| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 82.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 877 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "very" | | 2 | "softly" |
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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) | |
| 54.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 877 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "weight" | | 1 | "throb" | | 2 | "rhythmic" | | 3 | "measured" | | 4 | "pulsed" | | 5 | "warmth" | | 6 | "stomach" | | 7 | "could feel" |
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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) | |
| 65.64% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 74 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 75 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 7 | | totalWords | 877 | | ratio | 0.008 | | matches | | 0 | "Wildflowers bloom year-round," | | 1 | "Do not be startled." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 8 | | wordCount | 862 | | uniqueNames | 6 | | maxNameDensity | 0.35 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 3 | | Park | 1 | | Heartstone | 1 | | October | 1 | | Isolde | 1 | | Eva | 1 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 98.98% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | glossingSentenceCount | 1 | | matches | | 0 | "lines that seemed to shift when she stared at it, the way a word does when you repeat it too many times" |
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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 | 877 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 75 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 35.08 | | std | 23.96 | | cv | 0.683 | | sampleLengths | | 0 | 64 | | 1 | 62 | | 2 | 56 | | 3 | 26 | | 4 | 36 | | 5 | 13 | | 6 | 34 | | 7 | 40 | | 8 | 45 | | 9 | 26 | | 10 | 7 | | 11 | 85 | | 12 | 7 | | 13 | 52 | | 14 | 3 | | 15 | 26 | | 16 | 11 | | 17 | 15 | | 18 | 70 | | 19 | 76 | | 20 | 48 | | 21 | 45 | | 22 | 5 | | 23 | 17 | | 24 | 8 |
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| 72.07% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 74 | | matches | | 0 | "been left" | | 1 | "been told" | | 2 | "been told" | | 3 | "been startled" | | 4 | "was flattened" | | 5 | "been prepared" | | 6 | "been prepared" | | 7 | "been taken" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 133 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 75 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 865 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.03468208092485549 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.010404624277456647 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 75 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 75 | | mean | 11.69 | | std | 9.65 | | cv | 0.825 | | sampleLengths | | 0 | 19 | | 1 | 28 | | 2 | 17 | | 3 | 14 | | 4 | 8 | | 5 | 28 | | 6 | 12 | | 7 | 7 | | 8 | 24 | | 9 | 4 | | 10 | 21 | | 11 | 12 | | 12 | 14 | | 13 | 1 | | 14 | 1 | | 15 | 6 | | 16 | 4 | | 17 | 24 | | 18 | 9 | | 19 | 4 | | 20 | 5 | | 21 | 24 | | 22 | 5 | | 23 | 7 | | 24 | 9 | | 25 | 24 | | 26 | 7 | | 27 | 5 | | 28 | 21 | | 29 | 12 | | 30 | 5 | | 31 | 5 | | 32 | 7 | | 33 | 9 | | 34 | 7 | | 35 | 6 | | 36 | 13 | | 37 | 14 | | 38 | 20 | | 39 | 32 | | 40 | 7 | | 41 | 4 | | 42 | 1 | | 43 | 13 | | 44 | 7 | | 45 | 27 | | 46 | 1 | | 47 | 1 | | 48 | 1 | | 49 | 5 |
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| 64.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.4533333333333333 | | totalSentences | 75 | | uniqueOpeners | 34 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 65 | | matches | | 0 | "Then the starlight returned, thin" | | 1 | "Only her own breathing, and" | | 2 | "Then they were still again." |
| | ratio | 0.046 | |
| 47.69% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 65 | | matches | | 0 | "She stood there for a" | | 1 | "She had been told to" | | 2 | "She had been told not" | | 3 | "Its weight was reassuring." | | 4 | "It was late October." | | 5 | "She had not been startled." | | 6 | "She had been curious, and" | | 7 | "She clicked the torch off." | | 8 | "She had not noticed when" | | 9 | "She looked at the watch." | | 10 | "She had left the car" | | 11 | "It was not the sudden" | | 12 | "It was slow and deliberate," | | 13 | "She had felt it do" | | 14 | "She pressed her palm flat" | | 15 | "She turned her head." | | 16 | "She told herself she had" | | 17 | "She kept her eyes on" | | 18 | "Her voice came out smaller" | | 19 | "She turned slowly, scar-pale wrist" |
| | ratio | 0.431 | |
| 52.31% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 53 | | totalSentences | 65 | | matches | | 0 | "The gate in the park" | | 1 | "Richmond Park closed its gates" | | 2 | "She stood there for a" | | 3 | "The path ran straight for" | | 4 | "The bracken gave way to" | | 5 | "Oaks rose behind them, black" | | 6 | "She had been told to" | | 7 | "She had been told not" | | 8 | "Its weight was reassuring." | | 9 | "Rory stopped at the boundary" | | 10 | "The torch beam fell across" | | 11 | "A scatter of pale blue" | | 12 | "It was late October." | | 13 | "Every flower in that clearing" | | 14 | "*Wildflowers bloom year-round,* Isolde had" | | 15 | "She had not been startled." | | 16 | "She had been curious, and" | | 17 | "She clicked the torch off." | | 18 | "The dark came down like" | | 19 | "She had not noticed when" |
| | ratio | 0.815 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 1 | | matches | | 0 | "She pressed her palm flat over her sternum and kept walking toward the centre of the ring, where the grass was flattened and pale, as if something large had lai…" |
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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 | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |