| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.35% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1734 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "slightly" | | 2 | "slowly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 65.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1734 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "weight" | | 1 | "traced" | | 2 | "dancing" | | 3 | "throb" | | 4 | "grave" | | 5 | "intensity" | | 6 | "echoed" | | 7 | "throbbed" | | 8 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 285 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 285 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 285 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 19 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1734 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 1734 | | uniqueNames | 7 | | maxNameDensity | 1.15 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Silas | 20 | | Oxford | 1 | | Julian | 16 | | Cambridge | 1 | | Jules | 1 | | Sarah | 2 | | You | 15 |
| | persons | | 0 | "Silas" | | 1 | "Julian" | | 2 | "Jules" | | 3 | "Sarah" | | 4 | "You" |
| | places | | | globalScore | 0.923 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 127 | | 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 | 1734 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 285 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 44.46 | | std | 46.55 | | cv | 1.047 | | sampleLengths | | 0 | 137 | | 1 | 107 | | 2 | 5 | | 3 | 11 | | 4 | 6 | | 5 | 10 | | 6 | 41 | | 7 | 25 | | 8 | 64 | | 9 | 6 | | 10 | 40 | | 11 | 11 | | 12 | 35 | | 13 | 18 | | 14 | 56 | | 15 | 2 | | 16 | 83 | | 17 | 5 | | 18 | 28 | | 19 | 39 | | 20 | 3 | | 21 | 51 | | 22 | 48 | | 23 | 54 | | 24 | 97 | | 25 | 40 | | 26 | 5 | | 27 | 69 | | 28 | 29 | | 29 | 54 | | 30 | 6 | | 31 | 29 | | 32 | 81 | | 33 | 3 | | 34 | 22 | | 35 | 5 | | 36 | 66 | | 37 | 99 | | 38 | 244 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 285 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 361 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 285 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1734 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.025374855824682813 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005190311418685121 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 285 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 285 | | mean | 6.08 | | std | 3.66 | | cv | 0.601 | | sampleLengths | | 0 | 18 | | 1 | 19 | | 2 | 16 | | 3 | 16 | | 4 | 13 | | 5 | 4 | | 6 | 13 | | 7 | 19 | | 8 | 13 | | 9 | 6 | | 10 | 6 | | 11 | 15 | | 12 | 10 | | 13 | 2 | | 14 | 10 | | 15 | 11 | | 16 | 10 | | 17 | 10 | | 18 | 7 | | 19 | 11 | | 20 | 3 | | 21 | 6 | | 22 | 3 | | 23 | 3 | | 24 | 5 | | 25 | 5 | | 26 | 6 | | 27 | 6 | | 28 | 7 | | 29 | 2 | | 30 | 1 | | 31 | 8 | | 32 | 9 | | 33 | 4 | | 34 | 12 | | 35 | 4 | | 36 | 4 | | 37 | 6 | | 38 | 10 | | 39 | 5 | | 40 | 4 | | 41 | 6 | | 42 | 3 | | 43 | 8 | | 44 | 11 | | 45 | 11 | | 46 | 4 | | 47 | 9 | | 48 | 4 | | 49 | 1 |
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| 31.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 53 | | diversityRatio | 0.18596491228070175 | | totalSentences | 285 | | uniqueOpeners | 53 | |
| 26.04% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 256 | | matches | | 0 | "Then I took a match" | | 1 | "Then what do you do?" |
| | ratio | 0.008 | |
| 4.38% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 138 | | totalSentences | 256 | | matches | | 0 | "He traced the rim of" | | 1 | "He watched the door." | | 2 | "He kept his posture straight," | | 3 | "His eyes swept the room," | | 4 | "He didn’t look like the" | | 5 | "He carried a leather satchel" | | 6 | "He walked forward." | | 7 | "He just watched." | | 8 | "You kept the same chair." | | 9 | "I drove past three times" | | 10 | "He didn’t sit immediately." | | 11 | "He leaned against the back" | | 12 | "I thought you vanished." | | 13 | "He didn’t offer a glass." | | 14 | "You look tired, Julian." | | 15 | "He ran a hand through" | | 16 | "He reached out and rested" | | 17 | "You look like you’re already" | | 18 | "I never pack." | | 19 | "I just leave." |
| | ratio | 0.539 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 239 | | totalSentences | 256 | | matches | | 0 | "The green neon sign outside" | | 1 | "Silas sat at the far" | | 2 | "He traced the rim of" | | 3 | "The silver signet ring on" | | 4 | "He watched the door." | | 5 | "The streetlight caught dust motes" | | 6 | "He kept his posture straight," | | 7 | "Time had turned to stone" | | 8 | "The bell above the door" | | 9 | "A man stepped inside, shaking" | | 10 | "His eyes swept the room," | | 11 | "The coat slid off his" | | 12 | "He didn’t look like the" | | 13 | "The hair had thinned to" | | 14 | "Lines carved deep valleys around" | | 15 | "He carried a leather satchel" | | 16 | "He walked forward." | | 17 | "The floorboards creaked under his" | | 18 | "Silas didn’t rise." | | 19 | "He just watched." |
| | ratio | 0.934 | |
| 39.06% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 256 | | matches | | 0 | "If we actually meant it." | | 1 | "If I ask, maybe I’ll" |
| | ratio | 0.008 | |
| 96.27% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 3 | | matches | | 0 | "He traced the rim of his tumbler with a thumb that bore the calluses of decades." | | 1 | "He carried a leather satchel that dragged at his right shoulder." | | 2 | "She doesn’t see the ghost that follows me into grocery stores." |
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| 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 | |