| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.483 | | leniency | 0.966 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1147 | | 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) | |
| 47.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1147 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "pulse" | | 1 | "trembled" | | 2 | "silk" | | 3 | "shimmered" | | 4 | "etching" | | 5 | "loomed" | | 6 | "pulsed" | | 7 | "stomach" | | 8 | "echoed" | | 9 | "glinting" | | 10 | "unraveling" |
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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 | 99 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1136 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 923 | | uniqueNames | 13 | | maxNameDensity | 1.95 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Heartstone | 2 | | Pendant | 1 | | Nyx | 10 | | Geiger-counter | 1 | | Fae | 5 | | Aurora | 18 | | Dymas | 1 | | Part | 1 | | Hel-bound | 1 | | Marsh | 1 | | Isolde | 5 | | Grove | 1 | | Rory | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Pendant" | | 2 | "Nyx" | | 3 | "Aurora" | | 4 | "Isolde" | | 5 | "Rory" |
| | places | | | globalScore | 0.525 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | glossingSentenceCount | 1 | | matches | | 0 | "as if offering a peace offering" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.88 | | wordCount | 1136 | | matches | | 0 | "not metaphorically, but physically, each half drifting back to reveal an indigo sky" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 33.41 | | std | 20.31 | | cv | 0.608 | | sampleLengths | | 0 | 89 | | 1 | 24 | | 2 | 25 | | 3 | 13 | | 4 | 48 | | 5 | 3 | | 6 | 76 | | 7 | 58 | | 8 | 51 | | 9 | 31 | | 10 | 14 | | 11 | 60 | | 12 | 40 | | 13 | 37 | | 14 | 20 | | 15 | 48 | | 16 | 47 | | 17 | 21 | | 18 | 37 | | 19 | 42 | | 20 | 5 | | 21 | 43 | | 22 | 6 | | 23 | 46 | | 24 | 23 | | 25 | 25 | | 26 | 27 | | 27 | 56 | | 28 | 12 | | 29 | 9 | | 30 | 38 | | 31 | 19 | | 32 | 36 | | 33 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 99 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 178 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 114 | | ratio | 0.079 | | matches | | 0 | "Rory’s breath fogged in the air, but her phone screen remained empty—no signal, no light, just a black canvas instead of the usual glow." | | 1 | "The standing stones—ancient oaks bent into jagged lines—groaned." | | 2 | "The wildflowers gave way—nearly—then sprang back, a muscle memory of growth." | | 3 | "Her phone lit up—6:30 PM." | | 4 | "The writing on the stone shimmered—letters leapt and reformed, never staying still long enough to read." | | 5 | "Stepped again, and they reversed—her boots dusted with yesterday’s pollen." | | 6 | "A tree’s trunk split apart—not metaphorically, but physically, each half drifting back to reveal an indigo sky." | | 7 | "Her footprints didn’t bloom under Rory’s scrutiny—she hadn’t left any." | | 8 | "A distant crash—something falling in the marsh, in the oak, in the sky." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 939 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.02875399361022364 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004259850905218318 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 9.96 | | std | 5.52 | | cv | 0.554 | | sampleLengths | | 0 | 10 | | 1 | 16 | | 2 | 19 | | 3 | 12 | | 4 | 8 | | 5 | 24 | | 6 | 4 | | 7 | 13 | | 8 | 7 | | 9 | 17 | | 10 | 8 | | 11 | 9 | | 12 | 2 | | 13 | 2 | | 14 | 8 | | 15 | 6 | | 16 | 11 | | 17 | 11 | | 18 | 12 | | 19 | 3 | | 20 | 3 | | 21 | 5 | | 22 | 12 | | 23 | 10 | | 24 | 6 | | 25 | 3 | | 26 | 6 | | 27 | 20 | | 28 | 11 | | 29 | 10 | | 30 | 3 | | 31 | 15 | | 32 | 12 | | 33 | 11 | | 34 | 7 | | 35 | 5 | | 36 | 19 | | 37 | 16 | | 38 | 11 | | 39 | 17 | | 40 | 14 | | 41 | 7 | | 42 | 7 | | 43 | 2 | | 44 | 10 | | 45 | 16 | | 46 | 19 | | 47 | 13 | | 48 | 11 | | 49 | 17 |
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| 63.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.39473684210526316 | | totalSentences | 114 | | uniqueOpeners | 45 | |
| 70.92% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 94 | | matches | | 0 | "Somewhere, a peal of laughter" | | 1 | "Somewhere, a stone creaked, preparing" |
| | ratio | 0.021 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 94 | | matches | | 0 | "Their voice slithered between her" | | 1 | "Their silhouette smeared into the" | | 2 | "Her phone lit up—6:30 PM." | | 3 | "she called, though she couldn’t" | | 4 | "She palmed it, the moonsilver" | | 5 | "Her boots crunched over gravel" | | 6 | "She wasn’t in Dymas, but" | | 7 | "Her reflection stared out, multiplied," | | 8 | "She recognized this smell." | | 9 | "Her scar prickled." | | 10 | "She pressed forward, the Fae" | | 11 | "Her footprints didn’t bloom under" | | 12 | "She knew better, but her" | | 13 | "She took a breath and" | | 14 | "They were preparing." |
| | ratio | 0.16 | |
| 18.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 94 | | matches | | 0 | "Aurora’s fingers tightened around the" | | 1 | "The Heartstone Pendant pressed against" | | 2 | "Nyx moved like smoke beside" | | 3 | "Wildflowers swayed in a breeze" | | 4 | "Rory’s breath fogged in the" | | 5 | "Their voice slithered between her" | | 6 | "Aurora muttered, watching moss peel" | | 7 | "The standing stones—ancient oaks bent" | | 8 | "The first of the wildflowers" | | 9 | "Nyx said, already sliding through" | | 10 | "Their silhouette smeared into the" | | 11 | "Aurora followed, feeling the air" | | 12 | "The wildflowers gave way—nearly—then sprang" | | 13 | "The sky above was a" | | 14 | "Nyx had vanished." | | 15 | "Aurora’s pocket buzzed." | | 16 | "Her phone lit up—6:30 PM." | | 17 | "The path, too." | | 18 | "Trees arched into colonnades of" | | 19 | "The air smelled of candied" |
| | ratio | 0.883 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 94 | | matches | | 0 | "Now, the Geiger-counter pulse of" | | 1 | "Before her, the forest reshaped" |
| | ratio | 0.021 | |
| 94.16% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 3 | | matches | | 0 | "The Heartstone Pendant pressed against her skin, a steady heat that had guided her this far." | | 1 | "Trees arched into colonnades of ivory and bark, their canopies scattering emerald light over glades that glowed like new currency." | | 2 | "She knew better, but her hand snaked forward as if offering a peace offering." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "Isolde tossed, its seeds glinting with molten gold" |
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| 46.55% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 3 | | fancyTags | | 0 | "Nyx murmured (murmur)" | | 1 | "Aurora muttered (mutter)" | | 2 | "She took (take)" |
| | dialogueSentences | 29 | | tagDensity | 0.276 | | leniency | 0.552 | | rawRatio | 0.375 | | effectiveRatio | 0.207 | |