| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn stepped back [back]" | | 1 | "She turned again [again]" |
| | dialogueSentences | 70 | | tagDensity | 0.271 | | leniency | 0.543 | | rawRatio | 0.105 | | effectiveRatio | 0.057 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1223 | | 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) | |
| 91.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1223 | | 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 | 65 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 65 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1223 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 48.99% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 594 | | uniqueNames | 4 | | maxNameDensity | 2.02 | | worstName | "Okafor" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Okafor" | | discoveredNames | | Camden | 1 | | Okafor | 12 | | Quinn | 10 | | Rectangles | 1 |
| | persons | | | places | (empty) | | globalScore | 0.49 | | windowScore | 0.833 | |
| 91.86% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like every other tile, smeared wit" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1223 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 62 | | mean | 19.73 | | std | 19.08 | | cv | 0.967 | | sampleLengths | | 0 | 60 | | 1 | 38 | | 2 | 3 | | 3 | 5 | | 4 | 5 | | 5 | 3 | | 6 | 4 | | 7 | 56 | | 8 | 7 | | 9 | 52 | | 10 | 3 | | 11 | 6 | | 12 | 61 | | 13 | 4 | | 14 | 15 | | 15 | 4 | | 16 | 1 | | 17 | 19 | | 18 | 57 | | 19 | 5 | | 20 | 14 | | 21 | 8 | | 22 | 18 | | 23 | 15 | | 24 | 38 | | 25 | 5 | | 26 | 5 | | 27 | 20 | | 28 | 35 | | 29 | 9 | | 30 | 12 | | 31 | 5 | | 32 | 3 | | 33 | 24 | | 34 | 4 | | 35 | 3 | | 36 | 16 | | 37 | 69 | | 38 | 8 | | 39 | 32 | | 40 | 8 | | 41 | 7 | | 42 | 39 | | 43 | 39 | | 44 | 24 | | 45 | 3 | | 46 | 31 | | 47 | 6 | | 48 | 23 | | 49 | 6 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 98 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 116 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 595 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.021848739495798318 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0033613445378151263 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 10.54 | | std | 9.72 | | cv | 0.922 | | sampleLengths | | 0 | 13 | | 1 | 15 | | 2 | 7 | | 3 | 25 | | 4 | 18 | | 5 | 20 | | 6 | 3 | | 7 | 5 | | 8 | 5 | | 9 | 2 | | 10 | 1 | | 11 | 4 | | 12 | 16 | | 13 | 7 | | 14 | 11 | | 15 | 22 | | 16 | 5 | | 17 | 2 | | 18 | 7 | | 19 | 45 | | 20 | 3 | | 21 | 6 | | 22 | 11 | | 23 | 13 | | 24 | 11 | | 25 | 26 | | 26 | 4 | | 27 | 14 | | 28 | 1 | | 29 | 4 | | 30 | 1 | | 31 | 2 | | 32 | 14 | | 33 | 3 | | 34 | 30 | | 35 | 27 | | 36 | 5 | | 37 | 14 | | 38 | 7 | | 39 | 1 | | 40 | 13 | | 41 | 5 | | 42 | 5 | | 43 | 10 | | 44 | 29 | | 45 | 9 | | 46 | 5 | | 47 | 5 | | 48 | 4 | | 49 | 16 |
| |
| 98.28% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.603448275862069 | | totalSentences | 116 | | uniqueOpeners | 70 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 54 | | matches | | 0 | "She pointed her torch at" | | 1 | "She swept the beam over" | | 2 | "She stood, and her knees" | | 3 | "He crouched beside her, grimacing." | | 4 | "Her boots left clean prints" | | 5 | "She stopped and turned around." | | 6 | "She swung the torch flat" | | 7 | "His mouth tightened." | | 8 | "She turned her wrist, and" | | 9 | "She turned again, walking a" | | 10 | "She held it up to" | | 11 | "She looked at the bare" | | 12 | "She tucked the bag inside" |
| | ratio | 0.241 | |
| 6.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 54 | | matches | | 0 | "The stairwell to the old" | | 1 | "Quinn took the last step," | | 2 | "Cream and green, cracked like" | | 3 | "Somebody had strung police tape" | | 4 | "DS Okafor waited by the" | | 5 | "The body lay on the" | | 6 | "A dark crust of blood" | | 7 | "Quinn crouched, and the worn" | | 8 | "Okafor nodded at the pillars" | | 9 | "Quinn lifted the corner of" | | 10 | "The lining of the inside" | | 11 | "She pointed her torch at" | | 12 | "A tidy dark halo spread" | | 13 | "She swept the beam over" | | 14 | "Okafor rubbed the back of" | | 15 | "She stood, and her knees" | | 16 | "He crouched beside her, grimacing." | | 17 | "Quinn stepped back and studied" | | 18 | "Neither of them spoke." | | 19 | "Water dripped somewhere in the" |
| | ratio | 0.907 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 54 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 70 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0.2 | | effectiveRatio | 0.029 | |