| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 5 | | adverbTags | | 0 | "she said coldly [coldly]" | | 1 | "he said quietly [quietly]" | | 2 | "he whispered hoarsely [hoarsely]" | | 3 | "Evan said brokenly [brokenly]" | | 4 | "he whispered raggedly [raggedly]" |
| | dialogueSentences | 27 | | tagDensity | 0.481 | | leniency | 0.963 | | rawRatio | 0.385 | | effectiveRatio | 0.37 | |
| 89.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 942 | | 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) | |
| 46.92% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 942 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "sense of" | | 1 | "trembled" | | 2 | "weight" | | 3 | "shattered" | | 4 | "flicker" | | 5 | "familiar" | | 6 | "tenderness" | | 7 | "etched" | | 8 | "pang" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "flicker of emotion" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 68 | | matches | | 0 | "d in disbelief" | | 1 | "A flicker of hope" |
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| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 68 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 940 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 655 | | uniqueNames | 11 | | maxNameDensity | 0.61 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Carter | 1 | | Rory | 4 | | Raven | 1 | | Nest | 1 | | Thursday | 1 | | Soho | 1 | | Silas | 2 | | Blackwood | 1 | | Evan | 2 | | Rhys | 1 | | Cardiff | 1 |
| | persons | | 0 | "Carter" | | 1 | "Rory" | | 2 | "Silas" | | 3 | "Blackwood" | | 4 | "Evan" |
| | places | | 0 | "Raven" | | 1 | "Soho" | | 2 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | 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 | 940 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 33.57 | | std | 19.09 | | cv | 0.569 | | sampleLengths | | 0 | 51 | | 1 | 50 | | 2 | 35 | | 3 | 16 | | 4 | 16 | | 5 | 84 | | 6 | 24 | | 7 | 9 | | 8 | 7 | | 9 | 21 | | 10 | 24 | | 11 | 25 | | 12 | 23 | | 13 | 21 | | 14 | 22 | | 15 | 28 | | 16 | 43 | | 17 | 55 | | 18 | 41 | | 19 | 12 | | 20 | 74 | | 21 | 30 | | 22 | 29 | | 23 | 70 | | 24 | 34 | | 25 | 29 | | 26 | 23 | | 27 | 44 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 68 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 102 | | matches | (empty) | |
| 73.17% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 82 | | ratio | 0.024 | | matches | | 0 | "But those bright blue eyes, that crescent-shaped scar on his left wrist - Evan ap Rhys, her ex from university days in Cardiff." | | 1 | "The raw pain in his voice, the shattered look in his eyes - it cracked something open in her." |
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| 95.05% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 657 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.045662100456621 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.0167427701674277 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 11.46 | | std | 8.14 | | cv | 0.71 | | sampleLengths | | 0 | 20 | | 1 | 31 | | 2 | 17 | | 3 | 8 | | 4 | 21 | | 5 | 4 | | 6 | 2 | | 7 | 11 | | 8 | 10 | | 9 | 12 | | 10 | 14 | | 11 | 2 | | 12 | 9 | | 13 | 7 | | 14 | 12 | | 15 | 9 | | 16 | 6 | | 17 | 3 | | 18 | 23 | | 19 | 14 | | 20 | 17 | | 21 | 4 | | 22 | 9 | | 23 | 5 | | 24 | 6 | | 25 | 4 | | 26 | 5 | | 27 | 5 | | 28 | 2 | | 29 | 17 | | 30 | 3 | | 31 | 1 | | 32 | 6 | | 33 | 18 | | 34 | 7 | | 35 | 18 | | 36 | 19 | | 37 | 4 | | 38 | 8 | | 39 | 13 | | 40 | 5 | | 41 | 12 | | 42 | 5 | | 43 | 10 | | 44 | 18 | | 45 | 13 | | 46 | 11 | | 47 | 19 | | 48 | 7 | | 49 | 16 |
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| 73.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.5 | | totalSentences | 82 | | uniqueOpeners | 41 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 66 | | matches | | 0 | "Just then, the door swung" | | 1 | "Wordlessly, she reached out, grabbed" | | 2 | "Finally, she pulled back with" | | 3 | "Then he seemed to remember" |
| | ratio | 0.061 | |
| 68.48% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 66 | | matches | | 0 | "She sidled up to the" | | 1 | "She took a generous swig" | | 2 | "It couldn't be." | | 3 | "He looked different, though." | | 4 | "His eyes met hers and" | | 5 | "He sounded uncertain" | | 6 | "She gripped her glass tightly." | | 7 | "She let out a sharp" | | 8 | "She shook her head in" | | 9 | "He took a step closer," | | 10 | "she said coldly, eyeing his" | | 11 | "he said quietly" | | 12 | "Her voice shook" | | 13 | "She took another long drink." | | 14 | "He looked at his feet," | | 15 | "She stared at him, searching" | | 16 | "he whispered hoarsely, shoulders slumped" | | 17 | "Her hands trembled." | | 18 | "She believed him." | | 19 | "He shuddered against her, clinging" |
| | ratio | 0.379 | |
| 88.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 66 | | matches | | 0 | "Aurora Carter, known to her" | | 1 | "The dimly lit bar in" | | 2 | "She sidled up to the" | | 3 | "A grey-streaked auburn head turned" | | 4 | "The barkeep, Silas Blackwood, a" | | 5 | "The walls were covered with" | | 6 | "Groups of patrons huddled at" | | 7 | "Silas said, placing the glass" | | 8 | "She took a generous swig" | | 9 | "The whiskey burned all the" | | 10 | "A man stumbled inside, blinking" | | 11 | "Rory nearly spat out her" | | 12 | "It couldn't be." | | 13 | "The one who made her" | | 14 | "The one she fled in" | | 15 | "He looked different, though." | | 16 | "The arrogant swagger was gone." | | 17 | "His eyes met hers and" | | 18 | "He sounded uncertain" | | 19 | "She gripped her glass tightly." |
| | ratio | 0.742 | |
| 75.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 66 | | matches | | | ratio | 0.015 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 1 | | matches | | 0 | "He reached out, tucked a strand of hair behind her ear with a familiar tenderness that made her breath catch." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "He looked, his voice heavy" |
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| 75.93% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "he whispered hoarsely (whisper)" | | 1 | "he whispered raggedly (whisper)" |
| | dialogueSentences | 27 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0.333 | | effectiveRatio | 0.148 | |