| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 954 | | 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) | |
| 52.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 954 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "silence" | | 1 | "echo" | | 2 | "throb" | | 3 | "flickered" | | 4 | "weight" | | 5 | "lurched" | | 6 | "familiar" | | 7 | "scanned" |
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| 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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 954 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 935 | | uniqueNames | 4 | | maxNameDensity | 1.5 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 10 | | Midnight | 1 | | Rory | 14 | | Pembrokeshire | 1 |
| | persons | | | places | | | globalScore | 0.751 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 95.18% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.048 | | wordCount | 954 | | matches | | 0 | "not gradually but in a single step, as if she had walked from a warm room into" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 120 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 26.5 | | std | 17.37 | | cv | 0.655 | | sampleLengths | | 0 | 40 | | 1 | 32 | | 2 | 17 | | 3 | 52 | | 4 | 56 | | 5 | 3 | | 6 | 59 | | 7 | 37 | | 8 | 37 | | 9 | 23 | | 10 | 1 | | 11 | 36 | | 12 | 35 | | 13 | 61 | | 14 | 27 | | 15 | 29 | | 16 | 25 | | 17 | 41 | | 18 | 2 | | 19 | 5 | | 20 | 29 | | 21 | 31 | | 22 | 13 | | 23 | 2 | | 24 | 40 | | 25 | 26 | | 26 | 3 | | 27 | 21 | | 28 | 10 | | 29 | 23 | | 30 | 15 | | 31 | 47 | | 32 | 22 | | 33 | 3 | | 34 | 47 | | 35 | 4 |
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| 96.19% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 116 | | matches | | 0 | "been folded" | | 1 | "been watched" | | 2 | "been followed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 160 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 120 | | ratio | 0 | | matches | (empty) | |
| 99.55% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 938 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.04051172707889126 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006396588486140725 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 7.95 | | std | 5.71 | | cv | 0.718 | | sampleLengths | | 0 | 10 | | 1 | 6 | | 2 | 9 | | 3 | 7 | | 4 | 8 | | 5 | 15 | | 6 | 17 | | 7 | 14 | | 8 | 2 | | 9 | 1 | | 10 | 5 | | 11 | 20 | | 12 | 2 | | 13 | 7 | | 14 | 7 | | 15 | 11 | | 16 | 7 | | 17 | 22 | | 18 | 21 | | 19 | 6 | | 20 | 3 | | 21 | 9 | | 22 | 11 | | 23 | 2 | | 24 | 10 | | 25 | 2 | | 26 | 6 | | 27 | 6 | | 28 | 13 | | 29 | 22 | | 30 | 15 | | 31 | 8 | | 32 | 2 | | 33 | 7 | | 34 | 20 | | 35 | 4 | | 36 | 2 | | 37 | 1 | | 38 | 10 | | 39 | 2 | | 40 | 4 | | 41 | 1 | | 42 | 14 | | 43 | 5 | | 44 | 2 | | 45 | 15 | | 46 | 25 | | 47 | 6 | | 48 | 2 | | 49 | 2 |
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| 51.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.35 | | totalSentences | 120 | | uniqueOpeners | 42 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 101 | | matches | | 0 | "Then a blackbird sang from" | | 1 | "Only the blackbird, now mimicking" | | 2 | "Then the blackbird's song changed." | | 3 | "Exactly how Rory wore her" |
| | ratio | 0.04 | |
| 97.23% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 101 | | matches | | 0 | "Its surface was slick, warm," | | 1 | "She wiped her palm on" | | 2 | "Her heartstone pendant, warm at" | | 3 | "She had come for Eva." | | 4 | "She ducked under the arch" | | 5 | "They bent away from her" | | 6 | "She kept moving toward the" | | 7 | "She held her breath." | | 8 | "She waited for a reply." | | 9 | "She pressed her hand over" | | 10 | "She was certain of it." | | 11 | "She had not heard it" | | 12 | "It changes when you blink." | | 13 | "Her eyes began to burn." | | 14 | "She stared at the table" | | 15 | "She reached the altar." | | 16 | "Her shadow lay in front" | | 17 | "It should have moved when" | | 18 | "It did not." | | 19 | "She lurched backward." |
| | ratio | 0.307 | |
| 68.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 79 | | totalSentences | 101 | | matches | | 0 | "Rory wrenched her hand back" | | 1 | "Its surface was slick, warm," | | 2 | "She wiped her palm on" | | 3 | "The grove didn't need her" | | 4 | "The boundary was two ancient" | | 5 | "Her heartstone pendant, warm at" | | 6 | "She had come for Eva." | | 7 | "The note had been folded" | | 8 | "Eva had been missing for" | | 9 | "Rory had learned not to" | | 10 | "She ducked under the arch" | | 11 | "The temperature dropped not gradually" | | 12 | "The wildflowers underfoot were wrong" | | 13 | "They bent away from her" | | 14 | "The second time, the notes" | | 15 | "Blackbirds did not sing at" | | 16 | "The song came again, closer," | | 17 | "She kept moving toward the" | | 18 | "Eva had taken her there" | | 19 | "Something rustled in the undergrowth" |
| | ratio | 0.782 | |
| 49.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 101 | | matches | | 0 | "Now it stood close enough" |
| | ratio | 0.01 | |
| 81.63% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 3 | | matches | | 0 | "The temperature dropped not gradually but in a single step, as if she had walked from a warm room into a cellar." | | 1 | "The grass was still now, but the tips were bent as if something had been standing there a moment before." | | 2 | "The shadow stretched toward her across the grass, twitching, separating from the body that cast it." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |