| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said softly [softly]" | | 1 | "the voice called again [again]" |
| | dialogueSentences | 16 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0.4 | | effectiveRatio | 0.25 | |
| 88.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2260 | | totalAiIsmAdverbs | 5 | | found | | 0 | | | 1 | | | 2 | | | 3 | | adverb | "deliberately" | | count | 1 |
| | 4 | |
| | highlights | | 0 | "perfectly" | | 1 | "softly" | | 2 | "slowly" | | 3 | "deliberately" | | 4 | "slightly" |
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| 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) | |
| 66.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2260 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "weight" | | 1 | "warmth" | | 2 | "pulse" | | 3 | "mechanical" | | 4 | "resolve" | | 5 | "silence" | | 6 | "pulsed" | | 7 | "vibrated" | | 8 | "echo" | | 9 | "calculating" | | 10 | "could feel" |
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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 | 1 | | narrationSentences | 308 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 308 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 318 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2260 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 2217 | | uniqueNames | 13 | | maxNameDensity | 0.77 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Heartstone | 1 | | Hel | 1 | | Golden | 2 | | Empress | 2 | | Yu-Fei | 3 | | London | 1 | | Rory | 17 | | Evan | 1 | | Eva | 1 | | Seven | 3 | | You | 4 |
| | persons | | 0 | "Heartstone" | | 1 | "Empress" | | 2 | "Yu-Fei" | | 3 | "Rory" | | 4 | "Evan" | | 5 | "Eva" | | 6 | "You" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Golden" | | 3 | "London" |
| | globalScore | 1 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 160 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared ahead pale columns under ancient oaks" | | 1 | "seemed loud" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.442 | | wordCount | 2260 | | matches | | 0 | "not to sound afraid, but the breath behind them lasted too long" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 318 | | matches | | 0 | "take that photograph" | | 1 | "want that back" | | 2 | "was that panic" | | 3 | "knew that tone" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 199 | | mean | 11.36 | | std | 10.45 | | cv | 0.92 | | sampleLengths | | 0 | 7 | | 1 | 38 | | 2 | 21 | | 3 | 1 | | 4 | 6 | | 5 | 18 | | 6 | 20 | | 7 | 14 | | 8 | 21 | | 9 | 39 | | 10 | 24 | | 11 | 4 | | 12 | 8 | | 13 | 3 | | 14 | 62 | | 15 | 3 | | 16 | 9 | | 17 | 39 | | 18 | 21 | | 19 | 12 | | 20 | 37 | | 21 | 3 | | 22 | 5 | | 23 | 2 | | 24 | 29 | | 25 | 3 | | 26 | 1 | | 27 | 18 | | 28 | 33 | | 29 | 4 | | 30 | 1 | | 31 | 2 | | 32 | 6 | | 33 | 19 | | 34 | 9 | | 35 | 26 | | 36 | 7 | | 37 | 10 | | 38 | 4 | | 39 | 12 | | 40 | 15 | | 41 | 4 | | 42 | 5 | | 43 | 19 | | 44 | 9 | | 45 | 11 | | 46 | 3 | | 47 | 12 | | 48 | 2 | | 49 | 4 |
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| 97.29% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 308 | | matches | | 0 | "been seven" | | 1 | "been distracted" | | 2 | "was gone" | | 3 | "been found" | | 4 | "being drawn" | | 5 | "was lodged" | | 6 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 389 | | matches | | 0 | "was happening" | | 1 | "was wearing" | | 2 | "was trying" | | 3 | "was doing" | | 4 | "was dragging" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 318 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2221 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small white light rose" |
| | adverbCount | 74 | | adverbRatio | 0.033318325078793336 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.00765420981539847 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 318 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 318 | | mean | 7.11 | | std | 5.08 | | cv | 0.715 | | sampleLengths | | 0 | 7 | | 1 | 8 | | 2 | 6 | | 3 | 24 | | 4 | 10 | | 5 | 5 | | 6 | 6 | | 7 | 1 | | 8 | 3 | | 9 | 3 | | 10 | 5 | | 11 | 1 | | 12 | 12 | | 13 | 16 | | 14 | 2 | | 15 | 2 | | 16 | 14 | | 17 | 4 | | 18 | 1 | | 19 | 16 | | 20 | 6 | | 21 | 10 | | 22 | 23 | | 23 | 19 | | 24 | 5 | | 25 | 4 | | 26 | 8 | | 27 | 3 | | 28 | 14 | | 29 | 25 | | 30 | 5 | | 31 | 18 | | 32 | 3 | | 33 | 9 | | 34 | 3 | | 35 | 5 | | 36 | 16 | | 37 | 3 | | 38 | 12 | | 39 | 9 | | 40 | 2 | | 41 | 10 | | 42 | 12 | | 43 | 10 | | 44 | 15 | | 45 | 12 | | 46 | 3 | | 47 | 5 | | 48 | 2 | | 49 | 6 |
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| 45.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.2807570977917981 | | totalSentences | 317 | | uniqueOpeners | 89 | |
| 89.06% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 262 | | matches | | 0 | "Then she swept the torch" | | 1 | "Even the small movements of" | | 2 | "Somewhere to her left, someone" | | 3 | "Then, in her own voice:" | | 4 | "Of course she would." | | 5 | "Then she saw the wedge." | | 6 | "Then headlights moved beyond the" |
| | ratio | 0.027 | |
| 71.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 97 | | totalSentences | 262 | | matches | | 0 | "She had expected to climb" | | 1 | "She had brought gloves for" | | 2 | "She turned to check the" | | 3 | "It was late." | | 4 | "She took out her phone." | | 5 | "She could see the loose" | | 6 | "She checked the little torch" | | 7 | "Her voice went no farther" | | 8 | "She walked in." | | 9 | "She followed it." | | 10 | "She knew it happened here." | | 11 | "She had left a note" | | 12 | "Her torch picked out grooves" | | 13 | "She counted six." | | 14 | "Her memory was not a" | | 15 | "She had visited in daylight," | | 16 | "She counted again." | | 17 | "She had shifted her weight," | | 18 | "They bloomed here whatever the" | | 19 | "She crossed between the nearest" |
| | ratio | 0.37 | |
| 80.23% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 199 | | totalSentences | 262 | | matches | | 0 | "The gate into Richmond Park" | | 1 | "Rory stopped with her hand" | | 2 | "She had expected to climb" | | 3 | "She had brought gloves for" | | 4 | "She turned to check the" | | 5 | "It was late." | | 6 | "She took out her phone." | | 7 | "The message was still there," | | 8 | "She could see the loose" | | 9 | "That was why she had" | | 10 | "Someone had been close enough" | | 11 | "She checked the little torch" | | 12 | "Yu-Fei would want that back." | | 13 | "Her voice went no farther" | | 14 | "She walked in." | | 15 | "The path to the grove" | | 16 | "Tonight the turn was obvious." | | 17 | "The bracken lay flat, its" | | 18 | "She followed it." | | 19 | "That happened here." |
| | ratio | 0.76 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 6 | | totalSentences | 262 | | matches | | 0 | "If you want to know" | | 1 | "If I’m not back by" | | 2 | "Now she wished she had" | | 3 | "Whoever had sent the message" | | 4 | "Whoever had taken the photograph" | | 5 | "Before she could call, a" |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 78 | | technicalSentenceCount | 1 | | matches | | 0 | "The bracken lay flat, its stems pressed into the mud as though something broad had dragged itself through." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.313 | | leniency | 0.625 | | rawRatio | 0 | | effectiveRatio | 0 | |