| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1134 | | 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) | |
| 51.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1134 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "perfect" | | 1 | "warmth" | | 2 | "silence" | | 3 | "weight" | | 4 | "oppressive" | | 5 | "could feel" | | 6 | "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 | 126 | | matches | (empty) | |
| 86.17% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 5 | | narrationSentences | 126 | | filterMatches | (empty) | | hedgeMatches | | 0 | "seemed to" | | 1 | "tried to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 132 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 7 | | totalWords | 1134 | | ratio | 0.006 | | matches | | 0 | "Where are you? It's been six hours." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1082 | | uniqueNames | 19 | | maxNameDensity | 0.92 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 10 | | London | 2 | | Grove | 4 | | November | 2 | | Bloomsbury | 1 | | Muffled | 1 | | Hannah | 2 | | Marsh | 1 | | Richmond | 2 | | Park | 2 | | Precautions | 2 | | Eva | 1 | | Six | 1 | | Silas | 1 | | Laila | 2 | | Cardiff | 1 | | Dymas | 1 | | Hel | 1 | | Whitechapel | 1 |
| | persons | | 0 | "Rory" | | 1 | "Grove" | | 2 | "Hannah" | | 3 | "Eva" | | 4 | "Silas" | | 5 | "Laila" |
| | places | | 0 | "London" | | 1 | "Bloomsbury" | | 2 | "Marsh" | | 3 | "Richmond" | | 4 | "Park" | | 5 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 70.63% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 2 | | matches | | 0 | "shades that seemed to shift when she looked directly at them" | | 1 | "soil that seemed to go down forever" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.882 | | wordCount | 1134 | | matches | | 0 | "Not the absence of sound, but a presence" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 132 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 25.77 | | std | 17.92 | | cv | 0.695 | | sampleLengths | | 0 | 6 | | 1 | 36 | | 2 | 50 | | 3 | 31 | | 4 | 13 | | 5 | 58 | | 6 | 25 | | 7 | 7 | | 8 | 33 | | 9 | 7 | | 10 | 57 | | 11 | 9 | | 12 | 39 | | 13 | 27 | | 14 | 20 | | 15 | 29 | | 16 | 4 | | 17 | 55 | | 18 | 43 | | 19 | 7 | | 20 | 5 | | 21 | 2 | | 22 | 26 | | 23 | 3 | | 24 | 41 | | 25 | 27 | | 26 | 1 | | 27 | 17 | | 28 | 23 | | 29 | 36 | | 30 | 36 | | 31 | 4 | | 32 | 5 | | 33 | 43 | | 34 | 27 | | 35 | 4 | | 36 | 40 | | 37 | 68 | | 38 | 37 | | 39 | 44 | | 40 | 17 | | 41 | 16 | | 42 | 46 | | 43 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 126 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 173 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 132 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1087 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.03863845446182153 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.00827966881324747 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 132 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 132 | | mean | 8.59 | | std | 8.16 | | cv | 0.95 | | sampleLengths | | 0 | 6 | | 1 | 3 | | 2 | 12 | | 3 | 1 | | 4 | 2 | | 5 | 18 | | 6 | 16 | | 7 | 1 | | 8 | 1 | | 9 | 11 | | 10 | 21 | | 11 | 4 | | 12 | 2 | | 13 | 25 | | 14 | 7 | | 15 | 1 | | 16 | 5 | | 17 | 7 | | 18 | 13 | | 19 | 7 | | 20 | 31 | | 21 | 6 | | 22 | 1 | | 23 | 1 | | 24 | 17 | | 25 | 7 | | 26 | 2 | | 27 | 1 | | 28 | 21 | | 29 | 3 | | 30 | 1 | | 31 | 2 | | 32 | 3 | | 33 | 7 | | 34 | 33 | | 35 | 7 | | 36 | 17 | | 37 | 9 | | 38 | 10 | | 39 | 5 | | 40 | 2 | | 41 | 22 | | 42 | 3 | | 43 | 2 | | 44 | 2 | | 45 | 20 | | 46 | 3 | | 47 | 6 | | 48 | 7 | | 49 | 4 |
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| 58.59% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.4015151515151515 | | totalSentences | 132 | | uniqueOpeners | 53 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 97 | | matches | | 0 | "Just the oaks with their" | | 1 | "Then twelve again." | | 2 | "Just a slow, deliberate ripple" |
| | ratio | 0.031 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 97 | | matches | | 0 | "She stopped walking." | | 1 | "Her hand rose to the" | | 2 | "Her voice sounded wrong here" | | 3 | "She'd come because of the" | | 4 | "She counted them." | | 5 | "She said it to herself," | | 6 | "She didn't pull it out." | | 7 | "Her phone buzzed." | | 8 | "It's been six hours.*" | | 9 | "She'd entered the Grove maybe" | | 10 | "She stepped forward, testing the" | | 11 | "Her breath didn't fog, though." | | 12 | "It was the kind of" | | 13 | "She didn't see them move." | | 14 | "She kept her eyes forward." | | 15 | "It wasn't her name, wasn't" | | 16 | "She looked down." | | 17 | "She could feel it." | | 18 | "She steadied it." | | 19 | "She kept her eyes forward" |
| | ratio | 0.206 | |
| 88.87% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 97 | | matches | | 0 | "The pendant burned against Rory's" | | 1 | "She stopped walking." | | 2 | "Her hand rose to the" | | 3 | "The same heat she'd felt" | | 4 | "The Grove stretched ahead, a" | | 5 | "Foxgloves with their poisonous throats" | | 6 | "The ancient oaks formed a" | | 7 | "Rory checked her phone." | | 8 | "The screen showed 11:47 PM," | | 9 | "Her voice sounded wrong here" | | 10 | "She'd come because of the" | | 11 | "The police had searched the" | | 12 | "Rory had found Hannah's scarf" | | 13 | "The wildflowers crunched under her" | | 14 | "The sound was wrong for" | | 15 | "A branch snapped somewhere to" | | 16 | "She counted them." | | 17 | "The pendant's warmth spread up" | | 18 | "She said it to herself," | | 19 | "Precautions her father would have" |
| | ratio | 0.742 | |
| 51.55% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 97 | | matches | | 0 | "Now it barely accommodated her" |
| | ratio | 0.01 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 7 | | matches | | 0 | "The same heat she'd felt twice before, both times near things that shouldn't exist in London's tidy geography." | | 1 | "The Grove stretched ahead, a perfect circle of wildflowers that had no business blooming in November." | | 2 | "Precautions that had kept her alive through three encounters with things that defied his tidy legal logic." | | 3 | "The wildflowers continued their impossible bloom, petals in colours that didn't have names, shades that seemed to shift when she looked directly at them." | | 4 | "A bluebell turned from violet to something closer to bruise-purple to a colour that existed only in the space between seeing and understanding." | | 5 | "The pendant that had appeared on her pillow six months ago with no note, no explanation, no return address." | | 6 | "The wildflowers parted, stems bending away from a point directly in front of her, revealing dark soil that seemed to go down forever." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0 | | effectiveRatio | 0 | |