| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 532 | | totalAiIsmAdverbs | 1 | | 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) | |
| 15.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 532 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "charged" | | 1 | "vibrated" | | 2 | "crystal" | | 3 | "structure" | | 4 | "pulsed" | | 5 | "pounding" | | 6 | "beacon" | | 7 | "weight" |
| |
| 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 | 32 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 32 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 41 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 526 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 36.73% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 309 | | uniqueNames | 6 | | maxNameDensity | 2.27 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Finn | 3 | | Tala | 4 | | Isolde | 5 | | Rory | 7 | | Heartstone | 2 | | Fae-light | 1 |
| | persons | | 0 | "Finn" | | 1 | "Tala" | | 2 | "Isolde" | | 3 | "Rory" |
| | places | | | globalScore | 0.367 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 22 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 526 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 41 | | matches | (empty) | |
| 42.47% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 35.07 | | std | 10.47 | | cv | 0.299 | | sampleLengths | | 0 | 45 | | 1 | 43 | | 2 | 26 | | 3 | 39 | | 4 | 31 | | 5 | 42 | | 6 | 10 | | 7 | 42 | | 8 | 18 | | 9 | 28 | | 10 | 48 | | 11 | 31 | | 12 | 39 | | 13 | 44 | | 14 | 40 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 32 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 60 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 315 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.009523809523809525 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0031746031746031746 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 41 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 41 | | mean | 12.83 | | std | 8.48 | | cv | 0.661 | | sampleLengths | | 0 | 22 | | 1 | 11 | | 2 | 12 | | 3 | 5 | | 4 | 12 | | 5 | 12 | | 6 | 14 | | 7 | 18 | | 8 | 8 | | 9 | 15 | | 10 | 10 | | 11 | 14 | | 12 | 10 | | 13 | 9 | | 14 | 12 | | 15 | 9 | | 16 | 10 | | 17 | 10 | | 18 | 9 | | 19 | 4 | | 20 | 9 | | 21 | 1 | | 22 | 4 | | 23 | 38 | | 24 | 8 | | 25 | 10 | | 26 | 13 | | 27 | 5 | | 28 | 10 | | 29 | 14 | | 30 | 3 | | 31 | 31 | | 32 | 8 | | 33 | 23 | | 34 | 4 | | 35 | 35 | | 36 | 4 | | 37 | 29 | | 38 | 11 | | 39 | 25 | | 40 | 15 |
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| 100.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 0 | | diversityRatio | 0.6097560975609756 | | totalSentences | 41 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 31 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 5 | | totalSentences | 31 | | matches | | 0 | "Her silver hair rippled like" | | 1 | "She wore a dress the" | | 2 | "Her lilting accent lent an" | | 3 | "She stepped closer to Rory." | | 4 | "She turned to Rory." |
| | ratio | 0.161 | |
| 72.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 24 | | totalSentences | 31 | | matches | | 0 | "Rory, Finn, and Tala stood" | | 1 | "The air here felt heavy" | | 2 | "Tala stepped forward first, ducking" | | 3 | "Emerald moss coated every surface." | | 4 | "Bioluminescent vines hung from the" | | 5 | "Finn remarked, stooping to cup" | | 6 | "Tala waded into the shallow" | | 7 | "Rory followed, the moonsilver blade" | | 8 | "A barn door-type entrance creaked" | | 9 | "Her silver hair rippled like" | | 10 | "She wore a dress the" | | 11 | "the seer greeted, eyes flickering" | | 12 | "Rory asked, heart pounding" | | 13 | "Isolde inclined her head." | | 14 | "Her lilting accent lent an" | | 15 | "Isolde said, ignoring his outburst" | | 16 | "She stepped closer to Rory." | | 17 | "Rory pulled out the Heartstone" | | 18 | "The seer nodded." | | 19 | "Tala let out a shuddering" |
| | ratio | 0.774 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 31 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 1 | | matches | | 0 | "In the center stood a man-made structure that defied explanation." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "the seer greeted, eyes flickering between them" | | 1 | "Rory asked, heart pounding" |
| |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "Finn exclaimed (exclaim)" |
| | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0.333 | | effectiveRatio | 0.125 | |