| 57.14% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 1 | | adverbTags | | 0 | "it called again [again]" |
| | dialogueSentences | 10 | | tagDensity | 0.7 | | leniency | 1 | | rawRatio | 0.143 | | effectiveRatio | 0.143 | |
| 89.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1860 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "very" | | 1 | "perfectly" | | 2 | "slowly" |
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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) | |
| 38.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1860 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "pulse" | | 1 | "warmth" | | 2 | "silence" | | 3 | "echo" | | 4 | "pulsed" | | 5 | "flickered" | | 6 | "lilt" | | 7 | "stomach" | | 8 | "footsteps" | | 9 | "measured" | | 10 | "shattered" | | 11 | "throb" | | 12 | "throbbed" |
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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 | 259 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 259 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 263 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1857 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 63.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1839 | | uniqueNames | 12 | | maxNameDensity | 1.74 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 3 | | Park | 3 | | January | 1 | | Heartstone | 3 | | Yu-Fei | 1 | | Hel | 1 | | London | 1 | | Welsh | 1 | | Rory | 32 | | Aurora | 1 | | Are | 1 | | Turn | 1 |
| | persons | | 0 | "Heartstone" | | 1 | "Rory" | | 2 | "Turn" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "January" | | 3 | "London" |
| | globalScore | 0.63 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 127 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like old trees arranged by acciden" | | 1 | "sounded like her mother" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.539 | | wordCount | 1857 | | matches | | 0 | "not physically, but with a subtle insistence" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 263 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 174 | | mean | 10.67 | | std | 10.99 | | cv | 1.03 | | sampleLengths | | 0 | 11 | | 1 | 41 | | 2 | 46 | | 3 | 9 | | 4 | 9 | | 5 | 2 | | 6 | 35 | | 7 | 1 | | 8 | 10 | | 9 | 12 | | 10 | 6 | | 11 | 7 | | 12 | 2 | | 13 | 15 | | 14 | 20 | | 15 | 4 | | 16 | 4 | | 17 | 11 | | 18 | 52 | | 19 | 4 | | 20 | 1 | | 21 | 1 | | 22 | 3 | | 23 | 63 | | 24 | 22 | | 25 | 27 | | 26 | 4 | | 27 | 10 | | 28 | 47 | | 29 | 2 | | 30 | 4 | | 31 | 30 | | 32 | 13 | | 33 | 6 | | 34 | 9 | | 35 | 6 | | 36 | 6 | | 37 | 5 | | 38 | 6 | | 39 | 26 | | 40 | 4 | | 41 | 5 | | 42 | 43 | | 43 | 40 | | 44 | 3 | | 45 | 12 | | 46 | 7 | | 47 | 6 | | 48 | 5 | | 49 | 10 |
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| 99.84% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 259 | | matches | | 0 | "been worn" | | 1 | "been given" | | 2 | "been frightened" | | 3 | "been gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 321 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 263 | | ratio | 0.008 | | matches | | 0 | "The pendant warmed in her hand and pulled—not physically, but with a subtle insistence—toward the pool." | | 1 | "The park waited beyond them—or something wearing the shape of the park." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 272 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.029411764705882353 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.007352941176470588 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 263 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 263 | | mean | 7.06 | | std | 5.31 | | cv | 0.753 | | sampleLengths | | 0 | 11 | | 1 | 24 | | 2 | 5 | | 3 | 4 | | 4 | 8 | | 5 | 19 | | 6 | 6 | | 7 | 21 | | 8 | 9 | | 9 | 9 | | 10 | 2 | | 11 | 19 | | 12 | 11 | | 13 | 5 | | 14 | 1 | | 15 | 5 | | 16 | 3 | | 17 | 2 | | 18 | 12 | | 19 | 6 | | 20 | 7 | | 21 | 2 | | 22 | 5 | | 23 | 10 | | 24 | 3 | | 25 | 4 | | 26 | 13 | | 27 | 4 | | 28 | 4 | | 29 | 4 | | 30 | 7 | | 31 | 7 | | 32 | 18 | | 33 | 18 | | 34 | 9 | | 35 | 4 | | 36 | 1 | | 37 | 1 | | 38 | 3 | | 39 | 14 | | 40 | 19 | | 41 | 30 | | 42 | 22 | | 43 | 5 | | 44 | 22 | | 45 | 4 | | 46 | 10 | | 47 | 25 | | 48 | 6 | | 49 | 11 |
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| 42.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.2480916030534351 | | totalSentences | 262 | | uniqueOpeners | 65 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 231 | | matches | | 0 | "Then, somewhere among the trees," | | 1 | "Then it had pulsed." | | 2 | "Then the pressure released." | | 3 | "Only a wall of dark" | | 4 | "Only stories, fragments, and the" | | 5 | "Then a voice said," | | 6 | "Just bare winter grass." | | 7 | "Then, from inside the grove," |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 65 | | totalSentences | 231 | | matches | | 0 | "She crossed the last stretch" | | 1 | "It silvered the tips of" | | 2 | "Her fingers closed around the" | | 3 | "Its silver chain had tangled" | | 4 | "She worked it free, listening." | | 5 | "She waited, counting to ten." | | 6 | "She lowered the phone." | | 7 | "Her voice fell flat." | | 8 | "She had come because of" | | 9 | "It had burned hot enough" | | 10 | "She had delivered takeaway orders" | | 11 | "She had told herself that" | | 12 | "It pressed against her ribs" | | 13 | "They rose from the grass" | | 14 | "She walked toward them." | | 15 | "Their heads turned toward her." | | 16 | "She stopped with one boot" | | 17 | "She put her foot down." | | 18 | "Her phone screen flickered." | | 19 | "They grew over stones and" |
| | ratio | 0.281 | |
| 74.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 178 | | totalSentences | 231 | | matches | | 0 | "Rory knew Richmond Park well" | | 1 | "The trees gathered close." | | 2 | "The paths seemed to choose" | | 3 | "She crossed the last stretch" | | 4 | "Mist lay low over the" | | 5 | "It silvered the tips of" | | 6 | "Her fingers closed around the" | | 7 | "The Heartstone answered with a" | | 8 | "The deep-crimson stone rested against" | | 9 | "Its silver chain had tangled" | | 10 | "She worked it free, listening." | | 11 | "Rory turned her phone toward" | | 12 | "The beam caught trunks, mist," | | 13 | "She waited, counting to ten." | | 14 | "The suggestion of one." | | 15 | "A darker interruption in the" | | 16 | "She lowered the phone." | | 17 | "Her voice fell flat." | | 18 | "The silence absorbed it without" | | 19 | "She had come because of" |
| | ratio | 0.771 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 231 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 3 | | matches | | 0 | "The deep-crimson stone rested against her palm, thumbnail-sized and smooth as if it had been worn there for centuries." | | 1 | "They grew over stones and roots, around a shallow pool at the clearing’s center, and along the narrow path that vanished between the trees opposite her." | | 2 | "Jennifer’s voice carried a warm Welsh lilt, a softness that could turn stern without warning." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "her mother whispered (whisper)" |
| | dialogueSentences | 10 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0.333 | | effectiveRatio | 0.333 | |