| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.16% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 594 | | totalAiIsmAdverbs | 2 | | found | | 0 | | adverb | "reluctantly" | | count | 1 |
| | 1 | |
| | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 594 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | word | "down her spine" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "pulsed" | | 1 | "otherworldly" | | 2 | "down her spine" | | 3 | "etched" | | 4 | "whisper" | | 5 | "footsteps" | | 6 | "weight" | | 7 | "pounding" | | 8 | "determined" | | 9 | "dancing" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blink of an eye" | | count | 1 |
|
| | highlights | | 0 | "in the blink of an eye" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 55 | | matches | (empty) | |
| 90.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 55 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 59 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 591 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.39% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 559 | | uniqueNames | 6 | | maxNameDensity | 1.25 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Heartstone | 1 | | Aurora | 7 | | Fae | 2 | | Grove | 2 | | Richmond | 1 | | Park | 1 |
| | persons | | | places | | 0 | "Fae" | | 1 | "Grove" | | 2 | "Richmond" | | 3 | "Park" |
| | globalScore | 0.874 | | windowScore | 1 | |
| 21.79% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 39 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like a soft giggle" | | 1 | "blossoms that seemed to drink in the darkness" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 591 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 59 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 18 | | mean | 32.83 | | std | 16.69 | | cv | 0.508 | | sampleLengths | | 0 | 56 | | 1 | 63 | | 2 | 48 | | 3 | 41 | | 4 | 14 | | 5 | 40 | | 6 | 29 | | 7 | 19 | | 8 | 38 | | 9 | 44 | | 10 | 29 | | 11 | 30 | | 12 | 1 | | 13 | 38 | | 14 | 20 | | 15 | 53 | | 16 | 23 | | 17 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 55 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 99 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 59 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 562 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Many natural, normal creatures." |
| | adverbCount | 20 | | adverbRatio | 0.03558718861209965 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.017793594306049824 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 59 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 59 | | mean | 10.02 | | std | 7.48 | | cv | 0.746 | | sampleLengths | | 0 | 14 | | 1 | 19 | | 2 | 23 | | 3 | 13 | | 4 | 29 | | 5 | 21 | | 6 | 9 | | 7 | 13 | | 8 | 12 | | 9 | 1 | | 10 | 2 | | 11 | 11 | | 12 | 14 | | 13 | 5 | | 14 | 1 | | 15 | 1 | | 16 | 20 | | 17 | 11 | | 18 | 3 | | 19 | 7 | | 20 | 8 | | 21 | 4 | | 22 | 3 | | 23 | 7 | | 24 | 4 | | 25 | 7 | | 26 | 7 | | 27 | 16 | | 28 | 6 | | 29 | 17 | | 30 | 2 | | 31 | 10 | | 32 | 16 | | 33 | 1 | | 34 | 11 | | 35 | 26 | | 36 | 4 | | 37 | 9 | | 38 | 5 | | 39 | 8 | | 40 | 10 | | 41 | 6 | | 42 | 3 | | 43 | 2 | | 44 | 10 | | 45 | 5 | | 46 | 3 | | 47 | 6 | | 48 | 6 | | 49 | 1 |
| |
| 84.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5254237288135594 | | totalSentences | 59 | | uniqueOpeners | 31 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 49 | | matches | | 0 | "Only the unsettling stillness of" | | 1 | "Just an owl, surely." | | 2 | "Just her overactive imagination, spurred" | | 3 | "Finally, reluctantly, she turned back" |
| | ratio | 0.082 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 13 | | totalSentences | 49 | | matches | | 0 | "She stood at the edge" | | 1 | "She half-expected the trees to" | | 2 | "Her footsteps fell muffled on" | | 3 | "She switched on her flashlight," | | 4 | "Her voice barely carried over" | | 5 | "She laughed weakly at her" | | 6 | "She had to see this" | | 7 | "She was lost." | | 8 | "She'd find her way out." | | 9 | "She had to." | | 10 | "She shut her eyes, steeling" | | 11 | "She spun with a startled" | | 12 | "Her voice was music and" |
| | ratio | 0.265 | |
| 62.04% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 39 | | totalSentences | 49 | | matches | | 0 | "The Heartstone pulsed warm against" | | 1 | "She stood at the edge" | | 2 | "The air hummed with an" | | 3 | "This place OECDstitutionClassifier should not" | | 4 | "Aurora stepped forward, wending her" | | 5 | "The grove seemed to fold" | | 6 | "She half-expected the trees to" | | 7 | "Her footsteps fell muffled on" | | 8 | "The Grove held its breath." | | 9 | "She switched on her flashlight," | | 10 | "Her voice barely carried over" | | 11 | "A whisper of movement caught" | | 12 | "A flash of white between" | | 13 | "The grove was home to" | | 14 | "She laughed weakly at her" | | 15 | "Aurora pressed deeper into the" | | 16 | "She had to see this" | | 17 | "The pendant was her only" | | 18 | "A twig snapped off to" | | 19 | "The wind through the leaves" |
| | ratio | 0.796 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 5 | | matches | | 0 | "The air hummed with an otherworldly energy that sent chills down her spine, whispering of secrets long buried and magics best left undisturbed." | | 1 | "And yet, here it stood drinking in the moonlight, alive with the rustle of leaves and the hushed murmur of a breeze that carried the scent of wild roses." | | 2 | "Aurora stepped forward, wending her way between the boundary stones, each etched with runes that danced elusively away from her understanding." | | 3 | "Determined to see this through, she circled the clearing, playing her beam over ferns and mushrooms and pale blossoms that seemed to drink in the darkness." | | 4 | "The woman knelt beside her, movements liquid grace, and lifted a hand to brush Aurora's cheek, sending sparks of ice and fire dancing along her nerves." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "Aurora breathed (breathe)" |
| | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 1 | | effectiveRatio | 0.286 | |