| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.61% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 677 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 18.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 677 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "scanning" | | 1 | "glinting" | | 2 | "perfect" | | 3 | "etched" | | 4 | "whisper" | | 5 | "silence" | | 6 | "echoed" | | 7 | "trembled" | | 8 | "flickered" | | 9 | "pulse" |
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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 | 1 | | narrationSentences | 42 | | matches | | |
| 6.80% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 42 | | filterMatches | | | hedgeMatches | | 0 | "happened to" | | 1 | "begin to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 57 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 680 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 17.15% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 414 | | uniqueNames | 8 | | maxNameDensity | 2.66 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Eva | 8 | | Kowalski | 1 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Eva" | | 3 | "Kowalski" | | 4 | "Morris" |
| | places | (empty) | | globalScore | 0.171 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | 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 | 680 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 62.64% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 30.91 | | std | 11.41 | | cv | 0.369 | | sampleLengths | | 0 | 44 | | 1 | 33 | | 2 | 31 | | 3 | 23 | | 4 | 51 | | 5 | 18 | | 6 | 23 | | 7 | 40 | | 8 | 42 | | 9 | 11 | | 10 | 32 | | 11 | 45 | | 12 | 36 | | 13 | 24 | | 14 | 19 | | 15 | 33 | | 16 | 53 | | 17 | 29 | | 18 | 25 | | 19 | 10 | | 20 | 30 | | 21 | 28 |
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| 96.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 42 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 63 | | matches | (empty) | |
| 92.73% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 57 | | ratio | 0.018 | | matches | | 0 | "Beneath decades of grime, faint lines emerged - the same concentric circles as the blood pattern, etched into the tile." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 414 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 6 | | adverbRatio | 0.014492753623188406 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.00966183574879227 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 57 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 57 | | mean | 11.93 | | std | 5.12 | | cv | 0.429 | | sampleLengths | | 0 | 13 | | 1 | 15 | | 2 | 10 | | 3 | 6 | | 4 | 21 | | 5 | 12 | | 6 | 16 | | 7 | 5 | | 8 | 4 | | 9 | 6 | | 10 | 14 | | 11 | 9 | | 12 | 16 | | 13 | 12 | | 14 | 23 | | 15 | 3 | | 16 | 15 | | 17 | 12 | | 18 | 11 | | 19 | 16 | | 20 | 12 | | 21 | 6 | | 22 | 6 | | 23 | 15 | | 24 | 14 | | 25 | 13 | | 26 | 8 | | 27 | 3 | | 28 | 12 | | 29 | 20 | | 30 | 11 | | 31 | 13 | | 32 | 5 | | 33 | 6 | | 34 | 6 | | 35 | 4 | | 36 | 16 | | 37 | 20 | | 38 | 6 | | 39 | 18 | | 40 | 19 | | 41 | 14 | | 42 | 19 | | 43 | 9 | | 44 | 19 | | 45 | 15 | | 46 | 10 | | 47 | 13 | | 48 | 16 | | 49 | 13 |
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| 96.49% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.631578947368421 | | totalSentences | 57 | | uniqueOpeners | 36 | |
| 79.37% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 42 | | matches | | 0 | "Too deliberate, too artful." |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 3 | | totalSentences | 42 | | matches | | 0 | "She stood, scanning the platform" | | 1 | "Its face was etched with" | | 2 | "She thought of Morris, of" |
| | ratio | 0.071 | |
| 55.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 34 | | totalSentences | 42 | | matches | | 0 | "Detective Harlow Quinn crouched beside" | | 1 | "The abandoned Tube platform stretched" | | 2 | "The forensics tech gestured to" | | 3 | "Quinn's fingers brushed her worn" | | 4 | "The blood pattern was wrong." | | 5 | "She stood, scanning the platform" | | 6 | "Eva Kowalski emerged from behind" | | 7 | "The museum researcher tucked a" | | 8 | "Quinn's jaw tightened." | | 9 | "Eva clutched her leather satchel" | | 10 | "Quinn paced the platform edge," | | 11 | "The victim's blood formed perfect" | | 12 | "Eva pulled a small brass" | | 13 | "Its face was etched with" | | 14 | "The needle spun wildly before" | | 15 | "Quinn's hand instinctively moved to" | | 16 | "Eva held the compass flat" | | 17 | "Quinn barked out a laugh," | | 18 | "The scene before her brought" | | 19 | "Morris's face, contorted in terror." |
| | ratio | 0.81 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 42 | | matches | | | ratio | 0.024 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 16 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva Kowalski emerged, her round glasses glinting in the spotlights" | | 1 | "Quinn paced, boots crunching on broken glass" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 28 | | tagDensity | 0.036 | | leniency | 0.071 | | rawRatio | 1 | | effectiveRatio | 0.071 | |