| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 434 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 42.40% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 434 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "treacherous" | | 1 | "gleaming" | | 2 | "glint" | | 3 | "navigating" | | 4 | "flickered" |
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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 | 34 | | matches | (empty) | |
| 58.82% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 34 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 34 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 428 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 68.22% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 428 | | uniqueNames | 12 | | maxNameDensity | 1.64 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 7 | | Soho | 1 | | Herrera | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 6 | | Morris | 2 | | Veil | 1 | | Market | 1 | | Protocol | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Tomás" | | 6 | "Morris" | | 7 | "Protocol" |
| | places | | | globalScore | 0.682 | | windowScore | 1 | |
| 53.85% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 26 | | glossingSentenceCount | 1 | | matches | | 0 | "tunnels that seemed to breathe with an ancient, musty air" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 2.336 | | wordCount | 428 | | matches | | 0 | "no longer running scared but" |
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| 68.63% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 34 | | matches | | |
| 83.93% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 13 | | mean | 32.92 | | std | 14.61 | | cv | 0.444 | | sampleLengths | | 0 | 41 | | 1 | 49 | | 2 | 6 | | 3 | 39 | | 4 | 37 | | 5 | 41 | | 6 | 47 | | 7 | 54 | | 8 | 38 | | 9 | 28 | | 10 | 18 | | 11 | 10 | | 12 | 20 |
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| 63.98% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 34 | | matches | | 0 | "was plastered" | | 1 | "was connected" | | 2 | "were bought" | | 3 | "was connected" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 65 | | matches | | 0 | "was running" | | 1 | "wasn't losing" | | 2 | "was screaming" | | 3 | "was going" | | 4 | "was happening" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 34 | | ratio | 0.118 | | matches | | 0 | "Something about Tomás—about the entire clique he ran with—felt wrong." | | 1 | "At the bottom of the stairs, a distinctive green neon sign flickered—barely visible, a ghost of illumination." | | 2 | "Tomás pulled a small bone token from his pocket—some kind of entry pass—and slipped through a hidden doorway." | | 3 | "Quinn took a breath, tasted damp stone and something else—something metallic and strange." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 437 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 9 | | adverbRatio | 0.020594965675057208 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006864988558352402 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 34 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 34 | | mean | 12.59 | | std | 7 | | cv | 0.556 | | sampleLengths | | 0 | 15 | | 1 | 26 | | 2 | 12 | | 3 | 15 | | 4 | 22 | | 5 | 4 | | 6 | 2 | | 7 | 14 | | 8 | 13 | | 9 | 10 | | 10 | 2 | | 11 | 21 | | 12 | 14 | | 13 | 2 | | 14 | 24 | | 15 | 17 | | 16 | 23 | | 17 | 24 | | 18 | 17 | | 19 | 3 | | 20 | 16 | | 21 | 18 | | 22 | 18 | | 23 | 2 | | 24 | 7 | | 25 | 11 | | 26 | 15 | | 27 | 13 | | 28 | 8 | | 29 | 5 | | 30 | 5 | | 31 | 10 | | 32 | 13 | | 33 | 7 |
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| 92.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5882352941176471 | | totalSentences | 34 | | uniqueOpeners | 20 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 30 | | matches | | 0 | "Then she followed Tomás into" |
| | ratio | 0.033 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 4 | | totalSentences | 30 | | matches | | 0 | "He darted left, cutting between" | | 1 | "Her salt-and-pepper hair was plastered" | | 2 | "He scrambled down a set" | | 3 | "Her hand touched the holster" |
| | ratio | 0.133 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 21 | | totalSentences | 30 | | matches | | 0 | "The rain sliced down in" | | 1 | "Detective Harlow Quinn's boots slapped" | | 2 | "Tomás Herrera was running hard," | | 3 | "The Saint Christopher medallion bounced" | | 4 | "He darted left, cutting between" | | 5 | "Quinn wasn't losing him." | | 6 | "Her salt-and-pepper hair was plastered" | | 7 | "Something about Tomás—about the entire" | | 8 | "He scrambled down a set" | | 9 | "Quinn was right behind him," | | 10 | "The stairs spiraled down, away" | | 11 | "Tomás was moving with purpose" | | 12 | "The Veil Market." | | 13 | "Quinn had heard whispers about" | | 14 | "An underground market where things" | | 15 | "Tomás pulled a small bone" | | 16 | "Her hand touched the holster" | | 17 | "Protocol said wait for backup." | | 18 | "Protocol said assess the situation." | | 19 | "Protocol had never solved the" |
| | ratio | 0.7 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 30 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 1 | | matches | | 0 | "The stairs spiraled down, away from the rain-slicked streets, into a network of tunnels that seemed to breathe with an ancient, musty air." |
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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 | |