| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 60.78% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 255 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 255 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "silence" | | 2 | "quickened" | | 3 | "glint" | | 4 | "navigate" | | 5 | "echoed" | | 6 | "weight" | | 7 | "familiar" |
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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 | 25 | | matches | (empty) | |
| 85.71% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 25 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 25 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 22 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 252 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 69.68% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 8 | | wordCount | 249 | | uniqueNames | 5 | | maxNameDensity | 1.61 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 4 | | Soho | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.697 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 17 | | 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 | 252 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 25 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 11 | | mean | 22.91 | | std | 14.36 | | cv | 0.627 | | sampleLengths | | 0 | 35 | | 1 | 48 | | 2 | 11 | | 3 | 9 | | 4 | 33 | | 5 | 38 | | 6 | 34 | | 7 | 9 | | 8 | 3 | | 9 | 19 | | 10 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 25 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 39 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 25 | | ratio | 0.08 | | matches | | 0 | "The suspect—a lean figure in a dark overcoat—darted between parked cars, his movements fluid and desperate." | | 1 | "Her mind flashed to DS Morris—her former partner who'd vanished three years ago under circumstances that still haunted her investigative dreams." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 252 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.027777777777777776 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.015873015873015872 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 25 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 25 | | mean | 10.08 | | std | 6.23 | | cv | 0.618 | | sampleLengths | | 0 | 17 | | 1 | 18 | | 2 | 16 | | 3 | 16 | | 4 | 16 | | 5 | 11 | | 6 | 4 | | 7 | 5 | | 8 | 9 | | 9 | 16 | | 10 | 8 | | 11 | 3 | | 12 | 21 | | 13 | 14 | | 14 | 2 | | 15 | 11 | | 16 | 21 | | 17 | 7 | | 18 | 1 | | 19 | 1 | | 20 | 3 | | 21 | 6 | | 22 | 13 | | 23 | 8 | | 24 | 5 |
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| 96.00% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.6 | | totalSentences | 25 | | uniqueOpeners | 15 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 22 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 5 | | totalSentences | 22 | | matches | | 0 | "Her boots slammed against the" | | 1 | "Her command sliced through the" | | 2 | "He ducked suddenly, sliding beneath" | | 3 | "Her mind flashed to DS" | | 4 | "Her hand instinctively checked her" |
| | ratio | 0.227 | |
| 50.91% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 18 | | totalSentences | 22 | | matches | | 0 | "The rain pelted Detective Harlow" | | 1 | "Her boots slammed against the" | | 2 | "The suspect—a lean figure in" | | 3 | "Quinn's breath came in sharp" | | 4 | "Her command sliced through the" | | 5 | "The suspect didn't slow." | | 6 | "He ducked suddenly, sliding beneath" | | 7 | "Quinn vaulted over it in" | | 8 | "Water sprayed around her feet" | | 9 | "Camden's underground beckoned." | | 10 | "Subway maintenance tunnels twisted beneath" | | 11 | "The suspect's silhouette dissolved into" | | 12 | "Her mind flashed to DS" | | 13 | "The sounds of movement echoed" | | 14 | "Something wasn't right." | | 15 | "Her hand instinctively checked her" | | 16 | "The weight of her service" | | 17 | "The maintenance door dripped with" |
| | ratio | 0.818 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 22 | | matches | | 0 | "If anything, his pace quickened." |
| | ratio | 0.045 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 11 | | technicalSentenceCount | 1 | | matches | | 0 | "Her mind flashed to DS Morris—her former partner who'd vanished three years ago under circumstances that still haunted her investigative dreams." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |