| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 923 | | 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) | |
| 45.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 923 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "pulse" | | 1 | "warmth" | | 2 | "familiar" | | 3 | "pulsed" | | 4 | "could feel" | | 5 | "loomed" |
| |
| 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 | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 111 | | filterMatches | (empty) | | hedgeMatches | | 0 | "started to" | | 1 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 117 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 923 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 883 | | uniqueNames | 11 | | maxNameDensity | 0.68 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 | | Isolde | 1 | | Earth | 1 | | Fae | 1 | | Cardiff | 1 | | Evan | 1 | | Rory | 6 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Golden" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 91.66% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.083 | | wordCount | 923 | | matches | | 0 | "not stone, but the local name had stuck" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 117 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 29.77 | | std | 21.68 | | cv | 0.728 | | sampleLengths | | 0 | 50 | | 1 | 95 | | 2 | 38 | | 3 | 56 | | 4 | 3 | | 5 | 5 | | 6 | 36 | | 7 | 39 | | 8 | 84 | | 9 | 8 | | 10 | 36 | | 11 | 7 | | 12 | 37 | | 13 | 1 | | 14 | 35 | | 15 | 34 | | 16 | 28 | | 17 | 13 | | 18 | 5 | | 19 | 51 | | 20 | 31 | | 21 | 35 | | 22 | 8 | | 23 | 36 | | 24 | 25 | | 25 | 24 | | 26 | 7 | | 27 | 12 | | 28 | 26 | | 29 | 30 | | 30 | 28 |
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| 98.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 111 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 149 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 117 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 127 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 2 | | adverbRatio | 0.015748031496062992 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 117 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 117 | | mean | 7.89 | | std | 5.53 | | cv | 0.7 | | sampleLengths | | 0 | 9 | | 1 | 10 | | 2 | 14 | | 3 | 13 | | 4 | 4 | | 5 | 17 | | 6 | 25 | | 7 | 11 | | 8 | 15 | | 9 | 24 | | 10 | 3 | | 11 | 15 | | 12 | 9 | | 13 | 4 | | 14 | 10 | | 15 | 5 | | 16 | 11 | | 17 | 8 | | 18 | 17 | | 19 | 8 | | 20 | 7 | | 21 | 3 | | 22 | 3 | | 23 | 2 | | 24 | 4 | | 25 | 16 | | 26 | 16 | | 27 | 9 | | 28 | 2 | | 29 | 16 | | 30 | 3 | | 31 | 4 | | 32 | 5 | | 33 | 9 | | 34 | 21 | | 35 | 12 | | 36 | 14 | | 37 | 28 | | 38 | 3 | | 39 | 5 | | 40 | 5 | | 41 | 4 | | 42 | 1 | | 43 | 15 | | 44 | 2 | | 45 | 5 | | 46 | 4 | | 47 | 3 | | 48 | 4 | | 49 | 7 |
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| 36.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.3076923076923077 | | totalSentences | 117 | | uniqueOpeners | 36 | |
| 34.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 98 | | matches | | 0 | "Somewhere far off a dog" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 98 | | matches | | 0 | "It hung against her throat" | | 1 | "It had started to pulse" | | 2 | "She had told herself it" | | 3 | "She had checked the scar" | | 4 | "It did not." | | 5 | "She walked past the main" | | 6 | "They formed a loose ring" | | 7 | "She lifted the chain." | | 8 | "She had come because the" | | 9 | "She had laughed at a" | | 10 | "She turned her head." | | 11 | "She took a step into" | | 12 | "Her voice sounded too loud." | | 13 | "It bounced back wrong, as" | | 14 | "She told herself it was" | | 15 | "She crouched and touched a" | | 16 | "They smelled of nothing." | | 17 | "She stood and pressed her" | | 18 | "She pulled the chain free" | | 19 | "She did not run." |
| | ratio | 0.276 | |
| 5.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 98 | | matches | | 0 | "The gate at Richmond Park" | | 1 | "Rory ducked under the chain" | | 2 | "The delivery bag was gone," | | 3 | "The pendant was not." | | 4 | "It hung against her throat" | | 5 | "It had started to pulse" | | 6 | "She had told herself it" | | 7 | "She had checked the scar" | | 8 | "It did not." | | 9 | "She walked past the main" | | 10 | "The park map in her" | | 11 | "Streetlamps thinned to nothing." | | 12 | "The path under the trees" | | 13 | "The standing stones were there." | | 14 | "They formed a loose ring" | | 15 | "Wildflowers bloomed at their feet" | | 16 | "Rory stopped at the edge" | | 17 | "The air inside the clearing" | | 18 | "The pendant warmed." | | 19 | "She lifted the chain." |
| | ratio | 0.908 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 98 | | matches | | 0 | "By the time she reached" | | 1 | "Now she stood in a" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |