| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.538 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.42% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1165 | | 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) | |
| 44.21% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1165 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "pulsed" | | 1 | "whisper" | | 2 | "gloom" | | 3 | "perfect" | | 4 | "pulse" | | 5 | "stomach" | | 6 | "weight" | | 7 | "throbbed" | | 8 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 133 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 133 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 151 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1165 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 25 | | unquotedAttributions | 0 | | matches | (empty) | |
| 36.73% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 927 | | uniqueNames | 14 | | maxNameDensity | 2.27 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Heartstone | 1 | | Pendant | 1 | | December | 1 | | Richmond | 1 | | Road | 1 | | Fae-Forged | 1 | | Blade | 1 | | Aurora | 21 | | Nyx | 13 | | Isolde | 15 | | Grove | 1 | | Veil | 2 | | Dymas | 1 | | Violet | 3 |
| | persons | | 0 | "Pendant" | | 1 | "Blade" | | 2 | "Aurora" | | 3 | "Nyx" | | 4 | "Isolde" | | 5 | "Veil" | | 6 | "Violet" |
| | places | | 0 | "December" | | 1 | "Richmond" | | 2 | "Road" | | 3 | "Grove" |
| | globalScore | 0.367 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | 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 | 1165 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 151 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 17.39 | | std | 12.39 | | cv | 0.713 | | sampleLengths | | 0 | 26 | | 1 | 28 | | 2 | 20 | | 3 | 30 | | 4 | 15 | | 5 | 34 | | 6 | 9 | | 7 | 8 | | 8 | 5 | | 9 | 34 | | 10 | 11 | | 11 | 75 | | 12 | 21 | | 13 | 4 | | 14 | 15 | | 15 | 27 | | 16 | 30 | | 17 | 11 | | 18 | 17 | | 19 | 12 | | 20 | 9 | | 21 | 35 | | 22 | 12 | | 23 | 5 | | 24 | 23 | | 25 | 19 | | 26 | 9 | | 27 | 4 | | 28 | 28 | | 29 | 12 | | 30 | 25 | | 31 | 6 | | 32 | 9 | | 33 | 49 | | 34 | 8 | | 35 | 8 | | 36 | 26 | | 37 | 6 | | 38 | 37 | | 39 | 18 | | 40 | 8 | | 41 | 17 | | 42 | 8 | | 43 | 29 | | 44 | 13 | | 45 | 23 | | 46 | 15 | | 47 | 13 | | 48 | 10 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 133 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 175 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 151 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 928 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.02693965517241379 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.00646551724137931 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 151 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 151 | | mean | 7.72 | | std | 4.79 | | cv | 0.621 | | sampleLengths | | 0 | 14 | | 1 | 8 | | 2 | 4 | | 3 | 19 | | 4 | 9 | | 5 | 5 | | 6 | 15 | | 7 | 5 | | 8 | 5 | | 9 | 20 | | 10 | 2 | | 11 | 7 | | 12 | 6 | | 13 | 18 | | 14 | 5 | | 15 | 11 | | 16 | 3 | | 17 | 6 | | 18 | 8 | | 19 | 2 | | 20 | 3 | | 21 | 2 | | 22 | 8 | | 23 | 8 | | 24 | 16 | | 25 | 2 | | 26 | 9 | | 27 | 7 | | 28 | 5 | | 29 | 17 | | 30 | 19 | | 31 | 7 | | 32 | 20 | | 33 | 5 | | 34 | 16 | | 35 | 2 | | 36 | 2 | | 37 | 15 | | 38 | 11 | | 39 | 5 | | 40 | 11 | | 41 | 12 | | 42 | 11 | | 43 | 7 | | 44 | 4 | | 45 | 7 | | 46 | 5 | | 47 | 12 | | 48 | 5 | | 49 | 7 |
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| 42.05% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.2980132450331126 | | totalSentences | 151 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 105 | | matches | | 0 | "It pulsed once, warm." | | 1 | "Her breath made a cloud" | | 2 | "It was not a clearing." | | 3 | "It was a bowl of" | | 4 | "Their trunks were silver bark," | | 5 | "They stood half in solid" | | 6 | "She drew the Fae-Forged Blade" | | 7 | "She left no prints on" | | 8 | "Her voice held no welcome," | | 9 | "Their silhouette rippled." | | 10 | "It pulsed, slow and tired." | | 11 | "They landed on the moss" | | 12 | "She took a step forward." | | 13 | "she said to Isolde" | | 14 | "It throbbed in time with" | | 15 | "Their faces broke the surface," | | 16 | "She lifted the blade." | | 17 | "It smelled of roasting meat" | | 18 | "It smelled of Dymas." | | 19 | "Her skin was cool." |
| | ratio | 0.2 | |
| 17.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 105 | | matches | | 0 | "Aurora pushed through the park" | | 1 | "The Heartstone Pendant hung heavy" | | 2 | "It pulsed once, warm." | | 3 | "Nyx waited by the oak" | | 4 | "Violet caught the last light" | | 5 | "The voice came from everywhere" | | 6 | "Aurora lifted her left wrist." | | 7 | "The crescent scar caught light." | | 8 | "Shadow pooled at their feet," | | 9 | "The air between the trees" | | 10 | "A ring of standing stones" | | 11 | "Moss grew in their cracks." | | 12 | "Wildflowers bloomed at their bases," | | 13 | "Aurora stepped closer." | | 14 | "The pendant warmed against her" | | 15 | "The world folded." | | 16 | "The air thickened, sweet with" | | 17 | "The sound of Richmond Road" | | 18 | "Her breath made a cloud" | | 19 | "The clearing opened in front" |
| | ratio | 0.886 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "Their trunks were silver bark, smooth as bone, and their leaves caught a light that was not the sun." | | 1 | "The chorus in the trees rose to a pitch that made Aurora's teeth ache." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 21 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.538 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |