| 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 | 1433 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 82.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1433 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "measured" | | 1 | "gleaming" | | 2 | "traced" | | 3 | "weight" |
| |
| 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 | 68 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 85 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 72 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1433 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 722 | | uniqueNames | 11 | | maxNameDensity | 2.35 | | worstName | "Aurora" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Golden | 1 | | Empress | 1 | | London | 1 | | Prague | 1 | | Silas | 7 | | Aurora | 17 | | Eva | 16 | | Soho | 1 | | Ev | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Aurora" | | 4 | "Eva" |
| | places | | 0 | "Golden" | | 1 | "London" | | 2 | "Prague" | | 3 | "Soho" |
| | globalScore | 0.323 | | windowScore | 0.167 | |
| 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 | 1433 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 85 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 33.33 | | std | 19.5 | | cv | 0.585 | | sampleLengths | | 0 | 95 | | 1 | 40 | | 2 | 69 | | 3 | 8 | | 4 | 32 | | 5 | 10 | | 6 | 21 | | 7 | 19 | | 8 | 26 | | 9 | 23 | | 10 | 11 | | 11 | 14 | | 12 | 12 | | 13 | 37 | | 14 | 17 | | 15 | 42 | | 16 | 12 | | 17 | 40 | | 18 | 40 | | 19 | 35 | | 20 | 22 | | 21 | 47 | | 22 | 15 | | 23 | 71 | | 24 | 36 | | 25 | 57 | | 26 | 28 | | 27 | 43 | | 28 | 37 | | 29 | 55 | | 30 | 30 | | 31 | 63 | | 32 | 7 | | 33 | 32 | | 34 | 13 | | 35 | 46 | | 36 | 19 | | 37 | 51 | | 38 | 25 | | 39 | 31 | | 40 | 15 | | 41 | 24 | | 42 | 63 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 68 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 114 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 85 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 722 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.018005540166204988 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002770083102493075 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 85 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 85 | | mean | 16.86 | | std | 14.98 | | cv | 0.888 | | sampleLengths | | 0 | 25 | | 1 | 15 | | 2 | 20 | | 3 | 35 | | 4 | 16 | | 5 | 14 | | 6 | 10 | | 7 | 8 | | 8 | 12 | | 9 | 24 | | 10 | 16 | | 11 | 9 | | 12 | 8 | | 13 | 5 | | 14 | 7 | | 15 | 4 | | 16 | 16 | | 17 | 10 | | 18 | 10 | | 19 | 8 | | 20 | 3 | | 21 | 5 | | 22 | 14 | | 23 | 10 | | 24 | 6 | | 25 | 10 | | 26 | 23 | | 27 | 11 | | 28 | 14 | | 29 | 2 | | 30 | 10 | | 31 | 37 | | 32 | 7 | | 33 | 10 | | 34 | 42 | | 35 | 5 | | 36 | 7 | | 37 | 40 | | 38 | 7 | | 39 | 9 | | 40 | 24 | | 41 | 35 | | 42 | 12 | | 43 | 10 | | 44 | 47 | | 45 | 6 | | 46 | 9 | | 47 | 71 | | 48 | 10 | | 49 | 10 |
| |
| 49.80% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.3058823529411765 | | totalSentences | 85 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 66 | | matches | | 0 | "She set down her bag" | | 1 | "Her hair sat shorter now," | | 2 | "She carried a leather case" | | 3 | "Her gaze swept the interior" | | 4 | "They held the look for" | | 5 | "He poured a measure of" | | 6 | "She nodded once." | | 7 | "She lifted her glass and" | | 8 | "She spoke low enough that" | | 9 | "Her fingers pressed flat against" | | 10 | "She glanced at Silas as" | | 11 | "She flipped the latch and" | | 12 | "She placed it on the" | | 13 | "She folded it again and" | | 14 | "He turned the ring on" | | 15 | "Her finger followed the curve" | | 16 | "She met Eva's eyes directly." | | 17 | "She lifted the case and" | | 18 | "They stood level at the" |
| | ratio | 0.288 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 66 | | matches | | 0 | "The Raven's Nest pulled in" | | 1 | "Aurora sat at the far" | | 2 | "She set down her bag" | | 3 | "Silas leaned on the bar" | | 4 | "Maps from other cities hung" | | 5 | "Aurora watched Silas move toward" | | 6 | "The door pushed inward, hinges" | | 7 | "A woman stood in the" | | 8 | "Her hair sat shorter now," | | 9 | "She carried a leather case" | | 10 | "Her gaze swept the interior" | | 11 | "They held the look for" | | 12 | "Aurora rose from the stool." | | 13 | "Eva crossed the floor, coat" | | 14 | "Neither reached out first." | | 15 | "Eva set the case on" | | 16 | "Years settled between them like" | | 17 | "Silas limped closer and placed" | | 18 | "He poured a measure of" | | 19 | "She nodded once." |
| | ratio | 0.985 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 1 | | matches | | 0 | "Silas closed the register drawer and moved toward a table near the bookshelf that hid the back room access." |
| |
| 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 | |