| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1877 | | 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) | |
| 46.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1877 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "measured" | | 1 | "echo" | | 2 | "fluttered" | | 3 | "pulse" | | 4 | "throbbed" | | 5 | "warmth" | | 6 | "flickered" | | 7 | "vibrated" | | 8 | "whisper" | | 9 | "perfect" | | 10 | "pulsed" | | 11 | "familiar" | | 12 | "silence" | | 13 | "lilt" | | 14 | "could feel" | | 15 | "trembled" |
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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 | 235 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 235 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 249 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1876 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 70.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1820 | | uniqueNames | 13 | | maxNameDensity | 1.59 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 5 | | Fae | 1 | | Grove | 1 | | Richmond | 2 | | Park | 2 | | October | 1 | | Rory | 29 | | Come | 1 | | Hel | 1 | | Cardiff | 1 | | Nia | 2 | | Welsh | 1 | | One | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Rory" | | 2 | "Nia" |
| | places | | 0 | "Fae" | | 1 | "Grove" | | 2 | "Richmond" | | 3 | "Park" | | 4 | "October" | | 5 | "Cardiff" | | 6 | "One" |
| | globalScore | 0.703 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 146 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.533 | | wordCount | 1876 | | matches | | 0 | "Not the voice itself, but its shape: the high note rising, the little catch at the end" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 249 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 126 | | mean | 14.89 | | std | 14.58 | | cv | 0.98 | | sampleLengths | | 0 | 10 | | 1 | 6 | | 2 | 70 | | 3 | 22 | | 4 | 9 | | 5 | 6 | | 6 | 36 | | 7 | 8 | | 8 | 84 | | 9 | 12 | | 10 | 37 | | 11 | 6 | | 12 | 6 | | 13 | 2 | | 14 | 42 | | 15 | 1 | | 16 | 17 | | 17 | 3 | | 18 | 48 | | 19 | 8 | | 20 | 30 | | 21 | 4 | | 22 | 37 | | 23 | 4 | | 24 | 7 | | 25 | 2 | | 26 | 36 | | 27 | 5 | | 28 | 26 | | 29 | 5 | | 30 | 19 | | 31 | 5 | | 32 | 8 | | 33 | 4 | | 34 | 49 | | 35 | 7 | | 36 | 18 | | 37 | 2 | | 38 | 15 | | 39 | 6 | | 40 | 10 | | 41 | 32 | | 42 | 7 | | 43 | 3 | | 44 | 3 | | 45 | 20 | | 46 | 33 | | 47 | 6 | | 48 | 8 | | 49 | 32 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 235 | | matches | | 0 | "been scratched" | | 1 | "been looked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 283 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 249 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 185 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.02702702702702703 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 249 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 249 | | mean | 7.53 | | std | 4.98 | | cv | 0.66 | | sampleLengths | | 0 | 10 | | 1 | 6 | | 2 | 9 | | 3 | 10 | | 4 | 14 | | 5 | 11 | | 6 | 10 | | 7 | 16 | | 8 | 4 | | 9 | 2 | | 10 | 16 | | 11 | 3 | | 12 | 6 | | 13 | 6 | | 14 | 26 | | 15 | 2 | | 16 | 2 | | 17 | 6 | | 18 | 2 | | 19 | 3 | | 20 | 3 | | 21 | 8 | | 22 | 22 | | 23 | 4 | | 24 | 19 | | 25 | 31 | | 26 | 12 | | 27 | 5 | | 28 | 10 | | 29 | 22 | | 30 | 6 | | 31 | 2 | | 32 | 2 | | 33 | 2 | | 34 | 2 | | 35 | 11 | | 36 | 12 | | 37 | 19 | | 38 | 1 | | 39 | 11 | | 40 | 2 | | 41 | 4 | | 42 | 3 | | 43 | 12 | | 44 | 12 | | 45 | 12 | | 46 | 6 | | 47 | 6 | | 48 | 8 | | 49 | 2 |
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| 43.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.20080321285140562 | | totalSentences | 249 | | uniqueOpeners | 50 | |
| 93.90% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 213 | | matches | | 0 | "Just six words in careful" | | 1 | "Then came a child’s laugh." | | 2 | "Then it vanished." | | 3 | "Instead, it showed a call" | | 4 | "Then the call continued." | | 5 | "Only then did she glance" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 61 | | totalSentences | 213 | | matches | | 0 | "She stopped with one hand" | | 1 | "Its bark felt damp, though" | | 2 | "They had no business blooming" | | 3 | "They had no business blooming" | | 4 | "She had come for the" | | 5 | "She needed those names." | | 6 | "She wanted to know whether" | | 7 | "She pushed her phone into" | | 8 | "Their stems bent under each" | | 9 | "She could see the faint" | | 10 | "Her voice reached the far" | | 11 | "She kept walking." | | 12 | "She slid two fingers into" | | 13 | "She waited for her pulse" | | 14 | "Her fingers found metal." | | 15 | "It was long and black," | | 16 | "Its warmth had sharpened, no" | | 17 | "She drew the chain out" | | 18 | "It drifted from the trees" | | 19 | "She knew that voice." |
| | ratio | 0.286 | |
| 37.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 180 | | totalSentences | 213 | | matches | | 0 | "Rory crossed the line of" | | 1 | "The Heartstone warmed against her" | | 2 | "She stopped with one hand" | | 3 | "Its bark felt damp, though" | | 4 | "Wildflowers packed the clearing, their" | | 5 | "They had no business blooming" | | 6 | "They had no business blooming" | | 7 | "Rory checked her phone." | | 8 | "The screen showed 11:47, though" | | 9 | "She had come for the" | | 10 | "Isolde had left it tucked" | | 11 | "Rory had read it twice," | | 12 | "The key might open the" | | 13 | "She needed those names." | | 14 | "A man had followed her" | | 15 | "She wanted to know whether" | | 16 | "She pushed her phone into" | | 17 | "The flowers brushed her boots." | | 18 | "Their stems bent under each" | | 19 | "The clearing held no wind," |
| | ratio | 0.845 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 213 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 72 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 17 | | tagDensity | 0.176 | | leniency | 0.353 | | rawRatio | 0.333 | | effectiveRatio | 0.118 | |