| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "The man stepped aside [aside]" |
| | dialogueSentences | 30 | | tagDensity | 0.267 | | leniency | 0.533 | | rawRatio | 0.125 | | effectiveRatio | 0.067 | |
| 87.94% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 829 | | 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) | |
| 39.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 829 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "scanning" | | 3 | "gleaming" | | 4 | "familiar" | | 5 | "stomach" | | 6 | "churn" | | 7 | "oppressive" | | 8 | "stark" |
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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 | 63 | | matches | (empty) | |
| 97.51% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 63 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 2 | | totalWords | 824 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 63.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 633 | | uniqueNames | 6 | | maxNameDensity | 1.74 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Shaftesbury | 1 | | Avenue | 1 | | London-ish | 1 | | Quinn | 11 | | Tube | 1 | | London | 2 |
| | persons | | | places | | 0 | "Shaftesbury" | | 1 | "Avenue" | | 2 | "London" |
| | globalScore | 0.631 | | windowScore | 0.667 | |
| 96.81% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 824 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 19.16 | | std | 14.33 | | cv | 0.748 | | sampleLengths | | 0 | 37 | | 1 | 43 | | 2 | 10 | | 3 | 41 | | 4 | 11 | | 5 | 30 | | 6 | 4 | | 7 | 18 | | 8 | 5 | | 9 | 20 | | 10 | 12 | | 11 | 3 | | 12 | 32 | | 13 | 9 | | 14 | 32 | | 15 | 4 | | 16 | 12 | | 17 | 40 | | 18 | 14 | | 19 | 13 | | 20 | 6 | | 21 | 32 | | 22 | 4 | | 23 | 19 | | 24 | 12 | | 25 | 4 | | 26 | 3 | | 27 | 22 | | 28 | 23 | | 29 | 7 | | 30 | 30 | | 31 | 10 | | 32 | 5 | | 33 | 18 | | 34 | 62 | | 35 | 25 | | 36 | 4 | | 37 | 8 | | 38 | 44 | | 39 | 35 | | 40 | 3 | | 41 | 27 | | 42 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 104 | | matches | (empty) | |
| 6.80% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 84 | | ratio | 0.048 | | matches | | 0 | "He moved with that unsettling, fluid grace, the kind you saw in soldiers or addicts—people who didn't care about pain." | | 1 | "But the file on her desk burned a hole in her memory—the missing persons reports that didn't match the coroner's log." | | 2 | "The smell hit her first—a thick, cloying perfume mixed with the metallic tang of dried blood." | | 3 | "Voices drifted from the shadows—hushed negotiations, the clink of glass, the low growl of something predatory." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 638 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.032915360501567396 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0109717868338558 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 9.81 | | std | 6.01 | | cv | 0.613 | | sampleLengths | | 0 | 7 | | 1 | 16 | | 2 | 14 | | 3 | 23 | | 4 | 20 | | 5 | 10 | | 6 | 16 | | 7 | 9 | | 8 | 6 | | 9 | 1 | | 10 | 9 | | 11 | 9 | | 12 | 1 | | 13 | 1 | | 14 | 3 | | 15 | 11 | | 16 | 4 | | 17 | 12 | | 18 | 4 | | 19 | 9 | | 20 | 9 | | 21 | 5 | | 22 | 20 | | 23 | 12 | | 24 | 3 | | 25 | 14 | | 26 | 18 | | 27 | 4 | | 28 | 5 | | 29 | 25 | | 30 | 7 | | 31 | 4 | | 32 | 12 | | 33 | 12 | | 34 | 9 | | 35 | 8 | | 36 | 2 | | 37 | 9 | | 38 | 8 | | 39 | 6 | | 40 | 4 | | 41 | 3 | | 42 | 6 | | 43 | 6 | | 44 | 21 | | 45 | 11 | | 46 | 4 | | 47 | 19 | | 48 | 8 | | 49 | 4 |
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| 62.70% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.44047619047619047 | | totalSentences | 84 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 64.07% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 59 | | matches | | 0 | "Her breath hitched in her" | | 1 | "He moved with that unsettling," | | 2 | "She skidded around the corner," | | 3 | "Her hand connected with damp" | | 4 | "She grunted, rolling into a" | | 5 | "He stood twenty yards away," | | 6 | "He didn't look surprised." | | 7 | "He touched his watch, a" | | 8 | "His voice was smooth, lilting," | | 9 | "He took a step forward," | | 10 | "He sighed, a long, weary" | | 11 | "His hand slowly, almost theatrically," | | 12 | "He tossed it upward" | | 13 | "It spun, catching the dim" | | 14 | "He pointed the token at" | | 15 | "He jerked his head toward" | | 16 | "He laughed, a dry, rasping" | | 17 | "He smiled, revealing yellowed teeth." | | 18 | "Her tactical training screamed at" | | 19 | "He nodded, raising his hands." |
| | ratio | 0.39 | |
| 19.32% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 59 | | matches | | 0 | "Sleet hammered the pavement, stinging" | | 1 | "Quinn sprinted through the neon" | | 2 | "Her breath hitched in her" | | 3 | "He moved with that unsettling," | | 4 | "Quinn shouted, her voice swallowed" | | 5 | "She skidded around the corner," | | 6 | "Her hand connected with damp" | | 7 | "She grunted, rolling into a" | | 8 | "The alley smelled of damp" | | 9 | "Footsteps echoed from the far" | | 10 | "Quinn spun around." | | 11 | "He stood twenty yards away," | | 12 | "He didn't look surprised." | | 13 | "He touched his watch, a" | | 14 | "His voice was smooth, lilting," | | 15 | "He took a step forward," | | 16 | "Quinn narrowed her eyes, scanning" | | 17 | "The man’s face hardened." | | 18 | "Quinn took a step closer," | | 19 | "He sighed, a long, weary" |
| | ratio | 0.881 | |
| 84.75% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 59 | | matches | | | ratio | 0.017 | |
| 80.75% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 2 | | matches | | 0 | "Her breath hitched in her throat, a sharp, rattling gasp that tasted like copper." | | 1 | "He moved with that unsettling, fluid grace, the kind you saw in soldiers or addicts—people who didn't care about pain." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 30 | | tagDensity | 0.033 | | leniency | 0.067 | | rawRatio | 1 | | effectiveRatio | 0.067 | |