| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.07% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1120 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 55.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1120 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "pulse" | | 1 | "sentinels" | | 2 | "silence" | | 3 | "weight" | | 4 | "echo" | | 5 | "pulsed" | | 6 | "comfortable" |
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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 | 74 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 74 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 76 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 50 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1120 | | ratio | 0 | | matches | (empty) | |
| 89.29% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 1 | | matches | | 0 | "A fox, she told herself." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1102 | | uniqueNames | 8 | | maxNameDensity | 0.82 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Aurora | 1 | | Richmond | 2 | | Park | 2 | | Yu-Fei | 1 | | Rory | 9 | | London | 1 | | Cardiff | 1 | | Evan | 2 |
| | persons | | 0 | "Aurora" | | 1 | "Yu-Fei" | | 2 | "Rory" | | 3 | "Evan" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | 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 | 1120 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 76 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 38.62 | | std | 30.82 | | cv | 0.798 | | sampleLengths | | 0 | 21 | | 1 | 30 | | 2 | 99 | | 3 | 4 | | 4 | 48 | | 5 | 2 | | 6 | 29 | | 7 | 87 | | 8 | 15 | | 9 | 102 | | 10 | 1 | | 11 | 45 | | 12 | 21 | | 13 | 57 | | 14 | 24 | | 15 | 63 | | 16 | 12 | | 17 | 42 | | 18 | 26 | | 19 | 71 | | 20 | 83 | | 21 | 10 | | 22 | 7 | | 23 | 76 | | 24 | 35 | | 25 | 5 | | 26 | 77 | | 27 | 11 | | 28 | 17 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 74 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 182 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 76 | | ratio | 0 | | matches | (empty) | |
| 86.21% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 269 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.055762081784386616 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.007434944237918215 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 76 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 76 | | mean | 14.74 | | std | 11.64 | | cv | 0.79 | | sampleLengths | | 0 | 21 | | 1 | 2 | | 2 | 28 | | 3 | 37 | | 4 | 22 | | 5 | 25 | | 6 | 1 | | 7 | 14 | | 8 | 4 | | 9 | 23 | | 10 | 25 | | 11 | 2 | | 12 | 3 | | 13 | 4 | | 14 | 22 | | 15 | 30 | | 16 | 34 | | 17 | 3 | | 18 | 6 | | 19 | 14 | | 20 | 8 | | 21 | 7 | | 22 | 50 | | 23 | 32 | | 24 | 2 | | 25 | 2 | | 26 | 16 | | 27 | 1 | | 28 | 4 | | 29 | 3 | | 30 | 21 | | 31 | 17 | | 32 | 21 | | 33 | 12 | | 34 | 1 | | 35 | 6 | | 36 | 14 | | 37 | 5 | | 38 | 19 | | 39 | 13 | | 40 | 11 | | 41 | 9 | | 42 | 18 | | 43 | 6 | | 44 | 30 | | 45 | 12 | | 46 | 19 | | 47 | 5 | | 48 | 18 | | 49 | 26 |
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| 60.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.4342105263157895 | | totalSentences | 76 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 64 | | matches | | 0 | "Obviously nobody answered her." | | 1 | "Just the black lattice of" | | 2 | "Instead it went out and" | | 3 | "Then, near the far stones," |
| | ratio | 0.063 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 64 | | matches | | 0 | "She closed her fist around" | | 1 | "She stepped through anyway." | | 2 | "She said it anyway, needed" | | 3 | "She'd come anyway." | | 4 | "Her voice didn't echo." | | 5 | "It should have." | | 6 | "She turned in a slow" | | 7 | "She hadn't expected them to" | | 8 | "She'd expected, if she was" | | 9 | "She spun the torch round." | | 10 | "she said, holding the pendant" | | 11 | "She thought about the two" | | 12 | "She took a step towards" | | 13 | "She fixed her eyes on" | | 14 | "She reached the gap in" |
| | ratio | 0.234 | |
| 92.81% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 64 | | matches | | 0 | "The pendant burned against Aurora's" | | 1 | "She closed her fist around" | | 2 | "The standing stones waited exactly" | | 3 | "Rory had walked past them" | | 4 | "She stepped through anyway." | | 5 | "The air changed the moment" | | 6 | "Rory's torch beam caught wildflowers," | | 7 | "Nobody answered her." | | 8 | "She said it anyway, needed" | | 9 | "The note Yu-Fei had tucked" | | 10 | "Rory had read it four" | | 11 | "She'd come anyway." | | 12 | "Evan had taught her that" | | 13 | "Curiosity killed people slower than" | | 14 | "The clearing opened up ahead," | | 15 | "The trees ringed it like" | | 16 | "Her voice didn't echo." | | 17 | "It should have." | | 18 | "A clearing that size, ringed" | | 19 | "The pendant pulsed again, warmer" |
| | ratio | 0.734 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 64 | | matches | (empty) | | ratio | 0 | |
| 91.84% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 3 | | matches | | 0 | "Rory had read it four times over her lukewarm chow mein and told herself it was a joke, some elaborate prank from the kitchen staff who thought her a soft touch…" | | 1 | "Every foxglove, every campion bell, folded shut like fists, the whole carpet of them curled tight as though a frost had swept through in the last thirty seconds…" | | 2 | "Rory stared down at them and felt the first cold thread of real fear work its way up her spine, the kind that didn't announce itself with a scream, just settled…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "The note Yu-Fei had (have)" |
| | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |