13 | | 2 | 25 | | 3 | 7 | | 4 | 14 | | 5 | 10 | | 6 | 2 | | 7 | 17 | | 8 | 17 | | 9 | 14 | | 10 | 11 | | 11 | 2 | | 12 | 6 | | 13 | 10 | | 14 | 4 | | 15 | 11 | | 16 | 10 | | 17 | 4 | | 18 | 20 | | 19 | 6 | | 20 | 7 | | 21 | 14 | | 22 | 22 | | 23 | 8 | | 24 | 15 | | 25 | 6 | | 26 | 5 | | 27 | 13 | | 28 | 11 | | 29 | 7 | | 30 | 5 | | 31 | 6 | | 32 | 4 | | 33 | 7 | | 34 | 15 | | 35 | 7 | | 36 | 12 | | 37 | 11 | | 38 | 5 | | 39 | 10 | | 40 | 4 | | 41 | 3 | | 42 | 4 | | 43 | 7 | | 44 | 5 | | 45 | 3 | | 46 | 16 | | 47 | 12 | | 48 | 5 | | 49 | 15 |
| |
| 27.06% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 25 | | diversityRatio | 0.1651376146788991 | | totalSentences | 109 | | uniqueOpeners | 18 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 80 | | matches | | 0 | "She tucked a curl behind" | | 1 | "She did not touch the" | | 2 | "She traced the line from" | | 3 | "It sat flat against the" | | 4 | "It held warmth." | | 5 | "She turned it over." | | 6 | "Her thumbnail found the gap." | | 7 | "They stopped at the body." | | 8 | "She climbed onto a bench" | | 9 | "It carried a signature." | | 10 | "It stepped aside, hand extended," |
| | ratio | 0.138 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 78 | | totalSentences | 80 | | matches | | 0 | "Quinn came down the service" | | 1 | "The Veil Market had chosen" | | 2 | "Stalls leaned against the ticket" | | 3 | "A body lay under a" | | 4 | "The man wore a seller's" | | 5 | "A line ran from ear" | | 6 | "A brass compass lay three" | | 7 | "Eva Kowalski stood over the" | | 8 | "She tucked a curl behind" | | 9 | "She did not touch the" | | 10 | "She traced the line from" | | 11 | "Quinn lifted one boot." | | 12 | "The leather laced tight, but" | | 13 | "The man's feet had not" | | 14 | "Eva pulled a card from" | | 15 | "The card held a sketch" | | 16 | "Quinn turned the brass compass" | | 17 | "Eva glanced at the card." | | 18 | "Quinn held the compass to" | | 19 | "The needle did not tremble." |
| | ratio | 0.975 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |