| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.133 | | leniency | 0.267 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1506 | | 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) | |
| 76.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1506 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "warmth" | | 1 | "pulsed" | | 2 | "weight" |
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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 | 184 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 184 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 199 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1506 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 1456 | | uniqueNames | 9 | | maxNameDensity | 0.89 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Carter | 2 | | Golden | 1 | | Empress | 1 | | Aurora | 13 | | Cardiff | 1 | | Jennifer | 1 | | Rory | 1 |
| | persons | | 0 | "Carter" | | 1 | "Aurora" | | 2 | "Jennifer" | | 3 | "Rory" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Golden" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 107 | | glossingSentenceCount | 2 | | matches | | 0 | "as if listening to a song only it could hear" | | 1 | "seemed empty only ten feet away" |
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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 | 1506 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 199 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 114 | | mean | 13.21 | | std | 14.85 | | cv | 1.124 | | sampleLengths | | 0 | 50 | | 1 | 78 | | 2 | 10 | | 3 | 5 | | 4 | 10 | | 5 | 5 | | 6 | 47 | | 7 | 33 | | 8 | 9 | | 9 | 54 | | 10 | 24 | | 11 | 22 | | 12 | 20 | | 13 | 5 | | 14 | 2 | | 15 | 34 | | 16 | 4 | | 17 | 9 | | 18 | 35 | | 19 | 11 | | 20 | 16 | | 21 | 3 | | 22 | 29 | | 23 | 2 | | 24 | 34 | | 25 | 3 | | 26 | 6 | | 27 | 20 | | 28 | 12 | | 29 | 7 | | 30 | 3 | | 31 | 4 | | 32 | 1 | | 33 | 3 | | 34 | 3 | | 35 | 35 | | 36 | 12 | | 37 | 29 | | 38 | 4 | | 39 | 2 | | 40 | 35 | | 41 | 1 | | 42 | 31 | | 43 | 8 | | 44 | 39 | | 45 | 8 | | 46 | 9 | | 47 | 48 | | 48 | 6 | | 49 | 3 |
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| 99.54% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 184 | | matches | | 0 | "been shut" | | 1 | "been, braided" | | 2 | "been typed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 252 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 199 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 87 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.011494252873563218 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 199 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 199 | | mean | 7.57 | | std | 5.91 | | cv | 0.781 | | sampleLengths | | 0 | 10 | | 1 | 23 | | 2 | 14 | | 3 | 3 | | 4 | 13 | | 5 | 25 | | 6 | 8 | | 7 | 10 | | 8 | 4 | | 9 | 18 | | 10 | 10 | | 11 | 5 | | 12 | 5 | | 13 | 5 | | 14 | 5 | | 15 | 9 | | 16 | 13 | | 17 | 8 | | 18 | 17 | | 19 | 15 | | 20 | 4 | | 21 | 14 | | 22 | 4 | | 23 | 5 | | 24 | 3 | | 25 | 11 | | 26 | 7 | | 27 | 6 | | 28 | 27 | | 29 | 3 | | 30 | 5 | | 31 | 16 | | 32 | 7 | | 33 | 1 | | 34 | 7 | | 35 | 7 | | 36 | 13 | | 37 | 7 | | 38 | 5 | | 39 | 2 | | 40 | 8 | | 41 | 5 | | 42 | 21 | | 43 | 4 | | 44 | 9 | | 45 | 16 | | 46 | 9 | | 47 | 6 | | 48 | 4 | | 49 | 11 |
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| 30.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 38 | | diversityRatio | 0.27411167512690354 | | totalSentences | 197 | | uniqueOpeners | 54 | |
| 40.40% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 165 | | matches | | 0 | "Too long in the fingers." | | 1 | "Too loose at the knees." |
| | ratio | 0.012 | |
| 74.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 60 | | totalSentences | 165 | | matches | | 0 | "It was warm." | | 1 | "It had followed her through" | | 2 | "She had told herself she" | | 3 | "She had told herself she" | | 4 | "She had called it back." | | 5 | "Her battery icon sat at" | | 6 | "She pressed her thumb to" | | 7 | "She had learned early that" | | 8 | "Her boots struck the path," | | 9 | "She had entered the park" | | 10 | "She had been walking for" | | 11 | "She opened her voice recorder." | | 12 | "She stopped the recording and" | | 13 | "Her own voice came first." | | 14 | "She shut the phone." | | 15 | "Their bark had swallowed nails," | | 16 | "She stood at the boundary" | | 17 | "It folded once around the" | | 18 | "She looked at the phone." | | 19 | "You are alone." |
| | ratio | 0.364 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 143 | | totalSentences | 165 | | matches | | 0 | "The gate at Richmond Park" | | 1 | "Aurora Carter went through the" | | 2 | "The pendant at her throat" | | 3 | "It was warm." | | 4 | "The warmth had started at" | | 5 | "It had followed her through" | | 6 | "She had told herself she" | | 7 | "She had told herself she" | | 8 | "Those were both lies." | | 9 | "The stone at her neck" | | 10 | "The voicemail had come from" | | 11 | "She had called it back." | | 12 | "The line answered without ringing." | | 13 | "The map showed her walking" | | 14 | "The park paths smeared into" | | 15 | "Her battery icon sat at" | | 16 | "She pressed her thumb to" | | 17 | "She had learned early that" | | 18 | "Wildflowers broke through the frost." | | 19 | "The petals stood white and" |
| | ratio | 0.867 | |
| 30.30% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 165 | | matches | | 0 | "Now, under the first oaks," |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 2 | | matches | | 0 | "The scent reached her before the sound did, sweet, thick, with something beneath it that made her think of a basin emptied and refilled too many times." | | 1 | "After it, a small wet click, as if something had lifted itself from the microphone and returned it to the grass." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "It came, as if someone had copied Silas' voice from a recording and cut away the pauses" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |