| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.063 | | leniency | 0.125 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1309 | | 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) | |
| 8.33% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1309 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | | | 21 | | | 22 | |
| | highlights | | 0 | "flickered" | | 1 | "rhythmic" | | 2 | "familiar" | | 3 | "throb" | | 4 | "reminder" | | 5 | "weight" | | 6 | "warmth" | | 7 | "chaotic" | | 8 | "lilt" | | 9 | "intensity" | | 10 | "echoing" | | 11 | "furrowing" | | 12 | "scanning" | | 13 | "silence" | | 14 | "fleeting" | | 15 | "flicker" | | 16 | "profound" | | 17 | "whisper" | | 18 | "measured" | | 19 | "single tear" | | 20 | "perfect" | | 21 | "crystalline" | | 22 | "calculated" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 120 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1306 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 842 | | uniqueNames | 10 | | maxNameDensity | 1.31 | | worstName | "Julian" | | maxWindowNameDensity | 3 | | worstWindowName | "Clara" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 2 | | Blackwood | 1 | | Prague | 1 | | London | 1 | | Balkans | 1 | | Clara | 10 | | Julian | 11 | | Silas | 4 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Blackwood" | | 3 | "Clara" | | 4 | "Julian" | | 5 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Prague" | | 2 | "London" |
| | globalScore | 0.847 | | windowScore | 0.667 | |
| 60.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like she had been carved from a di" | | 1 | "sounded like a gavel hitting a block" |
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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 | 1306 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 120 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 16.12 | | std | 13.97 | | cv | 0.866 | | sampleLengths | | 0 | 56 | | 1 | 37 | | 2 | 30 | | 3 | 52 | | 4 | 13 | | 5 | 1 | | 6 | 17 | | 7 | 43 | | 8 | 1 | | 9 | 22 | | 10 | 14 | | 11 | 12 | | 12 | 14 | | 13 | 39 | | 14 | 6 | | 15 | 5 | | 16 | 27 | | 17 | 21 | | 18 | 4 | | 19 | 17 | | 20 | 35 | | 21 | 40 | | 22 | 2 | | 23 | 2 | | 24 | 25 | | 25 | 16 | | 26 | 7 | | 27 | 20 | | 28 | 10 | | 29 | 5 | | 30 | 1 | | 31 | 27 | | 32 | 9 | | 33 | 10 | | 34 | 43 | | 35 | 7 | | 36 | 7 | | 37 | 3 | | 38 | 5 | | 39 | 46 | | 40 | 12 | | 41 | 3 | | 42 | 2 | | 43 | 9 | | 44 | 36 | | 45 | 33 | | 46 | 4 | | 47 | 5 | | 48 | 9 | | 49 | 22 |
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| 91.23% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 75 | | matches | | 0 | "been carved" | | 1 | "was frayed" | | 2 | "was measured" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 71.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 120 | | ratio | 0.025 | | matches | | 0 | "His left leg gave a sharp, familiar throb—a ghostly reminder of Prague—prompting him to shift his weight." | | 1 | "A flicker of something raw and jagged peered through—a grief so profound it seemed to age her by a decade in a heartbeat." | | 2 | "The distance between them wasn't measured in inches; it was measured in the miles of divergent paths they had walked since that final summer." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 849 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 18 | | adverbRatio | 0.02120141342756184 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008244994110718492 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 120 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 120 | | mean | 10.88 | | std | 8.04 | | cv | 0.739 | | sampleLengths | | 0 | 21 | | 1 | 16 | | 2 | 19 | | 3 | 20 | | 4 | 17 | | 5 | 4 | | 6 | 26 | | 7 | 15 | | 8 | 18 | | 9 | 19 | | 10 | 2 | | 11 | 11 | | 12 | 1 | | 13 | 9 | | 14 | 8 | | 15 | 4 | | 16 | 7 | | 17 | 16 | | 18 | 16 | | 19 | 1 | | 20 | 5 | | 21 | 17 | | 22 | 14 | | 23 | 12 | | 24 | 14 | | 25 | 12 | | 26 | 15 | | 27 | 12 | | 28 | 6 | | 29 | 5 | | 30 | 16 | | 31 | 11 | | 32 | 4 | | 33 | 17 | | 34 | 4 | | 35 | 17 | | 36 | 14 | | 37 | 12 | | 38 | 6 | | 39 | 3 | | 40 | 10 | | 41 | 15 | | 42 | 8 | | 43 | 7 | | 44 | 2 | | 45 | 2 | | 46 | 11 | | 47 | 14 | | 48 | 16 | | 49 | 7 |
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| 42.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.26666666666666666 | | totalSentences | 120 | | uniqueOpeners | 32 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 42.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 70 | | matches | | 0 | "His left leg gave a" | | 1 | "She wore a tailored charcoal" | | 2 | "Her hair, once a chaotic" | | 3 | "She stopped dead in the" | | 4 | "It sounded like a gavel" | | 5 | "He looked older than his" | | 6 | "His flannel shirt was frayed" | | 7 | "He held a pint of" | | 8 | "She didn't move toward him." | | 9 | "She stayed rooted in the" | | 10 | "She stopped three feet away," | | 11 | "She looked at his worn" | | 12 | "He became a silent observer," | | 13 | "Her eyes, once wide with" | | 14 | "She reached into her leather" | | 15 | "She didn't ask for a" | | 16 | "She simply waited." | | 17 | "He stepped closer, the smell" | | 18 | "She looked around the bar," | | 19 | "She turned away, her eyes" |
| | ratio | 0.443 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 70 | | matches | | 0 | "The green neon sign of" | | 1 | "Maps of forgotten empires clung" | | 2 | "Silas Blackwood leaned against the" | | 3 | "His left leg gave a" | | 4 | "The door groaned open." | | 5 | "A gust of cold London" | | 6 | "She wore a tailored charcoal" | | 7 | "Her hair, once a chaotic" | | 8 | "She stopped dead in the" | | 9 | "The tumbler slipped from his" | | 10 | "The woman’s voice lacked the" | | 11 | "It sounded like a gavel" | | 12 | "Julian stared at her." | | 13 | "He looked older than his" | | 14 | "His flannel shirt was frayed" | | 15 | "He held a pint of" | | 16 | "She didn't move toward him." | | 17 | "She stayed rooted in the" | | 18 | "Julian took a slow sip" | | 19 | "Clara stepped forward, the click" |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 70 | | matches | (empty) | | ratio | 0 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "A gust of cold London air sliced through the warmth, bringing with it a woman who looked like she had been carved from a different era." | | 1 | "Her hair, once a chaotic blonde mane, now fell in a severe, platinum bob that grazed her jawline." | | 2 | "The silence stretched between them, thick and suffocating, filled with the ghosts of letters never sent and apologies that had rotted in their throats." | | 3 | "Her movements were fluid, calculated, and devoid of the hesitations that had defined her youth." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "She gestured, her bag, her polished exterior" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 48 | | tagDensity | 0.042 | | leniency | 0.083 | | rawRatio | 0.5 | | effectiveRatio | 0.042 | |