| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 70.59% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 850 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "perfectly" | | 1 | "slowly" | | 2 | "very" |
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| 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) | |
| 76.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 850 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "rhythmic" | | 3 | "footsteps" |
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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 | 79 | | matches | (empty) | |
| 70.52% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 79 | | filterMatches | | | hedgeMatches | | 0 | "managed to" | | 1 | "began to" | | 2 | "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 | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 33 | | totalWords | 850 | | ratio | 0.039 | | matches | | 0 | "Follow the path past the bridge. Count seven oaks. Step through on the stroke of midnight, and bring nothing that was not given to you." | | 1 | "Near a Hel portal" | | 2 | "Deer" | | 3 | "Badgers. Someone's dog." |
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| 41.67% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 1 | | matches | | 0 | "*Deer*, she told herself." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 839 | | uniqueNames | 7 | | maxNameDensity | 0.6 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 5 | | Three | 2 | | Hel | 1 | | October | 1 | | Evan | 2 | | Eva | 1 | | Laila | 1 |
| | persons | | 0 | "Rory" | | 1 | "Three" | | 2 | "Evan" | | 3 | "Eva" | | 4 | "Laila" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 50 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a quarter hour, perhaps more" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 850 | | matches | (empty) | |
| 82.28% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 79 | | matches | | 0 | "learned that much" | | 1 | "been that night" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 20 | | mean | 42.5 | | std | 30.55 | | cv | 0.719 | | sampleLengths | | 0 | 78 | | 1 | 86 | | 2 | 17 | | 3 | 55 | | 4 | 82 | | 5 | 51 | | 6 | 2 | | 7 | 67 | | 8 | 7 | | 9 | 10 | | 10 | 72 | | 11 | 16 | | 12 | 8 | | 13 | 104 | | 14 | 18 | | 15 | 58 | | 16 | 17 | | 17 | 35 | | 18 | 22 | | 19 | 45 |
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| 87.50% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 79 | | matches | | 0 | "been locked" | | 1 | "been deleted" | | 2 | "been carved" | | 3 | "was gone" |
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| 95.83% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 128 | | matches | | 0 | "was wasting" | | 1 | "were knocking" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 79 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 95 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.031578947368421054 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 10.76 | | std | 9.16 | | cv | 0.851 | | sampleLengths | | 0 | 32 | | 1 | 10 | | 2 | 10 | | 3 | 19 | | 4 | 1 | | 5 | 2 | | 6 | 4 | | 7 | 23 | | 8 | 11 | | 9 | 3 | | 10 | 22 | | 11 | 27 | | 12 | 9 | | 13 | 8 | | 14 | 26 | | 15 | 2 | | 16 | 15 | | 17 | 12 | | 18 | 12 | | 19 | 31 | | 20 | 12 | | 21 | 27 | | 22 | 4 | | 23 | 1 | | 24 | 1 | | 25 | 17 | | 26 | 1 | | 27 | 1 | | 28 | 7 | | 29 | 19 | | 30 | 1 | | 31 | 1 | | 32 | 9 | | 33 | 1 | | 34 | 2 | | 35 | 1 | | 36 | 4 | | 37 | 17 | | 38 | 25 | | 39 | 3 | | 40 | 5 | | 41 | 4 | | 42 | 1 | | 43 | 2 | | 44 | 3 | | 45 | 7 | | 46 | 24 | | 47 | 18 | | 48 | 19 | | 49 | 3 |
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| 63.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.44871794871794873 | | totalSentences | 78 | | uniqueOpeners | 35 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 63 | | matches | | 0 | "Instead she had read it" | | 1 | "Then, as she walked, it" | | 2 | "Instead she let her eyes" |
| | ratio | 0.048 | |
| 48.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 63 | | matches | | 0 | "She stood still until her" | | 1 | "She had expected that." | | 2 | "It was small at first," | | 3 | "She pressed her thumb against" | | 4 | "She had looked it up" | | 5 | "She had felt it once" | | 6 | "She counted the oaks." | | 7 | "It didn't become colder so" | | 8 | "She stopped walking." | | 9 | "She started forward." | | 10 | "Its bark had been carved," | | 11 | "It was October." | | 12 | "It was cool and damp" | | 13 | "She did not turn her" | | 14 | "She had learned that much" | | 15 | "Their shadows fell in the" | | 16 | "It was gone when she" | | 17 | "It was there again, two" | | 18 | "Her watch had stopped." | | 19 | "She noticed that now, her" |
| | ratio | 0.429 | |
| 71.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 63 | | matches | | 0 | "The park gates had been" | | 1 | "Richmond at midnight smelled of" | | 2 | "The deer had gone quiet" | | 3 | "She stood still until her" | | 4 | "She had expected that." | | 5 | "The directions had come in" | | 6 | "It was small at first," | | 7 | "The crimson stone pulsed once," | | 8 | "She pressed her thumb against" | | 9 | "She had looked it up" | | 10 | "She had felt it once" | | 11 | "She counted the oaks." | | 12 | "The path curved, and the" | | 13 | "The air changed around the" | | 14 | "It didn't become colder so" | | 15 | "A sound came from her" | | 16 | "Rory turned her head." | | 17 | "The sound came again, closer" | | 18 | "She stopped walking." | | 19 | "The knocking stopped with her." |
| | ratio | 0.778 | |
| 79.37% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 63 | | matches | | 0 | "Now the silver chain lay" |
| | ratio | 0.016 | |
| 99.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 2 | | matches | | 0 | "She had looked it up at two in the morning, half-convinced she was wasting her time, and found only a scatter of folklore and a forum thread that had been delet…" | | 1 | "The sound came again, closer to the ground now, as if something small were knocking on a hollow log in time with her own footsteps." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |