| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 921 | | totalAiIsmAdverbs | 3 | | found | | 0 | | adverb | "reluctantly" | | count | 1 |
| | 1 | | | 2 | |
| | highlights | | 0 | "reluctantly" | | 1 | "slightly" | | 2 | "slowly" |
| |
| 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) | |
| 24.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 921 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pulse" | | 1 | "fluttered" | | 2 | "loomed" | | 3 | "echo" | | 4 | "footsteps" | | 5 | "glinting" | | 6 | "tension" | | 7 | "unreadable" | | 8 | "silence" | | 9 | "whisper" | | 10 | "flicked" | | 11 | "roaring" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | 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 | 3 | | totalWords | 910 | | ratio | 0.003 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 841 | | uniqueNames | 11 | | maxNameDensity | 1.66 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Herrera" | | discoveredNames | | Quinn | 14 | | Neal | 1 | | Street | 1 | | Shaftesbury | 1 | | Avenue | 1 | | Raven | 1 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 9 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Market" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Herrera" |
| | places | | 0 | "Neal" | | 1 | "Street" | | 2 | "Shaftesbury" | | 3 | "Avenue" |
| | globalScore | 0.668 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | 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 | 910 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 18.96 | | std | 17.28 | | cv | 0.911 | | sampleLengths | | 0 | 58 | | 1 | 4 | | 2 | 18 | | 3 | 54 | | 4 | 3 | | 5 | 53 | | 6 | 8 | | 7 | 11 | | 8 | 55 | | 9 | 11 | | 10 | 3 | | 11 | 62 | | 12 | 9 | | 13 | 18 | | 14 | 3 | | 15 | 5 | | 16 | 60 | | 17 | 40 | | 18 | 24 | | 19 | 2 | | 20 | 13 | | 21 | 4 | | 22 | 47 | | 23 | 13 | | 24 | 7 | | 25 | 35 | | 26 | 2 | | 27 | 6 | | 28 | 24 | | 29 | 9 | | 30 | 12 | | 31 | 14 | | 32 | 8 | | 33 | 16 | | 34 | 6 | | 35 | 22 | | 36 | 9 | | 37 | 16 | | 38 | 24 | | 39 | 6 | | 40 | 20 | | 41 | 12 | | 42 | 16 | | 43 | 22 | | 44 | 4 | | 45 | 25 | | 46 | 10 | | 47 | 7 |
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| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 92 | | matches | | 0 | "were lined" | | 1 | "was fixed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 143 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 104 | | ratio | 0.077 | | matches | | 0 | "Rain needled her face, turning the neon signs into smears of colour—red, green, blue—all bleeding together in the downpour." | | 1 | "Then she spotted the green neon sign—*The Raven’s Nest*—and the figure darting inside." | | 2 | "The walls were lined with maps—old, yellowed, some with pins stuck in them like warnings." | | 3 | "The cavernous space stretched beneath the city, the air thick with the scent of incense and something sharper—copper, maybe, or ozone." | | 4 | "But the alternative—letting him disappear—was worse." | | 5 | "Then she heard it—the scuffle of boots on stone." | | 6 | "A figure stood over him—a man with a scar running down his forearm and a Saint Christopher medallion glinting at his throat." | | 7 | "But all he pulled out was a bone token—small, carved, strung on a leather cord." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 852 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.036384976525821594 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.009389671361502348 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 8.75 | | std | 6.07 | | cv | 0.694 | | sampleLengths | | 0 | 20 | | 1 | 19 | | 2 | 19 | | 3 | 3 | | 4 | 1 | | 5 | 8 | | 6 | 3 | | 7 | 3 | | 8 | 4 | | 9 | 24 | | 10 | 17 | | 11 | 13 | | 12 | 3 | | 13 | 11 | | 14 | 22 | | 15 | 20 | | 16 | 4 | | 17 | 4 | | 18 | 11 | | 19 | 10 | | 20 | 15 | | 21 | 15 | | 22 | 15 | | 23 | 11 | | 24 | 3 | | 25 | 7 | | 26 | 8 | | 27 | 3 | | 28 | 5 | | 29 | 21 | | 30 | 18 | | 31 | 9 | | 32 | 13 | | 33 | 5 | | 34 | 3 | | 35 | 3 | | 36 | 2 | | 37 | 5 | | 38 | 12 | | 39 | 19 | | 40 | 24 | | 41 | 4 | | 42 | 4 | | 43 | 8 | | 44 | 24 | | 45 | 7 | | 46 | 17 | | 47 | 2 | | 48 | 4 | | 49 | 3 |
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| 41.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.2980769230769231 | | totalSentences | 104 | | uniqueOpeners | 31 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 85 | | matches | | 0 | "Then she spotted the green" | | 1 | "Then the passage opened into" | | 2 | "Then he bolted." | | 3 | "Then she heard it—the scuffle" | | 4 | "Then Herrera sighed, his shoulders" | | 5 | "Then, slowly, he reached into" | | 6 | "Then she stepped forward, into" |
| | ratio | 0.082 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 85 | | matches | | 0 | "She didn’t slow." | | 1 | "She didn’t hesitate." | | 2 | "She shoved through the crowd," | | 3 | "She’d heard whispers of it," | | 4 | "He turned, just for a" | | 5 | "She dodged, her boots slipping" | | 6 | "He knew this place." | | 7 | "She took the stairs." | | 8 | "She rounded a corner and" | | 9 | "His gaze was fixed on" | | 10 | "She didn’t lower her gun." | | 11 | "He tossed it to her." | | 12 | "She caught it, her skin" | | 13 | "She didn’t trust either of" | | 14 | "She pocketed the token." | | 15 | "She took a breath, her" |
| | ratio | 0.188 | |
| 71.76% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 85 | | matches | | 0 | "The pavement cracked under Quinn’s" | | 1 | "The suspect’s coat flared like" | | 2 | "Rain needled her face, turning" | | 3 | "She didn’t slow." | | 4 | "A real lead." | | 5 | "A real suspect." | | 6 | "The kind with answers." | | 7 | "The alley spat her out" | | 8 | "A bus rumbled past, its" | | 9 | "She didn’t hesitate." | | 10 | "The bar’s door swung shut" | | 11 | "The air inside was thick" | | 12 | "Quinn’s eyes locked onto the" | | 13 | "She shoved through the crowd," | | 14 | "The bookshelf swung shut behind" | | 15 | "A narrow passage stretched ahead," | | 16 | "The walls were lined with" | | 17 | "Quinn’s fingers brushed her sidearm" | | 18 | "The Veil Market." | | 19 | "She’d heard whispers of it," |
| | ratio | 0.776 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "Stalls lined the walls, their wares hidden under cloth or glass, their owners watching her with unblinking eyes." | | 1 | "A stallholder hissed something in a language she didn’t know, his fingers tightening around a vial of swirling liquid." | | 2 | "She dodged, her boots slipping on the uneven ground, and nearly collided with a woman holding a cage of something that chirped and fluttered." |
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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 | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0 | | effectiveRatio | 0 | |