| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 700 | | 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) | |
| 28.57% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 700 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "chill" | | 1 | "loomed" | | 2 | "silence" | | 3 | "echoed" | | 4 | "stomach" | | 5 | "pulse" | | 6 | "rhythmic" | | 7 | "tracing" | | 8 | "vibrated" |
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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 | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 65 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 700 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 687 | | uniqueNames | 6 | | maxNameDensity | 0.73 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Park | 1 | | Heartstone | 1 | | Pendant | 1 | | London | 1 | | Cardiff | 1 | | Aurora | 5 |
| | persons | | | places | | 0 | "Park" | | 1 | "London" | | 2 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | 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 | 700 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 30.43 | | std | 20.58 | | cv | 0.676 | | sampleLengths | | 0 | 81 | | 1 | 17 | | 2 | 11 | | 3 | 55 | | 4 | 29 | | 5 | 53 | | 6 | 32 | | 7 | 2 | | 8 | 14 | | 9 | 51 | | 10 | 35 | | 11 | 11 | | 12 | 69 | | 13 | 18 | | 14 | 46 | | 15 | 1 | | 16 | 20 | | 17 | 11 | | 18 | 43 | | 19 | 18 | | 20 | 28 | | 21 | 32 | | 22 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 98 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 689 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.03773584905660377 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008708272859216255 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 65 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 65 | | mean | 10.77 | | std | 5.25 | | cv | 0.488 | | sampleLengths | | 0 | 9 | | 1 | 6 | | 2 | 12 | | 3 | 9 | | 4 | 7 | | 5 | 11 | | 6 | 11 | | 7 | 7 | | 8 | 9 | | 9 | 17 | | 10 | 11 | | 11 | 5 | | 12 | 17 | | 13 | 8 | | 14 | 12 | | 15 | 13 | | 16 | 7 | | 17 | 11 | | 18 | 11 | | 19 | 9 | | 20 | 2 | | 21 | 18 | | 22 | 14 | | 23 | 10 | | 24 | 11 | | 25 | 8 | | 26 | 13 | | 27 | 2 | | 28 | 10 | | 29 | 4 | | 30 | 12 | | 31 | 6 | | 32 | 22 | | 33 | 11 | | 34 | 8 | | 35 | 1 | | 36 | 13 | | 37 | 13 | | 38 | 11 | | 39 | 3 | | 40 | 16 | | 41 | 18 | | 42 | 9 | | 43 | 23 | | 44 | 18 | | 45 | 7 | | 46 | 16 | | 47 | 6 | | 48 | 17 | | 49 | 1 |
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| 56.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.38461538461538464 | | totalSentences | 65 | | uniqueOpeners | 25 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 61 | | matches | | 0 | "Usually, the city hummed a" | | 1 | "Then another answered, but the" | | 2 | "Just a dead drop for" | | 3 | "Too fast for a fox," | | 4 | "Then another ninety." |
| | ratio | 0.082 | |
| 88.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 61 | | matches | | 0 | "Her breath plumed grey against" | | 1 | "She reached beneath her collar," | | 2 | "She checked the watch on" | | 3 | "she murmured to the dark" | | 4 | "She swung her leg over" | | 5 | "It clicked in the high" | | 6 | "She stepped off the path," | | 7 | "It drifted sideways, staying perpendicular" | | 8 | "She blinked and stared straight" | | 9 | "She walked forward, thumb worrying" | | 10 | "It moved with a jagged," | | 11 | "she lied, her voice tight" | | 12 | "They hadn't been there when" | | 13 | "She knew every inch of" | | 14 | "It wore a heavy wool" | | 15 | "Its limbs elongated, joints cracking" | | 16 | "It didn't turn back around," | | 17 | "She hit the ground hard," | | 18 | "It stood eight feet tall" | | 19 | "It stepped across the threshold" |
| | ratio | 0.328 | |
| 17.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 61 | | matches | | 0 | "The headlights cut out, plunging" | | 1 | "Richmond Park swallowed the engine" | | 2 | "Aurora killed the ignition, the" | | 3 | "Fog rolled across the asphalt" | | 4 | "Her breath plumed grey against" | | 5 | "She reached beneath her collar," | | 6 | "The Heartstone Pendant rested against" | | 7 | "She checked the watch on" | | 8 | "The hands spun backward once," | | 9 | "she murmured to the dark" | | 10 | "The silence stretched too wide." | | 11 | "The air tasted of crushed" | | 12 | "She swung her leg over" | | 13 | "The sound echoed back at" | | 14 | "It clicked in the high" | | 15 | "Aurora unclipped the delivery box" | | 16 | "She stepped off the path," | | 17 | "The ground felt spongy, like" | | 18 | "A shadow detached itself from" | | 19 | "It drifted sideways, staying perpendicular" |
| | ratio | 0.885 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 1 | | matches | | 0 | "The perimeter stones began to hum, a deep, resonant tone that vibrated inside her skull." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she lied, her voice tight and thin" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she murmured (murmur)" | | 1 | "she lied (lie)" |
| | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |