| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 75.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1230 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slightly" | | 1 | "tightly" | | 2 | "slowly" | | 3 | "really" | | 4 | "softly" | | 5 | "suddenly" |
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| 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) | |
| 51.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1230 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "familiar" | | 1 | "rhythmic" | | 2 | "traced" | | 3 | "clenching" | | 4 | "silence" | | 5 | "navigate" | | 6 | "fleeting" | | 7 | "chill" | | 8 | "weight" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "knuckles turned white" | | 1 | "hung in the air" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 102 | | matches | (empty) | |
| 72.83% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 2 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 102 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1223 | | ratio | 0.001 | | matches | | |
| 17.86% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 3 | | matches | | 0 | "Aurora, he said, his voice dropping an octave." | | 1 | "You think it was about him, she said softly." | | 2 | "I suppose I expected a different welcome, he whispered." |
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| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 60 | | wordCount | 1223 | | uniqueNames | 16 | | maxNameDensity | 1.06 | | worstName | "You" | | maxWindowNameDensity | 4.5 | | worstWindowName | "You" | | discoveredNames | | Raven | 2 | | Nest | 2 | | Soho | 2 | | Tuesday | 1 | | Cardiff | 3 | | London | 2 | | Aurora | 11 | | English | 1 | | Carter | 1 | | Silas | 6 | | Dad | 4 | | Evan | 2 | | Rory | 3 | | Mayfair | 1 | | Brendan | 6 | | You | 13 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Carter" | | 4 | "Silas" | | 5 | "Evan" | | 6 | "Rory" | | 7 | "Brendan" | | 8 | "You" |
| | places | | 0 | "Soho" | | 1 | "Cardiff" | | 2 | "London" | | 3 | "Mayfair" |
| | globalScore | 0.969 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 79 | | glossingSentenceCount | 1 | | matches | | 0 | "sound that seemed to deflate his entire presence" |
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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 | 1223 | | matches | (empty) | |
| 68.63% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 102 | | matches | | 0 | "knew that cadence" | | 1 | "that girl" | | 2 | "decided that reputation" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 39.45 | | std | 20.39 | | cv | 0.517 | | sampleLengths | | 0 | 70 | | 1 | 71 | | 2 | 68 | | 3 | 52 | | 4 | 1 | | 5 | 43 | | 6 | 44 | | 7 | 1 | | 8 | 19 | | 9 | 51 | | 10 | 35 | | 11 | 41 | | 12 | 40 | | 13 | 27 | | 14 | 37 | | 15 | 65 | | 16 | 38 | | 17 | 19 | | 18 | 52 | | 19 | 26 | | 20 | 43 | | 21 | 58 | | 22 | 9 | | 23 | 50 | | 24 | 44 | | 25 | 45 | | 26 | 20 | | 27 | 30 | | 28 | 10 | | 29 | 30 | | 30 | 84 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 102 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 222 | | matches | | 0 | "weren't looking" | | 1 | "were looking" |
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| 30.81% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 102 | | ratio | 0.039 | | matches | | 0 | "He didn't offer a greeting, just a slow, recognizing nod, his right hand—adorned with the heavy silver signet ring—resting on a stack of damp coasters." | | 1 | "He looked at her—really looked at her—and the disappointment was a heavy, suffocating thing." | | 2 | "The charges, the pressure—everything fell apart after you left." | | 3 | "If you want to talk—properly—you know where to find me." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1232 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 30 | | adverbRatio | 0.024350649350649352 | | lyAdverbCount | 18 | | lyAdverbRatio | 0.01461038961038961 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 102 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 102 | | mean | 11.99 | | std | 7.88 | | cv | 0.657 | | sampleLengths | | 0 | 27 | | 1 | 19 | | 2 | 24 | | 3 | 12 | | 4 | 25 | | 5 | 34 | | 6 | 22 | | 7 | 18 | | 8 | 28 | | 9 | 18 | | 10 | 10 | | 11 | 13 | | 12 | 11 | | 13 | 1 | | 14 | 8 | | 15 | 14 | | 16 | 4 | | 17 | 17 | | 18 | 6 | | 19 | 10 | | 20 | 28 | | 21 | 1 | | 22 | 19 | | 23 | 6 | | 24 | 45 | | 25 | 8 | | 26 | 7 | | 27 | 2 | | 28 | 4 | | 29 | 8 | | 30 | 6 | | 31 | 8 | | 32 | 7 | | 33 | 14 | | 34 | 4 | | 35 | 4 | | 36 | 4 | | 37 | 7 | | 38 | 14 | | 39 | 3 | | 40 | 3 | | 41 | 9 | | 42 | 4 | | 43 | 13 | | 44 | 4 | | 45 | 10 | | 46 | 9 | | 47 | 9 | | 48 | 9 | | 49 | 5 |
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| 29.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.2549019607843137 | | totalSentences | 102 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 56 | | totalSentences | 98 | | matches | | 0 | "It was a Tuesday, the" | | 1 | "He didn't offer a greeting," | | 2 | "He shifted, his left leg" | | 3 | "She traced the rim of" | | 4 | "She had been living in" | | 5 | "He looked prosperous, his coat" | | 6 | "He stopped dead when he" | | 7 | "She went rigid, her fingers" | | 8 | "She knew that cadence." | | 9 | "She turned slowly on the" | | 10 | "His hair had thinned, and" | | 11 | "He looked around The Raven's" | | 12 | "I didn't think I’d find" | | 13 | "we’ve spent months looking." | | 14 | "You left quite the vacuum" | | 15 | "She kept the bar as" | | 16 | "I didn't go missing." | | 17 | "I went to ground." | | 18 | "He looked at her—really looked" | | 19 | "You look thin." |
| | ratio | 0.571 | |
| 5.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 98 | | matches | | 0 | "The green neon sign above" | | 1 | "Aurora pushed the heavy door" | | 2 | "It was a Tuesday, the" | | 3 | "Silas looked up, his grey-streaked" | | 4 | "He didn't offer a greeting," | | 5 | "He shifted, his left leg" | | 6 | "Aurora sat on a stool" | | 7 | "She traced the rim of" | | 8 | "She had been living in" | | 9 | "The door groaned again, letting" | | 10 | "A man stepped inside, shaking" | | 11 | "He looked prosperous, his coat" | | 12 | "He stopped dead when he" | | 13 | "The name hit Aurora like" | | 14 | "She went rigid, her fingers" | | 15 | "She knew that cadence." | | 16 | "The clipped, precise English of" | | 17 | "She turned slowly on the" | | 18 | "Brendan Carter stood there, aged" | | 19 | "His hair had thinned, and" |
| | ratio | 0.908 | |
| 51.02% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 98 | | matches | | 0 | "If you want to talk—properly—you" |
| | ratio | 0.01 | |
| 76.72% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 5 | | matches | | 0 | "The clipped, precise English of a man who had spent his life winning small arguments in courtrooms." | | 1 | "His hair had thinned, and there were vertical lines running from his mouth to his chin that hadn’t existed when she had fled her life three years ago." | | 2 | "He looked around The Raven's Nest with a frown, his gaze skimming the dingy wallpaper and the hidden bookshelf in the back, landing finally on Silas, who watche…" | | 3 | "Aurora leaned over the bar, her bright blue eyes searching his, looking for a shimmer of regret that wasn't there." | | 4 | "The silence that followed was heavy with the ticking of an old clock somewhere behind the bar." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |