| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "Rory said again [again]" |
| | dialogueSentences | 14 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 87.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1211 | | 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) | |
| 83.48% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1211 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "throb" | | 1 | "throbbed" | | 2 | "weight" | | 3 | "rhythmic" |
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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 | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1218 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 1145 | | uniqueNames | 7 | | maxNameDensity | 0.52 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Sheen | 1 | | Cross | 1 | | Rory | 6 | | Richmond | 1 | | Park | 1 | | November | 1 | | Six | 3 |
| | persons | | | places | | 0 | "Sheen" | | 1 | "Cross" | | 2 | "Richmond" | | 3 | "Park" | | 4 | "November" |
| | globalScore | 1 | | windowScore | 1 | |
| 62.28% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a man holding his coat open" | | 1 | "She'd said obviously to a wood, and the" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.821 | | wordCount | 1218 | | matches | | 0 | "not her steps, but four minutes was wrong by half" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 29 | | std | 25.93 | | cv | 0.894 | | sampleLengths | | 0 | 40 | | 1 | 9 | | 2 | 10 | | 3 | 69 | | 4 | 7 | | 5 | 72 | | 6 | 18 | | 7 | 8 | | 8 | 3 | | 9 | 66 | | 10 | 7 | | 11 | 76 | | 12 | 32 | | 13 | 37 | | 14 | 12 | | 15 | 22 | | 16 | 83 | | 17 | 42 | | 18 | 3 | | 19 | 10 | | 20 | 80 | | 21 | 2 | | 22 | 8 | | 23 | 23 | | 24 | 63 | | 25 | 33 | | 26 | 6 | | 27 | 43 | | 28 | 19 | | 29 | 27 | | 30 | 1 | | 31 | 21 | | 32 | 89 | | 33 | 5 | | 34 | 25 | | 35 | 7 | | 36 | 2 | | 37 | 47 | | 38 | 2 | | 39 | 25 | | 40 | 17 | | 41 | 47 |
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| 90.01% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 92 | | matches | | 0 | "was locked" | | 1 | "been told" | | 2 | "were lit" | | 3 | "been kept" |
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| 94.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 189 | | matches | | 0 | "was listening" | | 1 | "wasn't hiding" | | 2 | "was matching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 99 | | ratio | 0.061 | | matches | | 0 | "She'd walked this route in daylight twice, memorising it the way she used to memorise case citations — landmarks instead of paragraph numbers." | | 1 | "Not faded — went out, all of it at once, traffic and insects and the wet suck of her own boots, as if someone had put a thumb over the world's ear." | | 2 | "The stones came up out of the ground the way a shipwreck comes up out of fog — nothing, nothing, then the shape of something enormous that had been there the whole time." | | 3 | "The air changed the way it changes when you walk into a church — pressure, not temperature, a weight arriving on the eardrums." | | 4 | "That was the pattern, she realised — that was the whole shape of the night." | | 5 | "She turned to face the gap she'd come in through, and put one foot toward it, and behind her — close, close enough that she felt the air move against the fine hairs on her neck — something drew a breath through its teeth and held it." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1138 | | adjectiveStacks | 2 | | stackExamples | | 0 | "lay warm against her" | | 1 | "small, wet, rhythmic noise." |
| | adverbCount | 42 | | adverbRatio | 0.03690685413005272 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007908611599297012 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 12.3 | | std | 11.96 | | cv | 0.972 | | sampleLengths | | 0 | 40 | | 1 | 6 | | 2 | 3 | | 3 | 4 | | 4 | 3 | | 5 | 3 | | 6 | 23 | | 7 | 6 | | 8 | 12 | | 9 | 10 | | 10 | 11 | | 11 | 7 | | 12 | 7 | | 13 | 27 | | 14 | 2 | | 15 | 43 | | 16 | 7 | | 17 | 2 | | 18 | 9 | | 19 | 3 | | 20 | 5 | | 21 | 3 | | 22 | 6 | | 23 | 3 | | 24 | 41 | | 25 | 4 | | 26 | 12 | | 27 | 7 | | 28 | 9 | | 29 | 32 | | 30 | 21 | | 31 | 4 | | 32 | 10 | | 33 | 5 | | 34 | 27 | | 35 | 23 | | 36 | 14 | | 37 | 8 | | 38 | 4 | | 39 | 22 | | 40 | 33 | | 41 | 31 | | 42 | 19 | | 43 | 6 | | 44 | 36 | | 45 | 3 | | 46 | 10 | | 47 | 7 | | 48 | 23 | | 49 | 8 |
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| 63.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.43434343434343436 | | totalSentences | 99 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 74 | | matches | | 0 | "Just warm, like a coin" | | 1 | "Then it came back, and" | | 2 | "Just black, and the shape" | | 3 | "Then, off to the right," |
| | ratio | 0.054 | |
| 84.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 74 | | matches | | 0 | "she told the dark" | | 1 | "She'd walked this route in" | | 2 | "She'd counted her breaths, not" | | 3 | "She went on." | | 4 | "She'd expected that." | | 5 | "It was the gaps that" | | 6 | "She counted the gaps." | | 7 | "It stood with its trunk" | | 8 | "she said, out loud, because" | | 9 | "She put her palm flat" | | 10 | "She pressed it down through" | | 11 | "She stepped between two of" | | 12 | "They were lit." | | 13 | "She stood very still and" | | 14 | "Her voice came out thin" | | 15 | "She'd said obviously to a" | | 16 | "She crouched by the pool." | | 17 | "She didn't turn." | | 18 | "It went between two of" | | 19 | "It stopped as soon as" |
| | ratio | 0.338 | |
| 61.35% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 74 | | matches | | 0 | "The gate at Sheen Cross" | | 1 | "she told the dark" | | 2 | "The dark didn't answer." | | 3 | "That was fine." | | 4 | "That was normal." | | 5 | "She'd walked this route in" | | 6 | "The bench with the bronze" | | 7 | "The split beech that looked" | | 8 | "The bracken slope where the" | | 9 | "Tonight the bench came up" | | 10 | "Rory stopped with her hand" | | 11 | "She'd counted her breaths, not" | | 12 | "The pendant lay warm against" | | 13 | "She went on." | | 14 | "The park at night wasn't" | | 15 | "She'd expected that." | | 16 | "Traffic hummed somewhere off to" | | 17 | "It was the gaps that" | | 18 | "Every forty seconds or so," | | 19 | "She counted the gaps." |
| | ratio | 0.797 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 61.22% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 4 | | matches | | 0 | "She'd counted her breaths, not her steps, but four minutes was wrong by half, and the grass under her boots had gone from long and wet to cropped short, the way…" | | 1 | "Not faded — went out, all of it at once, traffic and insects and the wet suck of her own boots, as if someone had put a thumb over the world's ear." | | 2 | "That was the thing she couldn't argue away, standing there with wet socks and her hands going numb: the grove was listening." | | 3 | "She counted them a third time, going clockwise from the gap she'd entered by, touching each with her eyes and her lips moving." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "Rory whispered (whisper)" |
| | dialogueSentences | 14 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |