| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.295 | | leniency | 0.591 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1308 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "gently" | | 1 | "carefully" | | 2 | "slowly" | | 3 | "completely" |
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| 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) | |
| 4.43% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1308 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "scanning" | | 1 | "pulsed" | | 2 | "beacon" | | 3 | "wavered" | | 4 | "rhythmic" | | 5 | "loomed" | | 6 | "silk" | | 7 | "scanned" | | 8 | "traced" | | 9 | "etched" | | 10 | "pulse" | | 11 | "tracing" | | 12 | "structure" | | 13 | "mechanical" | | 14 | "throbbed" | | 15 | "churning" | | 16 | "tension" | | 17 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 106 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 106 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 137 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1308 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 20.89% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 54 | | wordCount | 852 | | uniqueNames | 9 | | maxNameDensity | 2.58 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 5 | | Rory | 22 | | Fae-Forged | 1 | | Blade | 3 | | Nyx | 18 | | Golden | 1 | | Empress | 1 | | Cheung | 1 | | Ming | 2 |
| | persons | | 0 | "Heartstone" | | 1 | "Rory" | | 2 | "Nyx" | | 3 | "Cheung" | | 4 | "Ming" |
| | places | (empty) | | globalScore | 0.209 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | 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 | 1308 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 137 | | matches | (empty) | |
| 88.67% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 28.43 | | std | 13.09 | | cv | 0.46 | | sampleLengths | | 0 | 68 | | 1 | 42 | | 2 | 20 | | 3 | 42 | | 4 | 30 | | 5 | 41 | | 6 | 21 | | 7 | 23 | | 8 | 45 | | 9 | 18 | | 10 | 27 | | 11 | 19 | | 12 | 49 | | 13 | 17 | | 14 | 39 | | 15 | 25 | | 16 | 24 | | 17 | 41 | | 18 | 12 | | 19 | 8 | | 20 | 15 | | 21 | 27 | | 22 | 19 | | 23 | 11 | | 24 | 43 | | 25 | 23 | | 26 | 28 | | 27 | 26 | | 28 | 44 | | 29 | 61 | | 30 | 12 | | 31 | 35 | | 32 | 19 | | 33 | 24 | | 34 | 36 | | 35 | 22 | | 36 | 40 | | 37 | 36 | | 38 | 12 | | 39 | 29 | | 40 | 21 | | 41 | 20 | | 42 | 36 | | 43 | 26 | | 44 | 14 | | 45 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 163 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 137 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 857 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 16 | | adverbRatio | 0.01866977829638273 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005834305717619603 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 137 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 137 | | mean | 9.55 | | std | 5.39 | | cv | 0.564 | | sampleLengths | | 0 | 21 | | 1 | 14 | | 2 | 12 | | 3 | 12 | | 4 | 9 | | 5 | 17 | | 6 | 7 | | 7 | 18 | | 8 | 12 | | 9 | 8 | | 10 | 11 | | 11 | 10 | | 12 | 21 | | 13 | 5 | | 14 | 12 | | 15 | 13 | | 16 | 5 | | 17 | 13 | | 18 | 13 | | 19 | 10 | | 20 | 7 | | 21 | 14 | | 22 | 8 | | 23 | 15 | | 24 | 22 | | 25 | 12 | | 26 | 11 | | 27 | 7 | | 28 | 11 | | 29 | 5 | | 30 | 12 | | 31 | 2 | | 32 | 1 | | 33 | 7 | | 34 | 4 | | 35 | 3 | | 36 | 9 | | 37 | 3 | | 38 | 6 | | 39 | 8 | | 40 | 9 | | 41 | 9 | | 42 | 3 | | 43 | 14 | | 44 | 9 | | 45 | 8 | | 46 | 6 | | 47 | 12 | | 48 | 21 | | 49 | 7 |
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| 67.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.41605839416058393 | | totalSentences | 137 | | uniqueOpeners | 57 | |
| 34.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 98 | | matches | | | ratio | 0.01 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 98 | | matches | | 0 | "She gritted her teeth, fingers" | | 1 | "Their violet eyes narrowed, scanning" | | 2 | "Their form wavered, edges dissolving" | | 3 | "They moved into the grove." | | 4 | "She pointed toward a break" | | 5 | "Their heads were smooth ovals" | | 6 | "She scanned the perimeter" | | 7 | "They crept along the ridge" | | 8 | "She glanced down." | | 9 | "she noted, voice low" | | 10 | "She scrambled forward, ignoring Nyx's" | | 11 | "She rolled the body over." | | 12 | "His skin had turned the" | | 13 | "She grabbed his wrist, turning" | | 14 | "She scanned the runes." | | 15 | "She stood, sheathing the Blade" | | 16 | "She looked at the Heartstone" | | 17 | "She kicked the grate." | | 18 | "She looked back at the" | | 19 | "She tested the rope's tension." |
| | ratio | 0.204 | |
| 11.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 98 | | matches | | 0 | "The rift tore open with" | | 1 | "Rory stepped through, her boots" | | 2 | "The Heartstone pressed against her" | | 3 | "She gritted her teeth, fingers" | | 4 | "The gem burned, a crimson" | | 5 | "Nyx flowed over the threshold," | | 6 | "Their violet eyes narrowed, scanning" | | 7 | "The air here tasted of" | | 8 | "Nyx whispered, voice rustling like" | | 9 | "Rory touched the crescent scar" | | 10 | "The stone pulsed, rhythm matching" | | 11 | "Nyx murmured, shifting stance" | | 12 | "Their form wavered, edges dissolving" | | 13 | "They moved into the grove." | | 14 | "Vines thick as ship ropes" | | 15 | "Leaves dripped golden syrup that" | | 16 | "The ground pulsed gently, a" | | 17 | "Rory crouched, eyes tracking the" | | 18 | "Nyx drifted forward, feet barely" | | 19 | "Rory stood, hand brushing the" |
| | ratio | 0.898 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "Rory stepped through, her boots hitting soil that felt spongy and far too warm." | | 1 | "Leaves dripped golden syrup that pooled in depressions, buzzing with fat, iridescent flies." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 6 | | matches | | 0 | "Nyx whispered, voice rustling like dry leaves skittering over stone" | | 1 | "Nyx hissed, shadows bristling along the arms" | | 2 | "she noted, voice low" | | 3 | "Rory said, voice flat" | | 4 | "Rory gripped, muscles straining" | | 5 | "Nyx whispered, voice carrying on the updraft" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 7 | | fancyTags | | 0 | "Nyx whispered (whisper)" | | 1 | "Nyx murmured (murmur)" | | 2 | "Nyx hissed (hiss)" | | 3 | "she noted (note)" | | 4 | "Rory breathed (breathe)" | | 5 | "Nyx murmured (murmur)" | | 6 | "Nyx whispered (whisper)" |
| | dialogueSentences | 44 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.875 | | effectiveRatio | 0.318 | |