| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1835 | | 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) | |
| 53.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1835 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "pulse" | | 3 | "flicked" | | 4 | "warmth" | | 5 | "echoed" | | 6 | "throbbed" | | 7 | "vibrated" | | 8 | "footsteps" | | 9 | "measured" | | 10 | "footfall" | | 11 | "perfect" |
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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 | 229 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 229 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 242 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1835 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1795 | | uniqueNames | 12 | | maxNameDensity | 0.78 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | January | 1 | | Heartstone | 6 | | Golden | 1 | | Empress | 1 | | Tube | 1 | | London | 2 | | Aurora | 14 | | One | 3 | | Through | 3 | | Tick | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Aurora" | | 2 | "One" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "January" | | 3 | "Golden" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 121 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1835 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 242 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 109 | | mean | 16.83 | | std | 17.62 | | cv | 1.047 | | sampleLengths | | 0 | 20 | | 1 | 54 | | 2 | 4 | | 3 | 2 | | 4 | 72 | | 5 | 25 | | 6 | 36 | | 7 | 35 | | 8 | 9 | | 9 | 1 | | 10 | 10 | | 11 | 56 | | 12 | 73 | | 13 | 44 | | 14 | 46 | | 15 | 5 | | 16 | 13 | | 17 | 30 | | 18 | 6 | | 19 | 9 | | 20 | 5 | | 21 | 42 | | 22 | 8 | | 23 | 1 | | 24 | 8 | | 25 | 7 | | 26 | 29 | | 27 | 4 | | 28 | 42 | | 29 | 56 | | 30 | 5 | | 31 | 5 | | 32 | 9 | | 33 | 48 | | 34 | 56 | | 35 | 10 | | 36 | 6 | | 37 | 28 | | 38 | 5 | | 39 | 36 | | 40 | 5 | | 41 | 31 | | 42 | 7 | | 43 | 3 | | 44 | 8 | | 45 | 2 | | 46 | 44 | | 47 | 1 | | 48 | 1 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 229 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 286 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 242 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1798 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 46 | | adverbRatio | 0.025583982202447165 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0016685205784204673 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 242 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 242 | | mean | 7.58 | | std | 6.81 | | cv | 0.898 | | sampleLengths | | 0 | 20 | | 1 | 8 | | 2 | 5 | | 3 | 3 | | 4 | 6 | | 5 | 6 | | 6 | 5 | | 7 | 21 | | 8 | 4 | | 9 | 2 | | 10 | 20 | | 11 | 7 | | 12 | 16 | | 13 | 29 | | 14 | 14 | | 15 | 11 | | 16 | 15 | | 17 | 7 | | 18 | 2 | | 19 | 2 | | 20 | 1 | | 21 | 9 | | 22 | 12 | | 23 | 4 | | 24 | 2 | | 25 | 4 | | 26 | 13 | | 27 | 9 | | 28 | 1 | | 29 | 5 | | 30 | 5 | | 31 | 6 | | 32 | 21 | | 33 | 8 | | 34 | 10 | | 35 | 11 | | 36 | 19 | | 37 | 13 | | 38 | 7 | | 39 | 34 | | 40 | 44 | | 41 | 6 | | 42 | 15 | | 43 | 4 | | 44 | 21 | | 45 | 5 | | 46 | 4 | | 47 | 9 | | 48 | 10 | | 49 | 2 |
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| 53.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 24 | | diversityRatio | 0.38016528925619836 | | totalSentences | 242 | | uniqueOpeners | 92 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 172 | | matches | | 0 | "Then the warmth sharpened into" | | 1 | "Then brighter, until red slid" | | 2 | "Too smooth for a fox," | | 3 | "Then, just for a beat," | | 4 | "Then another, in sequence, all" | | 5 | "Then the movement curved behind" | | 6 | "Then the voice spoke from" |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 172 | | matches | | 0 | "It sat across her shoulders" | | 1 | "Their heads tilted as if" | | 2 | "She let out a short" | | 3 | "Her voice did not travel." | | 4 | "It dropped at her feet." | | 5 | "She turned the phone torch" | | 6 | "She had come because the" | | 7 | "She crouched near the nearest" | | 8 | "She ran her light across" | | 9 | "She felt them there, as" | | 10 | "She straightened at once and" | | 11 | "She hated that more than" | | 12 | "Her left hand found the" | | 13 | "She stepped deeper into the" | | 14 | "Their stems felt fleshy through" | | 15 | "Her torch beam shook over" | | 16 | "She crouched and held the" | | 17 | "She did not pull back." | | 18 | "She whipped the torch across." | | 19 | "It moved in a circle" |
| | ratio | 0.256 | |
| 87.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 128 | | totalSentences | 172 | | matches | | 0 | "Aurora reached the oak stones" | | 1 | "The path had fallen away" | | 2 | "London had gone with it." | | 3 | "The silence here had weight." | | 4 | "It sat across her shoulders" | | 5 | "Wildflowers covered the ground." | | 6 | "Their heads tilted as if" | | 7 | "The grass between them looked" | | 8 | "The standing stones ringed the" | | 9 | "The Heartstone pendant lay cold" | | 10 | "The moment she stepped over" | | 11 | "Heat spread through the thumbnail-sized" | | 12 | "A faint pulse pressed against" | | 13 | "Aurora took her phone from" | | 14 | "The time read 11:07." | | 15 | "She let out a short" | | 16 | "Her voice did not travel." | | 17 | "It dropped at her feet." | | 18 | "She turned the phone torch" | | 19 | "The beam cut a pale" |
| | ratio | 0.744 | |
| 29.07% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 172 | | matches | | 0 | "While she watched, the numbers" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 2 | | matches | | 0 | "The beam cut a pale lane through the flowers, and the clearing answered with colours that looked wrong in artificial light." | | 1 | "Yet the blooms nearest the bowl bent low, all at once, their petals turned inward as if bowing to heat." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 14 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 1 | | effectiveRatio | 0.143 | |