| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1333 | | totalAiIsmAdverbs | 1 | | 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) | |
| 77.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1333 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "weight" | | 1 | "warmth" | | 2 | "grave" | | 3 | "silence" |
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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 | 105 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 105 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 4 | | totalWords | 1333 | | ratio | 0.003 | | matches | | 0 | "Grove's gone quiet. Come." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 1311 | | uniqueNames | 13 | | maxNameDensity | 0.38 | | worstName | "Isolde" | | maxWindowNameDensity | 1 | | worstWindowName | "Silas" | | discoveredNames | | Sheen | 1 | | Gate | 1 | | Park | 2 | | Silas | 2 | | Quiet | 1 | | Stupid | 1 | | Isolde | 5 | | Hel | 1 | | Richmond | 2 | | Japanese | 1 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 |
| | persons | | 0 | "Gate" | | 1 | "Silas" | | 2 | "Isolde" | | 3 | "Hel" | | 4 | "Yu-Fei" |
| | places | | 0 | "Sheen" | | 1 | "Park" | | 2 | "Richmond" | | 3 | "Japanese" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like a man dying of something drea" |
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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 | 1333 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 109 | | matches | | 0 | "did that thing" | | 1 | "carrying that scuff" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 45 | | mean | 29.62 | | std | 23.97 | | cv | 0.809 | | sampleLengths | | 0 | 26 | | 1 | 42 | | 2 | 47 | | 3 | 34 | | 4 | 99 | | 5 | 13 | | 6 | 52 | | 7 | 22 | | 8 | 12 | | 9 | 19 | | 10 | 3 | | 11 | 40 | | 12 | 7 | | 13 | 49 | | 14 | 12 | | 15 | 33 | | 16 | 66 | | 17 | 6 | | 18 | 44 | | 19 | 6 | | 20 | 83 | | 21 | 20 | | 22 | 38 | | 23 | 22 | | 24 | 5 | | 25 | 54 | | 26 | 27 | | 27 | 24 | | 28 | 66 | | 29 | 11 | | 30 | 70 | | 31 | 16 | | 32 | 9 | | 33 | 60 | | 34 | 6 | | 35 | 12 | | 36 | 38 | | 37 | 4 | | 38 | 63 | | 39 | 1 | | 40 | 19 | | 41 | 7 | | 42 | 7 | | 43 | 2 | | 44 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 105 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 210 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 109 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1312 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Cold, dry, ordinary bark," |
| | adverbCount | 44 | | adverbRatio | 0.03353658536585366 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.007621951219512195 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 12.23 | | std | 11.3 | | cv | 0.924 | | sampleLengths | | 0 | 26 | | 1 | 3 | | 2 | 18 | | 3 | 1 | | 4 | 2 | | 5 | 18 | | 6 | 11 | | 7 | 6 | | 8 | 29 | | 9 | 1 | | 10 | 8 | | 11 | 26 | | 12 | 30 | | 13 | 2 | | 14 | 20 | | 15 | 8 | | 16 | 22 | | 17 | 17 | | 18 | 13 | | 19 | 27 | | 20 | 25 | | 21 | 8 | | 22 | 14 | | 23 | 4 | | 24 | 5 | | 25 | 3 | | 26 | 19 | | 27 | 3 | | 28 | 34 | | 29 | 4 | | 30 | 2 | | 31 | 7 | | 32 | 9 | | 33 | 4 | | 34 | 4 | | 35 | 30 | | 36 | 2 | | 37 | 12 | | 38 | 3 | | 39 | 14 | | 40 | 5 | | 41 | 2 | | 42 | 9 | | 43 | 2 | | 44 | 2 | | 45 | 25 | | 46 | 37 | | 47 | 6 | | 48 | 9 | | 49 | 1 |
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| 70.34% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.47706422018348627 | | totalSentences | 109 | | uniqueOpeners | 52 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Then the wildflowers." | | 1 | "Then, from the treeline, a" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 82 | | matches | | 0 | "I landed badly." | | 1 | "I kept my torch off" | | 2 | "You could scream here for" | | 3 | "I put my palm on" | | 4 | "They were still there." | | 5 | "I stood at the boundary" | | 6 | "I said, and my voice" | | 7 | "I walked in." | | 8 | "It made no noise at" | | 9 | "I crouched by it and" | | 10 | "I pulled the chain out" | | 11 | "I didn't turn my head," | | 12 | "I let it stay in" | | 13 | "I counted to twenty." | | 14 | "It didn't move again." | | 15 | "I started a slow circuit" | | 16 | "They came out of the" | | 17 | "I stood over them for" | | 18 | "I said to the trees" | | 19 | "My mother's voice." |
| | ratio | 0.256 | |
| 88.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 82 | | matches | | 0 | "The railing at Sheen Gate" | | 1 | "I landed badly." | | 2 | "Richmond Park held six hundred" | | 3 | "The pendant lay flat against" | | 4 | "That was the point of" | | 5 | "Isolde had left a message" | | 6 | "I kept my torch off" | | 7 | "That's the trick of this" | | 8 | "London stays visible, a low" | | 9 | "You could scream here for" | | 10 | "The standing stones showed up" | | 11 | "I put my palm on" | | 12 | "The shimmer let me through" | | 13 | "The grove bloomed all year," | | 14 | "They were still there." | | 15 | "Every single one of them" | | 16 | "I stood at the boundary" | | 17 | "Flowers turn to light." | | 18 | "The moon sat behind the" | | 19 | "I said, and my voice" |
| | ratio | 0.744 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "The grove bloomed all year, that was its whole character, wild garlic and foxgloves and something violet that Isolde refused to name, all of them jumbled togeth…" | | 1 | "The crimson stone lay in my palm with its little inner glow, and while I watched it, the glow strengthened, faded, strengthened, faded, keeping a pace that had …" | | 2 | "The silence that came after it had weight, pressed against my eardrums like altitude, and in it I heard the softest sound of the whole night: grass, receiving a…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 8 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0 | | effectiveRatio | 0 | |