| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1355 | | 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) | |
| 66.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1355 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "throbbed" | | 1 | "pulse" | | 2 | "weight" | | 3 | "footsteps" | | 4 | "silence" | | 5 | "pulsed" |
| |
| 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 | 166 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 166 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 173 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1355 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 1311 | | uniqueNames | 22 | | maxNameDensity | 0.84 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Richmond | 2 | | Park | 2 | | Heartstone | 1 | | Pendant | 1 | | Silas | 1 | | Evan | 1 | | Pen | 3 | | Ponds | 3 | | Jennifer | 1 | | Hel | 1 | | Fae | 1 | | Grove | 1 | | Eva | 2 | | Rory | 11 | | Cardiff | 2 | | Heat | 5 | | Wildflowers | 3 | | Left | 4 |
| | persons | | 0 | "Yu-Fei" | | 1 | "Cheung" | | 2 | "Pendant" | | 3 | "Silas" | | 4 | "Evan" | | 5 | "Jennifer" | | 6 | "Eva" | | 7 | "Rory" | | 8 | "Heat" | | 9 | "Wildflowers" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Pen" | | 3 | "Fae" | | 4 | "Grove" | | 5 | "Cardiff" | | 6 | "Left" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 118 | | 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 | 1355 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 136 | | mean | 9.96 | | std | 5.1 | | cv | 0.511 | | sampleLengths | | 0 | 5 | | 1 | 27 | | 2 | 14 | | 3 | 15 | | 4 | 10 | | 5 | 13 | | 6 | 29 | | 7 | 32 | | 8 | 15 | | 9 | 11 | | 10 | 20 | | 11 | 13 | | 12 | 8 | | 13 | 14 | | 14 | 11 | | 15 | 7 | | 16 | 11 | | 17 | 14 | | 18 | 3 | | 19 | 13 | | 20 | 12 | | 21 | 7 | | 22 | 6 | | 23 | 10 | | 24 | 10 | | 25 | 10 | | 26 | 11 | | 27 | 7 | | 28 | 8 | | 29 | 14 | | 30 | 6 | | 31 | 13 | | 32 | 12 | | 33 | 7 | | 34 | 10 | | 35 | 8 | | 36 | 6 | | 37 | 7 | | 38 | 26 | | 39 | 8 | | 40 | 6 | | 41 | 5 | | 42 | 6 | | 43 | 22 | | 44 | 24 | | 45 | 19 | | 46 | 16 | | 47 | 7 | | 48 | 4 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 166 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 209 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 173 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1314 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 11 | | adverbRatio | 0.00837138508371385 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 173 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 173 | | mean | 7.83 | | std | 4.34 | | cv | 0.555 | | sampleLengths | | 0 | 5 | | 1 | 27 | | 2 | 6 | | 3 | 8 | | 4 | 9 | | 5 | 6 | | 6 | 10 | | 7 | 13 | | 8 | 10 | | 9 | 19 | | 10 | 32 | | 11 | 15 | | 12 | 11 | | 13 | 16 | | 14 | 4 | | 15 | 13 | | 16 | 8 | | 17 | 14 | | 18 | 7 | | 19 | 2 | | 20 | 2 | | 21 | 7 | | 22 | 11 | | 23 | 6 | | 24 | 8 | | 25 | 3 | | 26 | 13 | | 27 | 4 | | 28 | 8 | | 29 | 4 | | 30 | 3 | | 31 | 6 | | 32 | 10 | | 33 | 10 | | 34 | 5 | | 35 | 5 | | 36 | 11 | | 37 | 7 | | 38 | 8 | | 39 | 14 | | 40 | 6 | | 41 | 13 | | 42 | 12 | | 43 | 7 | | 44 | 10 | | 45 | 8 | | 46 | 6 | | 47 | 7 | | 48 | 6 | | 49 | 20 |
| |
| 41.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.26011560693641617 | | totalSentences | 173 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 150 | | matches | (empty) | | ratio | 0 | |
| 94.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 47 | | totalSentences | 150 | | matches | | 0 | "Her trainers caught on a" | | 1 | "She wrenched free and landed" | | 2 | "Her breath fogged in a" | | 3 | "She pulled her jacket tight" | | 4 | "She blamed Evan for that" | | 5 | "She pushed it back." | | 6 | "Her left wrist throbbed where" | | 7 | "She counted five trunks to" | | 8 | "She held the phone out" | | 9 | "She shook the phone." | | 10 | "She slipped the phone into" | | 11 | "She set her foot down" | | 12 | "She ducked under a branch" | | 13 | "Her blue eyes watered from" | | 14 | "She stood and brushed dirt" | | 15 | "It warmed on the third" | | 16 | "She knew the pattern from" | | 17 | "She pulled the chain out" | | 18 | "She counted her own steps" | | 19 | "Her pulse beat in both" |
| | ratio | 0.313 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 130 | | totalSentences | 150 | | matches | | 0 | "The park gates stood locked." | | 1 | "Rory placed both palms on" | | 2 | "Her trainers caught on a" | | 3 | "She wrenched free and landed" | | 4 | "Her breath fogged in a" | | 5 | "She pulled her jacket tight" | | 6 | "The Heartstone Pendant lay cold" | | 7 | "Heat spread from the deep" | | 8 | "She blamed Evan for that" | | 9 | "A map on the back" | | 10 | "Rory tucked hair behind her" | | 11 | "The cut through bracken gave" | | 12 | "She pushed it back." | | 13 | "Her left wrist throbbed where" | | 14 | "The path narrowed and the" | | 15 | "She counted five trunks to" | | 16 | "Sound came from the pond" | | 17 | "A bell struck once across" | | 18 | "Rory stopped under an oak" | | 19 | "She held the phone out" |
| | ratio | 0.867 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 150 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |