| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 100 | | tagDensity | 0.16 | | leniency | 0.32 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1733 | | 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) | |
| 94.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1733 | | 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 | 124 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 124 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 208 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1733 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1103 | | uniqueNames | 11 | | maxNameDensity | 1.99 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 22 | | Camden | 1 | | Veil | 1 | | Market | 1 | | Detective | 2 | | Sergeant | 1 | | Farid | 1 | | Iqbal | 15 | | Eva | 9 | | Venn | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Sergeant" | | 4 | "Iqbal" | | 5 | "Eva" |
| | places | | | globalScore | 0.503 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 81 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1733 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 208 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 126 | | mean | 13.75 | | std | 14.64 | | cv | 1.064 | | sampleLengths | | 0 | 11 | | 1 | 50 | | 2 | 60 | | 3 | 37 | | 4 | 6 | | 5 | 26 | | 6 | 14 | | 7 | 3 | | 8 | 30 | | 9 | 32 | | 10 | 2 | | 11 | 22 | | 12 | 5 | | 13 | 10 | | 14 | 71 | | 15 | 21 | | 16 | 10 | | 17 | 3 | | 18 | 17 | | 19 | 3 | | 20 | 1 | | 21 | 1 | | 22 | 16 | | 23 | 45 | | 24 | 4 | | 25 | 23 | | 26 | 5 | | 27 | 4 | | 28 | 5 | | 29 | 14 | | 30 | 6 | | 31 | 5 | | 32 | 40 | | 33 | 4 | | 34 | 6 | | 35 | 3 | | 36 | 11 | | 37 | 4 | | 38 | 13 | | 39 | 5 | | 40 | 15 | | 41 | 5 | | 42 | 1 | | 43 | 5 | | 44 | 17 | | 45 | 3 | | 46 | 3 | | 47 | 1 | | 48 | 7 | | 49 | 6 |
| |
| 99.60% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 124 | | matches | | 0 | "been pushed" | | 1 | "been cleaned" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 178 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 208 | | ratio | 0.005 | | matches | | 0 | "Metal scraped against metal; the lock opened." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1104 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.016304347826086956 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0018115942028985507 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 208 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 208 | | mean | 8.33 | | std | 5.46 | | cv | 0.655 | | sampleLengths | | 0 | 11 | | 1 | 10 | | 2 | 6 | | 3 | 7 | | 4 | 27 | | 5 | 10 | | 6 | 18 | | 7 | 18 | | 8 | 14 | | 9 | 12 | | 10 | 12 | | 11 | 13 | | 12 | 6 | | 13 | 19 | | 14 | 7 | | 15 | 14 | | 16 | 3 | | 17 | 30 | | 18 | 6 | | 19 | 4 | | 20 | 22 | | 21 | 2 | | 22 | 22 | | 23 | 5 | | 24 | 4 | | 25 | 6 | | 26 | 13 | | 27 | 12 | | 28 | 9 | | 29 | 22 | | 30 | 15 | | 31 | 9 | | 32 | 4 | | 33 | 8 | | 34 | 5 | | 35 | 5 | | 36 | 3 | | 37 | 17 | | 38 | 3 | | 39 | 1 | | 40 | 1 | | 41 | 16 | | 42 | 4 | | 43 | 19 | | 44 | 9 | | 45 | 6 | | 46 | 7 | | 47 | 4 | | 48 | 5 | | 49 | 18 |
| |
| 58.81% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3701923076923077 | | totalSentences | 208 | | uniqueOpeners | 77 | |
| 30.58% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 109 | | matches | | 0 | "Only the lever frame remained," |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 109 | | matches | | 0 | "She stepped into the disused" | | 1 | "Its stalls had been pushed" | | 2 | "Its brass handle shone where" | | 3 | "She did not cross it." | | 4 | "He tapped his notebook with" | | 5 | "She tucked a loose strand" | | 6 | "It had soaked the hem" | | 7 | "His left hand curled around" | | 8 | "He could have been sitting." | | 9 | "It had dried pale, almost" | | 10 | "She pointed to a faint" | | 11 | "It had not come from" | | 12 | "He studied the floor again." | | 13 | "It held steady, aimed away" | | 14 | "She took a steel ruler" | | 15 | "She lowered the ruler until" | | 16 | "She moved the ruler away" | | 17 | "He crouched to inspect the" | | 18 | "She reached the clean strip." | | 19 | "It pointed straight at the" |
| | ratio | 0.193 | |
| 70.09% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 109 | | matches | | 0 | "The stairwell ended at a" | | 1 | "Detective Harlow Quinn passed her" | | 2 | "A narrow hand drew it" | | 3 | "Metal scraped against metal; the" | | 4 | "She stepped into the disused" | | 5 | "The Veil Market occupied the" | | 6 | "Its stalls had been pushed" | | 7 | "A man in a fox" | | 8 | "Quinn kept her eyes on" | | 9 | "A forensic photographer crouched at" | | 10 | "Quinn glanced at his notebook" | | 11 | "The door stood open." | | 12 | "Its brass handle shone where" | | 13 | "The room had once held" | | 14 | "Someone had set a folding" | | 15 | "Blood had spread beneath his" | | 16 | "A small brass compass rested" | | 17 | "Verdigris clouded its casing." | | 18 | "Fine marks, almost like thorns," | | 19 | "Quinn crouched at the threshold." |
| | ratio | 0.78 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 109 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 100 | | tagDensity | 0.13 | | leniency | 0.26 | | rawRatio | 0 | | effectiveRatio | 0 | |