| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 39 | | tagDensity | 0.026 | | leniency | 0.051 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1224 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 79.58% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1224 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "pulsed" | | 1 | "stomach" | | 2 | "pulse" | | 3 | "warmth" |
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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 | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 149 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1224 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 25.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 961 | | uniqueNames | 8 | | maxNameDensity | 2.5 | | worstName | "Aurora" | | maxWindowNameDensity | 4 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Aurora | 24 | | Heartstone | 2 | | Fae-forged | 1 | | Grove | 1 | | Nyx | 12 | | Isolde | 8 |
| | persons | | 0 | "Aurora" | | 1 | "Grove" | | 2 | "Nyx" | | 3 | "Isolde" |
| | places | | | globalScore | 0.251 | | windowScore | 0.333 | |
| 75.37% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 67 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a city after rain: tires, gul" | | 1 | "looked like whipped cream" |
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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 | 1224 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 149 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 16 | | mean | 76.5 | | std | 46.94 | | cv | 0.614 | | sampleLengths | | 0 | 49 | | 1 | 29 | | 2 | 52 | | 3 | 47 | | 4 | 79 | | 5 | 50 | | 6 | 4 | | 7 | 117 | | 8 | 91 | | 9 | 53 | | 10 | 61 | | 11 | 105 | | 12 | 61 | | 13 | 136 | | 14 | 209 | | 15 | 81 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 164 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 149 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 964 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.025933609958506226 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 149 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 149 | | mean | 8.21 | | std | 5.43 | | cv | 0.661 | | sampleLengths | | 0 | 12 | | 1 | 13 | | 2 | 15 | | 3 | 9 | | 4 | 10 | | 5 | 3 | | 6 | 7 | | 7 | 1 | | 8 | 4 | | 9 | 4 | | 10 | 12 | | 11 | 12 | | 12 | 5 | | 13 | 18 | | 14 | 5 | | 15 | 4 | | 16 | 3 | | 17 | 19 | | 18 | 4 | | 19 | 5 | | 20 | 7 | | 21 | 5 | | 22 | 3 | | 23 | 8 | | 24 | 13 | | 25 | 8 | | 26 | 11 | | 27 | 13 | | 28 | 4 | | 29 | 4 | | 30 | 4 | | 31 | 11 | | 32 | 5 | | 33 | 13 | | 34 | 9 | | 35 | 17 | | 36 | 6 | | 37 | 4 | | 38 | 9 | | 39 | 13 | | 40 | 18 | | 41 | 5 | | 42 | 20 | | 43 | 6 | | 44 | 4 | | 45 | 5 | | 46 | 3 | | 47 | 10 | | 48 | 9 | | 49 | 5 |
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| 56.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3624161073825503 | | totalSentences | 149 | | uniqueOpeners | 54 | |
| 32.05% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 104 | | matches | | 0 | "Instead, a ring of black" |
| | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 104 | | matches | | 0 | "She looked at Aurora" | | 1 | "Her pale lavender eyes caught" | | 2 | "She pressed it to the" | | 3 | "Their bark was black, their" | | 4 | "Her reflection wore no flat." | | 5 | "She pulled her hand back." | | 6 | "They moved around the well." | | 7 | "He wore a clean apron" | | 8 | "His hands had too many" | | 9 | "It held a small glass" |
| | ratio | 0.096 | |
| 12.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 93 | | totalSentences | 104 | | matches | | 0 | "The last oak in Richmond" | | 1 | "Aurora paused before it, fingers" | | 2 | "Here the noise thinned to" | | 3 | "Nyx leaned against the trunk," | | 4 | "Aurora touched the pendant under" | | 5 | "Nyx tilted their head." | | 6 | "Isolde stood between the standing" | | 7 | "Wildflowers pressed close around her" | | 8 | "Isolde looked at the stones." | | 9 | "She looked at Aurora" | | 10 | "Aurora counted the stones." | | 11 | "The oldest one had split" | | 12 | "Aurora touched the split." | | 13 | "Nyx laughed, low and dry" | | 14 | "Isolde stepped aside." | | 15 | "Her pale lavender eyes caught" | | 16 | "Aurora pulled the Heartstone pendant" | | 17 | "The crimson stone pulsed against" | | 18 | "The chain went slack, then" | | 19 | "Aurora held the pendant." |
| | ratio | 0.894 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 104 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 1 | | matches | | 0 | "The mouths on the steps opened as they passed, releasing breaths that smelled of different meals: honey, burnt toast, salted lamb, wine gone sour." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |