| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 81.62% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1360 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "really" | | 3 | "slowly" |
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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) | |
| 26.47% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1360 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "stark" | | 1 | "weight" | | 2 | "scanning" | | 3 | "glint" | | 4 | "charged" | | 5 | "scanned" | | 6 | "tension" | | 7 | "silence" | | 8 | "familiar" | | 9 | "sentinel" | | 10 | "etched" | | 11 | "desire" | | 12 | "flickered" | | 13 | "warmth" | | 14 | "chill" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "air was thick with" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
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| | highlights | | 0 | "the air was thick with" | | 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 | 133 | | matches | (empty) | |
| 99.89% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 1 | | narrationSentences | 133 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 133 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1360 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 7 | | matches | | 0 | "I thought you were in London, he said, his voice cracking slightly." | | 1 | "I am in London, Aurora said." | | 2 | "You look different, Nathaniel said." | | 3 | "I heard about Evan, Nathaniel said softly." | | 4 | "On the house, Silas said." | | 5 | "Old ghosts, he said quietly." | | 6 | "Thank you, she said." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 57 | | wordCount | 1360 | | uniqueNames | 20 | | maxNameDensity | 0.88 | | worstName | "Nathaniel" | | maxWindowNameDensity | 2 | | worstWindowName | "Nathaniel" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Berlin | 1 | | Wall | 1 | | Golden | 1 | | Empress | 1 | | Cardiff | 3 | | Nathaniel | 12 | | Pre-Law | 1 | | Aurora | 11 | | Evan | 2 | | Supreme | 1 | | Court | 1 | | London | 2 | | Silas | 9 | | Rory | 2 | | Nath | 1 | | You | 4 |
| | persons | | 0 | "Carter" | | 1 | "Wall" | | 2 | "Nathaniel" | | 3 | "Aurora" | | 4 | "Evan" | | 5 | "Silas" | | 6 | "Rory" | | 7 | "You" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Berlin" | | 3 | "Cardiff" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 92.53% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like it had seen too much and said" | | 1 | "tasted like regret" |
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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 | 1360 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 133 | | matches | | 0 | "learned that tone" | | 1 | "reversed, that they" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 31.63 | | std | 32.66 | | cv | 1.033 | | sampleLengths | | 0 | 132 | | 1 | 99 | | 2 | 78 | | 3 | 46 | | 4 | 1 | | 5 | 59 | | 6 | 41 | | 7 | 20 | | 8 | 21 | | 9 | 68 | | 10 | 5 | | 11 | 3 | | 12 | 13 | | 13 | 7 | | 14 | 26 | | 15 | 4 | | 16 | 98 | | 17 | 7 | | 18 | 13 | | 19 | 10 | | 20 | 63 | | 21 | 13 | | 22 | 56 | | 23 | 9 | | 24 | 2 | | 25 | 24 | | 26 | 20 | | 27 | 83 | | 28 | 4 | | 29 | 31 | | 30 | 26 | | 31 | 6 | | 32 | 3 | | 33 | 40 | | 34 | 41 | | 35 | 5 | | 36 | 8 | | 37 | 66 | | 38 | 4 | | 39 | 3 | | 40 | 3 | | 41 | 15 | | 42 | 84 |
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| 92.07% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 133 | | matches | | 0 | "was permitted" | | 1 | "was gone" | | 2 | "been replaced" | | 3 | "was frayed" | | 4 | "were uncrossed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 251 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 133 | | ratio | 0.008 | | matches | | 0 | "The past was never just a visitor; it was a tenant that never paid rent." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1366 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 36 | | adverbRatio | 0.02635431918008785 | | lyAdverbCount | 12 | | lyAdverbRatio | 0.008784773060029283 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 133 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 133 | | mean | 10.23 | | std | 7.78 | | cv | 0.761 | | sampleLengths | | 0 | 23 | | 1 | 24 | | 2 | 29 | | 3 | 25 | | 4 | 31 | | 5 | 23 | | 6 | 19 | | 7 | 19 | | 8 | 10 | | 9 | 28 | | 10 | 24 | | 11 | 8 | | 12 | 17 | | 13 | 3 | | 14 | 5 | | 15 | 21 | | 16 | 6 | | 17 | 19 | | 18 | 8 | | 19 | 13 | | 20 | 1 | | 21 | 7 | | 22 | 8 | | 23 | 3 | | 24 | 2 | | 25 | 18 | | 26 | 21 | | 27 | 3 | | 28 | 17 | | 29 | 21 | | 30 | 12 | | 31 | 8 | | 32 | 6 | | 33 | 5 | | 34 | 7 | | 35 | 2 | | 36 | 1 | | 37 | 1 | | 38 | 9 | | 39 | 3 | | 40 | 14 | | 41 | 26 | | 42 | 15 | | 43 | 5 | | 44 | 3 | | 45 | 6 | | 46 | 7 | | 47 | 7 | | 48 | 13 | | 49 | 5 |
