| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1056 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 14.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1056 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "pulsed" | | 1 | "weight" | | 2 | "rhythmic" | | 3 | "sanctuary" | | 4 | "glint" | | 5 | "throbbed" | | 6 | "flicker" | | 7 | "perfect" | | 8 | "unreadable" | | 9 | "tracing" | | 10 | "silk" | | 11 | "silence" | | 12 | "measured" | | 13 | "stark" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | 0 | "the weight of the silence" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 67 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | 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 | 1055 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 820 | | uniqueNames | 11 | | maxNameDensity | 1.59 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Aurora | 13 | | Soho | 1 | | London | 2 | | Golden | 1 | | Empress | 1 | | Welsh | 1 | | Cardiff | 2 | | Silas | 1 | | Eva | 13 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Silas" | | 4 | "Eva" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Golden" | | 3 | "Cardiff" |
| | globalScore | 0.707 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a tear, but the woman remaine" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1055 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 18.84 | | std | 14.9 | | cv | 0.791 | | sampleLengths | | 0 | 57 | | 1 | 62 | | 2 | 51 | | 3 | 34 | | 4 | 14 | | 5 | 26 | | 6 | 1 | | 7 | 17 | | 8 | 30 | | 9 | 1 | | 10 | 21 | | 11 | 43 | | 12 | 6 | | 13 | 22 | | 14 | 9 | | 15 | 9 | | 16 | 18 | | 17 | 15 | | 18 | 20 | | 19 | 7 | | 20 | 22 | | 21 | 13 | | 22 | 14 | | 23 | 13 | | 24 | 5 | | 25 | 23 | | 26 | 12 | | 27 | 7 | | 28 | 47 | | 29 | 15 | | 30 | 16 | | 31 | 6 | | 32 | 15 | | 33 | 11 | | 34 | 44 | | 35 | 7 | | 36 | 24 | | 37 | 3 | | 38 | 11 | | 39 | 20 | | 40 | 4 | | 41 | 4 | | 42 | 33 | | 43 | 11 | | 44 | 23 | | 45 | 7 | | 46 | 27 | | 47 | 10 | | 48 | 14 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 67 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 125 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 93 | | ratio | 0.011 | | matches | | 0 | "The woman’s profile was a silhouette of precision—high cheekbones, a jawline carved from granite, and hair pulled back into a knot so tight it looked painful." |
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| 82.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 826 | | adjectiveStacks | 3 | | stackExamples | | 0 | "framed, sepia-toned map" | | 1 | "dim, map-strewn sanctuary." | | 2 | "small, crescent-shaped scar" |
| | adverbCount | 19 | | adverbRatio | 0.023002421307506054 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007263922518159807 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 11.34 | | std | 6.93 | | cv | 0.611 | | sampleLengths | | 0 | 24 | | 1 | 15 | | 2 | 18 | | 3 | 10 | | 4 | 32 | | 5 | 20 | | 6 | 17 | | 7 | 8 | | 8 | 26 | | 9 | 8 | | 10 | 26 | | 11 | 5 | | 12 | 9 | | 13 | 6 | | 14 | 20 | | 15 | 1 | | 16 | 6 | | 17 | 11 | | 18 | 3 | | 19 | 18 | | 20 | 9 | | 21 | 1 | | 22 | 3 | | 23 | 18 | | 24 | 5 | | 25 | 17 | | 26 | 21 | | 27 | 6 | | 28 | 16 | | 29 | 6 | | 30 | 9 | | 31 | 9 | | 32 | 18 | | 33 | 15 | | 34 | 6 | | 35 | 3 | | 36 | 11 | | 37 | 7 | | 38 | 11 | | 39 | 11 | | 40 | 13 | | 41 | 6 | | 42 | 8 | | 43 | 13 | | 44 | 5 | | 45 | 23 | | 46 | 12 | | 47 | 7 | | 48 | 22 | | 49 | 10 |
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| 41.40% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.23655913978494625 | | totalSentences | 93 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 84.62% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 65 | | matches | | 0 | "Her shoulder ached from the" | | 1 | "She pushed a stray lock" | | 2 | "She didn't belong in this" | | 3 | "It felt heavy, like a" | | 4 | "She set her glass down" | | 5 | "She remained anchored to the" | | 6 | "She stopped at the edge" | | 7 | "She swirled the amber liquid" | | 8 | "She sat, feeling the grit" | | 9 | "She leaned back, the silk" | | 10 | "They were red-raw from dishwater" | | 11 | "It looked like a tear," | | 12 | "Her voice was low, stripped" | | 13 | "She forced her breathing to" | | 14 | "She extracted a crisp note" | | 15 | "It sat there, white and" | | 16 | "It felt insulting, a transaction" | | 17 | "She smoothed the front of" | | 18 | "She turned to leave, her" | | 19 | "She didn't move." |
| | ratio | 0.338 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 65 | | matches | | 0 | "The green neon sign outside" | | 1 | "Rain streaked the windows, blurring" | | 2 | "Aurora wiped a ring of" | | 3 | "Her shoulder ached from the" | | 4 | "She pushed a stray lock" | | 5 | "A woman sat in the" | | 6 | "She didn't belong in this" | | 7 | "The light from a single" | | 8 | "Aurora paused, the cloth stilled" | | 9 | "The woman’s profile was a" | | 10 | "The woman turned her head." | | 11 | "The candlelight hit her eyes," | | 12 | "Aurora’s grip tightened on the" | | 13 | "The small, crescent-shaped scar on" | | 14 | "The word barely escaped her" | | 15 | "It felt heavy, like a" | | 16 | "The woman froze." | | 17 | "The poise didn't break, but" | | 18 | "She set her glass down" | | 19 | "Eva didn't stand." |
| | ratio | 0.985 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 65 | | matches | (empty) | | ratio | 0 | |
| 84.94% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 3 | | matches | | 0 | "The girl who had shared peppermint sweets and whispered secrets in a Cardiff bedroom was gone, replaced by this creature of sharp angles and cold currency." | | 1 | "She smoothed the front of her blazer, her expression hardening back into the mask of the woman who conquered boardrooms." | | 2 | "The green neon light hummed, indifferent to the weight of the silence left in the wake of the woman who had once been her entire world." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0 | | effectiveRatio | 0 | |