| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "His accent wrapped around [around]" |
| | dialogueSentences | 56 | | tagDensity | 0.232 | | leniency | 0.464 | | rawRatio | 0.077 | | effectiveRatio | 0.036 | |
| 95.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1105 | | 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) | |
| 59.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1105 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "comfortable" | | 1 | "throbbed" | | 2 | "silk" | | 3 | "silence" | | 4 | "measured" | | 5 | "racing" | | 6 | "pulse" | | 7 | "eyebrow" | | 8 | "shattered" |
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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 | 1 | | narrationSentences | 81 | | matches | | |
| 72.31% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "try to" | | 2 | "tried to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1105 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 768 | | uniqueNames | 15 | | maxNameDensity | 0.78 | | worstName | "Eva" | | maxWindowNameDensity | 2 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 6 | | Moreau | 1 | | French | 1 | | London | 1 | | Three | 2 | | Kensington | 2 | | Demon | 1 | | Avaros | 1 | | Lucien | 5 | | Small | 1 | | Evan | 2 | | Bitter | 1 | | Marseille | 1 | | Cardiff | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Eva" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Evan" | | 4 | "Ptolemy" |
| | places | | 0 | "London" | | 1 | "Kensington" | | 2 | "Avaros" | | 3 | "Marseille" | | 4 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1105 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 19.05 | | std | 19.43 | | cv | 1.02 | | sampleLengths | | 0 | 7 | | 1 | 27 | | 2 | 6 | | 3 | 63 | | 4 | 25 | | 5 | 6 | | 6 | 54 | | 7 | 1 | | 8 | 1 | | 9 | 71 | | 10 | 44 | | 11 | 4 | | 12 | 1 | | 13 | 1 | | 14 | 18 | | 15 | 44 | | 16 | 2 | | 17 | 76 | | 18 | 2 | | 19 | 6 | | 20 | 19 | | 21 | 4 | | 22 | 8 | | 23 | 37 | | 24 | 19 | | 25 | 53 | | 26 | 24 | | 27 | 4 | | 28 | 40 | | 29 | 2 | | 30 | 10 | | 31 | 23 | | 32 | 4 | | 33 | 5 | | 34 | 5 | | 35 | 44 | | 36 | 1 | | 37 | 2 | | 38 | 45 | | 39 | 13 | | 40 | 7 | | 41 | 12 | | 42 | 4 | | 43 | 33 | | 44 | 5 | | 45 | 18 | | 46 | 36 | | 47 | 6 | | 48 | 3 | | 49 | 3 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 139 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 124 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 770 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.024675324675324677 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0025974025974025974 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 8.91 | | std | 7.21 | | cv | 0.809 | | sampleLengths | | 0 | 7 | | 1 | 15 | | 2 | 3 | | 3 | 9 | | 4 | 2 | | 5 | 4 | | 6 | 20 | | 7 | 19 | | 8 | 8 | | 9 | 6 | | 10 | 10 | | 11 | 17 | | 12 | 8 | | 13 | 6 | | 14 | 35 | | 15 | 15 | | 16 | 4 | | 17 | 1 | | 18 | 1 | | 19 | 15 | | 20 | 2 | | 21 | 27 | | 22 | 18 | | 23 | 9 | | 24 | 26 | | 25 | 5 | | 26 | 4 | | 27 | 9 | | 28 | 4 | | 29 | 1 | | 30 | 1 | | 31 | 10 | | 32 | 3 | | 33 | 2 | | 34 | 3 | | 35 | 6 | | 36 | 1 | | 37 | 16 | | 38 | 21 | | 39 | 2 | | 40 | 17 | | 41 | 14 | | 42 | 7 | | 43 | 4 | | 44 | 10 | | 45 | 11 | | 46 | 13 | | 47 | 2 | | 48 | 6 | | 49 | 8 |
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| 56.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.4112903225806452 | | totalSentences | 124 | | uniqueOpeners | 51 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 62.25% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 71 | | matches | | 0 | "I froze, hand outstretched toward" | | 1 | "His heterochromatic eyes, one amber" | | 2 | "His accent wrapped around the" | | 3 | "He stepped inside without invitation," | | 4 | "His tailored charcoal suit looked" | | 5 | "I glanced at the clock" | | 6 | "He moved deeper into the" | | 7 | "He stopped at the window," | | 8 | "My chest tightened, and I" | | 9 | "He turned from the window," | | 10 | "His father from Avaros, whatever" | | 11 | "It meant those eyes." | | 12 | "It meant the way he" | | 13 | "It meant I'd trusted him," | | 14 | "He wound between Lucien's ankles," | | 15 | "I crossed my arms over" | | 16 | "I heard the accusation in" | | 17 | "I tasted the word" | | 18 | "He moved toward me, each" | | 19 | "He was close now." |
| | ratio | 0.394 | |
| 9.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 64 | | totalSentences | 71 | | matches | | 0 | "The deadbolt turned before I" | | 1 | "I froze, hand outstretched toward" | | 2 | "Ptolemy's ears flattened." | | 3 | "The tabby shot under Eva's" | | 4 | "The door swung inward." | | 5 | "Lucien Moreau stood in the" | | 6 | "His heterochromatic eyes, one amber" | | 7 | "The old comfortable jumper I'd" | | 8 | "The chai I'd let go" | | 9 | "The shadows under my eyes" | | 10 | "His accent wrapped around the" | | 11 | "He stepped inside without invitation," | | 12 | "His tailored charcoal suit looked" | | 13 | "The words came out sharper" | | 14 | "I glanced at the clock" | | 15 | "He moved deeper into the" | | 16 | "That he'd been here before." | | 17 | "That he'd been watching." | | 18 | "He stopped at the window," | | 19 | "The name hit like a" |
| | ratio | 0.901 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 32.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 4 | | matches | | 0 | "His heterochromatic eyes, one amber and one black, swept over me in a single assessing glance that missed nothing." | | 1 | "I threw my arms up as something large and dark vaulted through the broken frame, landing in a crouch that cracked the floorboards." | | 2 | "Grey skin stretched over a skull that was wrong, too angular, too many teeth." | | 3 | "A name that belonged to a different life, a different world, one I'd buried when I'd fled Cardiff." |
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| 48.08% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 2 | | matches | | 0 | "He turned, and the streetlight caught his mismatched eyes" | | 1 | "He moved, each step measured, deliberate" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 56 | | tagDensity | 0.018 | | leniency | 0.036 | | rawRatio | 1 | | effectiveRatio | 0.036 | |