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| 30.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 26 | | diversityRatio | 0.2706766917293233 | | totalSentences | 133 | | uniqueOpeners | 36 | |
| 28.25% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 118 | | matches | | 0 | "Then his eyes locked onto" |
| | ratio | 0.008 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 69 | | totalSentences | 118 | | matches | | 0 | "She wore the yellow and" | | 1 | "It was a uniform of" | | 2 | "He wiped a tumbler with" | | 3 | "He wore his silver signet" | | 4 | "He caught her eye and" | | 5 | "She was safe here, in" | | 6 | "He was older than she" | | 7 | "It was Nathaniel." | | 8 | "He didn't see her at" | | 9 | "He scanned the room, his" | | 10 | "His face went slack, the" | | 11 | "She didn't smile." | | 12 | "She walked toward him, her" | | 13 | "He reached out a hand," | | 14 | "He looked at the apron," | | 15 | "I thought you were in" | | 16 | "I thought you were making" | | 17 | "I am in London, Aurora" | | 18 | "Her voice was steady, cool." | | 19 | "She had learned that tone" |
| | ratio | 0.585 | |
| 40.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 118 | | matches | | 0 | "The neon sign above the" | | 1 | "Aurora Carter sat at the" | | 2 | "She wore the yellow and" | | 3 | "It was a uniform of" | | 4 | "Silas moved behind the bar" | | 5 | "He wiped a tumbler with" | | 6 | "He wore his silver signet" | | 7 | "He caught her eye and" | | 8 | "She was safe here, in" | | 9 | "The bell above the door" | | 10 | "A man stepped in, shaking" | | 11 | "He was older than she" | | 12 | "It was Nathaniel." | | 13 | "Nathaniel from the Pre-Law society." | | 14 | "Nathaniel who had argued the" | | 15 | "He didn't see her at" | | 16 | "He scanned the room, his" | | 17 | "His face went slack, the" | | 18 | "The name felt foreign in" | | 19 | "Aurora stood, her chair scraping" |
| | ratio | 0.839 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 118 | | matches | | 0 | "Now, Aurora was standing on" | | 1 | "if you want to catch" | | 2 | "To the present." | | 3 | "To the present." |
| | ratio | 0.034 | |
| 25.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 9 | | matches | | 0 | "Aurora Carter sat at the corner table, the one tucked beneath a faded map of the Berlin Wall, nursing a glass of water that had long since gone flat." | | 1 | "She was safe here, in his territory, but tonight the air felt charged, heavy with a static that had nothing to do with the storm battering the windows." | | 2 | "Nathaniel who had argued the merits of tort law over cheap pints while Aurora had been planning her escape from Evan." | | 3 | "He scanned the room, his gaze drifting over the black-and-white photographs of spies and smugglers that lined the walls." | | 4 | "The bright blue of her eyes seemed to widen, reflecting the green neon that filtered through the haze." | | 5 | "She walked toward him, her movements fluid, but there was a tension in her shoulders that hadn't been there in Cardiff." | | 6 | "The older man leaned against the counter, his grey-streaked auburn beard framing a face that looked like it had seen too much and said too little." | | 7 | "She felt the familiar weight of the small crescent-shaped scar on her left wrist, the souvenir of a childhood accident that had taught her early on that skin he…" | | 8 | "She took a sip, letting the warmth spread through her chest, pushing back the chill that had settled there when the door closed." |
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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 | |