| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "Isolde smiled faintly [faintly]" |
| | dialogueSentences | 24 | | tagDensity | 0.458 | | leniency | 0.917 | | rawRatio | 0.182 | | effectiveRatio | 0.167 | |
| 90.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1009 | | 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) | |
| 70.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1009 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "reminder" | | 1 | "warmth" | | 2 | "pulsed" | | 3 | "could feel" | | 4 | "comforting" | | 5 | "silence" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 64 | | matches | (empty) | |
| 75.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 64 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | 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 | 0 | | markdownWords | 0 | | totalWords | 1009 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 73.08% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 845 | | uniqueNames | 7 | | maxNameDensity | 1.54 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | February | 1 | | Richmond | 1 | | Park | 1 | | Rory | 13 | | Isolde | 7 | | Heartstone | 1 | | Nyx | 5 |
| | persons | | | places | | | globalScore | 0.731 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 1.78% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.982 | | wordCount | 1009 | | matches | | 0 | "not warmer exactly, but it was softer" | | 1 | "Not the warmth of skin, but a deeper heat, like a coal banked under ash" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 77 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 32.55 | | std | 29.09 | | cv | 0.894 | | sampleLengths | | 0 | 69 | | 1 | 37 | | 2 | 15 | | 3 | 78 | | 4 | 12 | | 5 | 89 | | 6 | 9 | | 7 | 16 | | 8 | 45 | | 9 | 60 | | 10 | 5 | | 11 | 16 | | 12 | 78 | | 13 | 6 | | 14 | 36 | | 15 | 3 | | 16 | 24 | | 17 | 2 | | 18 | 19 | | 19 | 95 | | 20 | 54 | | 21 | 6 | | 22 | 14 | | 23 | 87 | | 24 | 23 | | 25 | 5 | | 26 | 4 | | 27 | 46 | | 28 | 34 | | 29 | 3 | | 30 | 19 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 64 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 135 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 77 | | ratio | 0 | | matches | (empty) | |
| 88.85% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 850 | | adjectiveStacks | 1 | | stackExamples | | 0 | "slender leaf-shaped dagger," |
| | adverbCount | 39 | | adverbRatio | 0.04588235294117647 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009411764705882352 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 13.1 | | std | 8.59 | | cv | 0.655 | | sampleLengths | | 0 | 18 | | 1 | 16 | | 2 | 21 | | 3 | 6 | | 4 | 8 | | 5 | 3 | | 6 | 26 | | 7 | 8 | | 8 | 7 | | 9 | 8 | | 10 | 10 | | 11 | 23 | | 12 | 3 | | 13 | 7 | | 14 | 35 | | 15 | 12 | | 16 | 7 | | 17 | 24 | | 18 | 30 | | 19 | 17 | | 20 | 11 | | 21 | 9 | | 22 | 16 | | 23 | 6 | | 24 | 20 | | 25 | 14 | | 26 | 5 | | 27 | 30 | | 28 | 7 | | 29 | 23 | | 30 | 5 | | 31 | 10 | | 32 | 6 | | 33 | 23 | | 34 | 12 | | 35 | 22 | | 36 | 15 | | 37 | 6 | | 38 | 2 | | 39 | 4 | | 40 | 29 | | 41 | 7 | | 42 | 3 | | 43 | 12 | | 44 | 12 | | 45 | 2 | | 46 | 19 | | 47 | 4 | | 48 | 20 | | 49 | 27 |
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| 75.32% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.4675324675324675 | | totalSentences | 77 | | uniqueOpeners | 36 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 57 | | matches | | 0 | "Then she noticed the flowers." | | 1 | "Then Nyx straightened and the" |
| | ratio | 0.035 | |
| 79.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 57 | | matches | | 0 | "It was February." | | 1 | "Her silver hair moved down" | | 2 | "She walked a pace ahead," | | 3 | "It never came." | | 4 | "It drifted like a breath" | | 5 | "Their eyes, faintly violet, were" | | 6 | "It was not warmer exactly," | | 7 | "They grew in drifts across" | | 8 | "she said quietly" | | 9 | "She rubbed it absently and" | | 10 | "It pulsed once, slow and" | | 11 | "She kept her eyes on" | | 12 | "Their trunks were pale and" | | 13 | "It held the reflection of" | | 14 | "They reached a second ring" | | 15 | "She had carried a blade" | | 16 | "It was always cold." | | 17 | "It came again, and the" | | 18 | "Her watch read a little" | | 19 | "She glanced at it and" |
| | ratio | 0.351 | |
| 47.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 57 | | matches | | 0 | "The standing stones rose out" | | 1 | "Rory counted them without meaning" | | 2 | "Each was rough-barked oak that" | | 3 | "Moss grew on the north" | | 4 | "Lichen spread in pale rings" | | 5 | "It was February." | | 6 | "Isolde said, without turning around" | | 7 | "Her silver hair moved down" | | 8 | "She walked a pace ahead," | | 9 | "It never came." | | 10 | "The ground took no print" | | 11 | "Rory glanced down at her" | | 12 | "Nyx murmured at her shoulder" | | 13 | "The voice came from nowhere" | | 14 | "It drifted like a breath" | | 15 | "Nyx had been a silhouette" | | 16 | "Their eyes, faintly violet, were" | | 17 | "It was not warmer exactly," | | 18 | "Rory breathed it in and" | | 19 | "They grew in drifts across" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 56.28% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 4 | | matches | | 0 | "Each was rough-barked oak that had been split and set upright, though no hand she could imagine had done the work." | | 1 | "Rory glanced down at her own boots, which had left dark crescents at every step, and then at the grass ahead, which sprang back straight behind Isolde as if nob…" | | 2 | "Their trunks were pale and smooth as bone, and their branches arched overhead to form a roof of gold-green leaves that filtered the light into slow-moving coins…" | | 3 | "Rory saw the shadow lean over the pool, and for an instant there was a second shape beneath the surface, a figure with its arms raised and its face turned upwar…" |
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| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | 0 | "Isolde said, without turning around" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 24 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0.1 | | effectiveRatio | 0.083 | |