| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 432 | | 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) | |
| 18.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 432 | | totalAiIsms | 7 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "down her spine" | | count | 1 |
| | 5 | | | 6 | |
| | highlights | | 0 | "pulsed" | | 1 | "weight" | | 2 | "familiar" | | 3 | "chill" | | 4 | "down her spine" | | 5 | "silence" | | 6 | "pulse" |
| |
| 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 | "sent a shiver through" | | count | 1 |
|
| | highlights | | 0 | "The air was thick with" | | 1 | "sent a chill down" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 31 | | matches | (empty) | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 31 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 35 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 429 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.03% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 397 | | uniqueNames | 7 | | maxNameDensity | 1.26 | | worstName | "Tomás" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Harlow | 1 | | Quinn | 4 | | Tomás | 5 | | Herrera | 1 | | Soho | 1 |
| | persons | | 0 | "Raven" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Tomás" | | 4 | "Herrera" |
| | places | | | globalScore | 0.87 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 23 | | 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 | 429 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 35 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 28.6 | | std | 26.88 | | cv | 0.94 | | sampleLengths | | 0 | 81 | | 1 | 96 | | 2 | 10 | | 3 | 32 | | 4 | 7 | | 5 | 8 | | 6 | 20 | | 7 | 23 | | 8 | 13 | | 9 | 36 | | 10 | 18 | | 11 | 5 | | 12 | 54 | | 13 | 6 | | 14 | 20 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 31 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 61 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 35 | | ratio | 0.086 | | matches | | 0 | "The air was thick with the stink of damp and something sharper—burnt oil, maybe, or the metallic tang of blood." | | 1 | "Tomás had been slipping something into her bag earlier, something she couldn’t put her finger on, but the way he’d looked at her—like she was already compromised—had sent a chill down her spine." | | 2 | "Tomás was already moving, his scarred hand flashing—" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 400 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.035 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0025 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 35 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 35 | | mean | 12.26 | | std | 8.44 | | cv | 0.689 | | sampleLengths | | 0 | 29 | | 1 | 25 | | 2 | 27 | | 3 | 22 | | 4 | 20 | | 5 | 21 | | 6 | 33 | | 7 | 10 | | 8 | 23 | | 9 | 9 | | 10 | 7 | | 11 | 5 | | 12 | 3 | | 13 | 8 | | 14 | 12 | | 15 | 3 | | 16 | 11 | | 17 | 9 | | 18 | 4 | | 19 | 9 | | 20 | 3 | | 21 | 7 | | 22 | 26 | | 23 | 12 | | 24 | 6 | | 25 | 3 | | 26 | 2 | | 27 | 10 | | 28 | 12 | | 29 | 13 | | 30 | 11 | | 31 | 8 | | 32 | 6 | | 33 | 16 | | 34 | 4 |
| |
| 54.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.34285714285714286 | | totalSentences | 35 | | uniqueOpeners | 12 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 30 | | matches | | 0 | "Then she heard it: the" | | 1 | "Instead, she stepped closer, her" | | 2 | "Then, the scrape of a" | | 3 | "Instead, she twisted, her gun" |
| | ratio | 0.133 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 8 | | totalSentences | 30 | | matches | | 0 | "She stepped into the alley," | | 1 | "Her breath fogged in the" | | 2 | "He turned, his warm brown" | | 3 | "he said, not a question" | | 4 | "She didn’t answer." | | 5 | "She could hear the distant" | | 6 | "She stumbled, her grip slipping" | | 7 | "She thrashed, her fingers clawing" |
| | ratio | 0.267 | |
| 26.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 26 | | totalSentences | 30 | | matches | | 0 | "The neon glow of the" | | 1 | "Detective Harlow Quinn adjusted the" | | 2 | "The man had vanished into" | | 3 | "She stepped into the alley," | | 4 | "The air was thick with" | | 5 | "Her breath fogged in the" | | 6 | "Tomás had been slipping something" | | 7 | "A shadow detached itself from" | | 8 | "He turned, his warm brown" | | 9 | "he said, not a question" | | 10 | "Quinn didn’t lower her gun." | | 11 | "Tomás smirked, the movement too" | | 12 | "She didn’t answer." | | 13 | "A beat of silence." | | 14 | "Quinn’s pulse jumped." | | 15 | "The alley narrowed, the walls" | | 16 | "She could hear the distant" | | 17 | "Tomás turned, his hand already" | | 18 | "Quinn didn’t hesitate." | | 19 | "The moment her boot hit" |
| | ratio | 0.867 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 30 | | matches | (empty) | | ratio | 0 | |
| 16.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 17 | | technicalSentenceCount | 3 | | matches | | 0 | "The neon glow of the Raven’s Nest pulsed like a dying heartbeat against the storm-wracked sky, its green sign flickering as if the rain itself argued with the e…" | | 1 | "Detective Harlow Quinn adjusted the strap of her bag, the leather watch on her wrist ticking away the seconds she’d spent tracking Tomás Herrera down." | | 2 | "She stepped into the alley, her boots sinking into the mud, the scent of damp stone and old wood filling her lungs." |
| |
| 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 | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |