| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1199 | | 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) | |
| 45.79% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1199 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "fractured" | | 1 | "footsteps" | | 2 | "echoes" | | 3 | "flickered" | | 4 | "echoing" | | 5 | "etched" | | 6 | "shimmered" | | 7 | "weight" | | 8 | "scanned" | | 9 | "gleaming" |
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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 | 61 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 61 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 71 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1196 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 85.62% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 932 | | uniqueNames | 16 | | maxNameDensity | 1.29 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Tomás" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 12 | | Herrera | 1 | | Camden | 1 | | Saint | 1 | | Christopher | 1 | | Raven | 2 | | Nest | 2 | | Morris | 2 | | Tomás | 12 | | Tube | 2 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Raven" | | 6 | "Nest" | | 7 | "Morris" | | 8 | "Tomás" | | 9 | "Market" | | 10 | "Police" |
| | places | | | globalScore | 0.856 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 1 | | matches | | 0 | "as if sharing a secret amid the din" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1196 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 71 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 47.84 | | std | 31.39 | | cv | 0.656 | | sampleLengths | | 0 | 78 | | 1 | 63 | | 2 | 17 | | 3 | 79 | | 4 | 118 | | 5 | 34 | | 6 | 71 | | 7 | 113 | | 8 | 107 | | 9 | 28 | | 10 | 22 | | 11 | 23 | | 12 | 23 | | 13 | 26 | | 14 | 54 | | 15 | 23 | | 16 | 40 | | 17 | 30 | | 18 | 45 | | 19 | 80 | | 20 | 36 | | 21 | 11 | | 22 | 33 | | 23 | 12 | | 24 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 61 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 164 | | matches | (empty) | |
| 22.13% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 71 | | ratio | 0.042 | | matches | | 0 | "She had tracked him from that dimly lit bar with the distinctive green neon sign—The Raven's Nest, locals called it—after overhearing fragments about a supplier who dealt in things no one admitted existed." | | 1 | "This was the Veil Market, shifting locations every full moon, accessible only with the right token—like the bone chip Tomás now palmed from his pocket to the gatekeeper's hand." | | 2 | "The underground market hummed with activity—dealers demonstrating potions that burned cold when uncorked, whispers about artifacts that bent reality." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 938 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.028784648187633263 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005330490405117271 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 71 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 71 | | mean | 16.85 | | std | 8.4 | | cv | 0.499 | | sampleLengths | | 0 | 19 | | 1 | 27 | | 2 | 13 | | 3 | 19 | | 4 | 30 | | 5 | 27 | | 6 | 6 | | 7 | 17 | | 8 | 21 | | 9 | 14 | | 10 | 11 | | 11 | 18 | | 12 | 15 | | 13 | 5 | | 14 | 15 | | 15 | 18 | | 16 | 21 | | 17 | 33 | | 18 | 26 | | 19 | 16 | | 20 | 18 | | 21 | 3 | | 22 | 13 | | 23 | 8 | | 24 | 18 | | 25 | 29 | | 26 | 23 | | 27 | 14 | | 28 | 11 | | 29 | 21 | | 30 | 20 | | 31 | 11 | | 32 | 13 | | 33 | 10 | | 34 | 22 | | 35 | 11 | | 36 | 15 | | 37 | 21 | | 38 | 28 | | 39 | 12 | | 40 | 16 | | 41 | 22 | | 42 | 17 | | 43 | 6 | | 44 | 23 | | 45 | 4 | | 46 | 22 | | 47 | 14 | | 48 | 40 | | 49 | 13 |
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| 53.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3380281690140845 | | totalSentences | 71 | | uniqueOpeners | 24 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 61 | | matches | (empty) | | ratio | 0 | |
| 82.30% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 61 | | matches | | 0 | "She lengthened her pace, heart" | | 1 | "Her voice cut through the" | | 2 | "He glanced over his shoulder," | | 3 | "She followed, boots hitting a" | | 4 | "She had tracked him from" | | 5 | "Her missing partner, DS Morris," | | 6 | "she called ahead, voice echoing" | | 7 | "He shoulder-checked a heavy metal" | | 8 | "She had suspected the clique" | | 9 | "He paused at a stall" | | 10 | "Her brown eyes scanned every" | | 11 | "She pressed on, the decision" | | 12 | "She closed on Tomás near" | | 13 | "He reached for a small" | | 14 | "Her response came clipped." | | 15 | "He shook his head, raindrops" | | 16 | "Her voice dropped low, carrying" | | 17 | "His olive skin glistened under" | | 18 | "He hesitated, then leaned in" | | 19 | "She weighed his words against" |
| | ratio | 0.344 | |
| 0.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 61 | | matches | | 0 | "Detective Harlow Quinn sprinted through" | | 1 | "The suspect ahead veered around" | | 2 | "She lengthened her pace, heart" | | 3 | "Tomás Herrera had ducked into" | | 4 | "Quinn closed the gap, lungs" | | 5 | "Her voice cut through the" | | 6 | "He glanced over his shoulder," | | 7 | "Quinn followed without hesitation, the" | | 8 | "The alley dropped into darkness" | | 9 | "Tomás wrenched the grate aside" | | 10 | "She followed, boots hitting a" | | 11 | "The descent swallowed her whole." | | 12 | "Tomás moved fast, his Saint" | | 13 | "Quinn's sharp jaw set tight" | | 14 | "She had tracked him from" | | 15 | "Her missing partner, DS Morris," | | 16 | "she called ahead, voice echoing" | | 17 | "Tomás didn't slow." | | 18 | "He shoulder-checked a heavy metal" | | 19 | "Quinn burst through seconds later" |
| | ratio | 0.918 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 61 | | matches | | 0 | "If she retreated, evidence stayed" | | 1 | "If she advanced, the dangers" |
| | ratio | 0.033 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 6 | | matches | | 0 | "Rain hammered the pavements of Soho, turning the streets into slick mirrors that reflected the fractured glow of streetlamps." | | 1 | "She lengthened her pace, heart hammering against her ribs in a rhythm that matched the slap of her shoes." | | 2 | "She had tracked him from that dimly lit bar with the distinctive green neon sign—The Raven's Nest, locals called it—after overhearing fragments about a supplier…" | | 3 | "He shoulder-checked a heavy metal door that groaned open into a vast chamber." | | 4 | "A vendor with scales for eyes bartered alchemical powders that shimmered under the lights." | | 5 | "She had suspected the clique tied to Tomás for months, whispers of supernatural dealings that explained too many open cases." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "she called, voice echoing hard against the walls" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.083 | | leniency | 0.167 | | rawRatio | 0 | | effectiveRatio | 0 | |