| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 90.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1620 | | totalAiIsmAdverbs | 3 | | 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) | |
| 41.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1620 | | totalAiIsms | 19 | | found | | | highlights | | 0 | "gloom" | | 1 | "warmth" | | 2 | "scanned" | | 3 | "silence" | | 4 | "throbbed" | | 5 | "echoed" | | 6 | "scanning" | | 7 | "sentinels" | | 8 | "echo" | | 9 | "could feel" | | 10 | "pulsed" | | 11 | "whisper" | | 12 | "chill" |
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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 | 186 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 186 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 186 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1620 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 1 | | matches | | 0 | "Do not run, she told herself." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 1620 | | uniqueNames | 15 | | maxNameDensity | 0.49 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Grove" | | discoveredNames | | Carter | 1 | | Park | 1 | | Grove | 5 | | Heartstone | 1 | | Golden | 1 | | Empress | 1 | | Evan | 1 | | Cardiff | 1 | | London | 3 | | Determine | 1 | | November | 1 | | Earth | 1 | | Silas | 1 | | Fae | 1 | | Rory | 8 |
| | persons | | 0 | "Carter" | | 1 | "Empress" | | 2 | "Evan" | | 3 | "Silas" | | 4 | "Rory" |
| | places | | 0 | "Park" | | 1 | "Golden" | | 2 | "Cardiff" | | 3 | "London" | | 4 | "Earth" |
| | globalScore | 1 | | windowScore | 1 | |
| 66.67% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 120 | | glossingSentenceCount | 4 | | matches | | 0 | "sounded like dry leaves skittering over pa" | | 1 | "sounded like something dragging itself thr" | | 2 | "sounded like her name, but distorted, stre" | | 3 | "looked like nothing more than weathered w" |
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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 | 1620 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 186 | | matches | | |
| 90.47% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 49.09 | | std | 22.91 | | cv | 0.467 | | sampleLengths | | 0 | 61 | | 1 | 102 | | 2 | 65 | | 3 | 64 | | 4 | 68 | | 5 | 109 | | 6 | 7 | | 7 | 53 | | 8 | 19 | | 9 | 66 | | 10 | 53 | | 11 | 67 | | 12 | 47 | | 13 | 61 | | 14 | 4 | | 15 | 52 | | 16 | 67 | | 17 | 11 | | 18 | 53 | | 19 | 20 | | 20 | 51 | | 21 | 43 | | 22 | 48 | | 23 | 50 | | 24 | 50 | | 25 | 18 | | 26 | 43 | | 27 | 56 | | 28 | 40 | | 29 | 37 | | 30 | 51 | | 31 | 28 | | 32 | 56 |
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| 93.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 186 | | matches | | 0 | "was closed" | | 1 | "was gone" | | 2 | "were gone" | | 3 | "was filled" | | 4 | "was tethered" | | 5 | "were gone" |
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| 53.48% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 273 | | matches | | 0 | "was behaving" | | 1 | "was drawing" | | 2 | "was standing" | | 3 | "was shutting" | | 4 | "was digesting" | | 5 | "was waiting" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 186 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1624 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 58 | | adverbRatio | 0.03571428571428571 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.008620689655172414 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 186 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 186 | | mean | 8.71 | | std | 5.53 | | cv | 0.635 | | sampleLengths | | 0 | 13 | | 1 | 18 | | 2 | 9 | | 3 | 14 | | 4 | 7 | | 5 | 8 | | 6 | 13 | | 7 | 3 | | 8 | 21 | | 9 | 35 | | 10 | 22 | | 11 | 4 | | 12 | 13 | | 13 | 14 | | 14 | 4 | | 15 | 4 | | 16 | 26 | | 17 | 5 | | 18 | 10 | | 19 | 8 | | 20 | 6 | | 21 | 10 | | 22 | 13 | | 23 | 12 | | 24 | 5 | | 25 | 8 | | 26 | 3 | | 27 | 11 | | 28 | 20 | | 29 | 4 | | 30 | 8 | | 31 | 9 | | 32 | 9 | | 33 | 22 | | 34 | 5 | | 35 | 13 | | 36 | 4 | | 37 | 1 | | 38 | 6 | | 39 | 4 | | 40 | 8 | | 41 | 11 | | 42 | 15 | | 43 | 11 | | 44 | 7 | | 45 | 2 | | 46 | 12 | | 47 | 18 | | 48 | 12 | | 49 | 9 |
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| 30.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 37 | | diversityRatio | 0.24193548387096775 | | totalSentences | 186 | | uniqueOpeners | 45 | |
| 38.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 175 | | matches | | 0 | "Just the flowers and the" | | 1 | "Then the second." |
| | ratio | 0.011 | |
| 55.43% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 72 | | totalSentences | 175 | | matches | | 0 | "She paused, letting her eyes" | | 1 | "It did not obey much" | | 2 | "She touched the silver chain" | | 3 | "She had come because the" | | 4 | "They should be closed." | | 5 | "They should be sleeping." | | 6 | "She took a step forward." | | 7 | "Her boots sank into the" | | 8 | "They stretched toward her, long" | | 9 | "She was twenty-five years old," | | 10 | "She assessed the situation." | | 11 | "She lifted her left wrist" | | 12 | "She tapped the glass." | | 13 | "She looked up at the" | | 14 | "They were in the wrong" | | 15 | "Her body felt as though" | | 16 | "She turned slowly, her bright" | | 17 | "she called out." | | 18 | "Her voice sounded flat, absorbed" | | 19 | "It did not echo." |
| | ratio | 0.411 | |
| 57.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 141 | | totalSentences | 175 | | matches | | 0 | "The air inside the boundary" | | 1 | "Aurora Carter stepped between the" | | 2 | "She paused, letting her eyes" | | 3 | "Richmond Park was closed at" | | 4 | "It did not obey much" | | 5 | "She touched the silver chain" | | 6 | "The Heartstone pendant rested against" | | 7 | "Tonight it hummed." | | 8 | "A faint warmth radiated from" | | 9 | "She had come because the" | | 10 | "The benefactor who gave it" | | 11 | "Rory scanned the clearing." | | 12 | "Wildflowers bloomed in the darkness," | | 13 | "Bluebells and poppies opened wide" | | 14 | "They should be closed." | | 15 | "They should be sleeping." | | 16 | "The silence of the park" | | 17 | "She took a step forward." | | 18 | "Her boots sank into the" | | 19 | "That was the first wrong" |
| | ratio | 0.806 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 175 | | matches | | 0 | "If the time moved differently" | | 1 | "If she stayed too long," | | 2 | "If she slowed, it slowed." | | 3 | "If she sped up, it" |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 4 | | matches | | 0 | "A faint warmth radiated from the deep crimson gemstone, pulsing in a rhythm that matched the thud of her own heart." | | 1 | "She was twenty-five years old, not a frightened child, and she had a mind that solved problems for a living." | | 2 | "The moonlight caught the small crescent-shaped scar there, a pale ridge from a childhood fall that throbbed whenever the air pressure dropped." | | 3 | "She remembered the stories Silas told at the bar, half-drunk whispers about things that lived in the gaps of the city." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |