| 78.79% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn said softly [softly]" | | 1 | "Gently Quinn pressed [Gently]" |
| | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0.143 | | effectiveRatio | 0.121 | |
| 86.32% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1462 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "softly" | | 1 | "gently" | | 2 | "anxiously" |
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| 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) | |
| 38.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1462 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "pulse" | | 1 | "echo" | | 2 | "echoing" | | 3 | "velvet" | | 4 | "scanning" | | 5 | "traced" | | 6 | "flicked" | | 7 | "etched" | | 8 | "flicker" | | 9 | "tracing" | | 10 | "flickered" | | 11 | "shattered" | | 12 | "footsteps" | | 13 | "gloom" | | 14 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 102 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 121 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1443 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 1065 | | uniqueNames | 12 | | maxNameDensity | 2.25 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 24 | | Tube | 1 | | London | 1 | | Camden | 1 | | Veil | 2 | | Market | 2 | | Kowalski | 1 | | Eva | 14 | | Oxford | 1 | | Morris | 1 | | Headquarters | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" | | 4 | "Morris" |
| | places | | | globalScore | 0.373 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 74 | | 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 | 1443 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 121 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 46.55 | | std | 29.97 | | cv | 0.644 | | sampleLengths | | 0 | 123 | | 1 | 99 | | 2 | 68 | | 3 | 44 | | 4 | 37 | | 5 | 67 | | 6 | 76 | | 7 | 57 | | 8 | 54 | | 9 | 57 | | 10 | 43 | | 11 | 22 | | 12 | 36 | | 13 | 85 | | 14 | 9 | | 15 | 64 | | 16 | 15 | | 17 | 73 | | 18 | 16 | | 19 | 68 | | 20 | 6 | | 21 | 34 | | 22 | 9 | | 23 | 58 | | 24 | 9 | | 25 | 26 | | 26 | 68 | | 27 | 5 | | 28 | 12 | | 29 | 24 | | 30 | 79 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 102 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 195 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 5 | | flaggedSentences | 14 | | totalSentences | 121 | | ratio | 0.116 | | matches | | 0 | "A faint pulse of murmured bartering drifted from deeper in the tunnels—voices too hushed to make out, punctuated by the scrape of crates on concrete." | | 1 | "She inhaled, tasting damp stone and something more metallic—blood, she suspected, or the echo of it." | | 2 | "Vendors had packed away most wares—brass talismans, phials of writhing ichor, dusty tomes—leaving only six feet of open space around one stall draped in tattered velvet." | | 3 | "A yellow police cordon bisected the tunnel; ghostly bodies of uniformed officers stood at its perimeter, nodding when Quinn produced her badge." | | 4 | "The man’s cloak—a midnight blue weave that somehow absorbed ambient light—had parted to reveal a suit stained in blossom-shaped splatters of crimson." | | 5 | "The tunnel roof curved low here; steel girders arched overhead." | | 6 | "She flicked her jawline against stubble of frustration—another ritualistic murder?" | | 7 | "In three strides she reached the man’s shoes—Oxford brogues polished so dark they were almost black." | | 8 | "A flicker of shifting color—violet and black streamers, like oil on water." | | 9 | "Three yellow tags marked pieces of charcoal and iron filings along the tile edge—evidence collected by junior officers." | | 10 | "Quinn’s watch beeped softly; she checked the screen: five missed texts from CID Headquarters, three more from a number she didn’t know." | | 11 | "Most lay empty; a few lingering merchants squared shoulders at the police cordon, their eyes flicking between Quinn and the body." | | 12 | "She pressed a finger to the compass in her pocket; the sigils on its face gleamed faintly." | | 13 | "In the gloom, two women moved toward the silent breach—one with the precision of a soldier, the other with the knowledge of ancient rites." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1079 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.025023169601482854 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.008341056533827619 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 121 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 121 | | mean | 11.93 | | std | 7.49 | | cv | 0.628 | | sampleLengths | | 0 | 23 | | 1 | 20 | | 2 | 25 | | 3 | 25 | | 4 | 14 | | 5 | 16 | | 6 | 14 | | 7 | 14 | | 8 | 6 | | 9 | 17 | | 10 | 26 | | 11 | 22 | | 12 | 12 | | 13 | 22 | | 14 | 3 | | 15 | 10 | | 16 | 12 | | 17 | 9 | | 18 | 12 | | 19 | 11 | | 20 | 15 | | 21 | 6 | | 22 | 13 | | 23 | 10 | | 24 | 4 | | 25 | 10 | | 26 | 3 | | 27 | 13 | | 28 | 34 | | 29 | 17 | | 30 | 4 | | 31 | 17 | | 32 | 16 | | 33 | 10 | | 34 | 17 | | 35 | 12 | | 36 | 11 | | 37 | 7 | | 38 | 10 | | 39 | 15 | | 40 | 5 | | 41 | 9 | | 42 | 3 | | 43 | 8 | | 44 | 8 | | 45 | 3 | | 46 | 15 | | 47 | 14 | | 48 | 3 | | 49 | 12 |
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| 64.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.39669421487603307 | | totalSentences | 121 | | uniqueOpeners | 48 | |
| 66.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 100 | | matches | | 0 | "Gently, Quinn pressed her fingertips" | | 1 | "Most lay empty; a few" |
| | ratio | 0.02 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 100 | | matches | | 0 | "She inhaled, tasting damp stone" | | 1 | "She descended the final steps" | | 2 | "She dropped to one knee," | | 3 | "She touched the nape of" | | 4 | "She flicked her jawline against" | | 5 | "She met Eva’s gaze." | | 6 | "She tucked a curl behind" | | 7 | "She tipped a small sample" | | 8 | "She watched vendors and buyers" | | 9 | "She knelt again and pried" | | 10 | "She bit the corner of" | | 11 | "She leaned in." | | 12 | "She gestured to the runes" | | 13 | "She walked the perimeter of" | | 14 | "She ignored all of them." | | 15 | "Her gaze snapped to an" | | 16 | "She followed it, elbowing past" | | 17 | "She turned, scanning other stalls" | | 18 | "She cleared her throat." | | 19 | "She paused at the body," |
| | ratio | 0.27 | |
| 15.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 89 | | totalSentences | 100 | | matches | | 0 | "Detective Harlow Quinn paused at" | | 1 | "The dim vault of the" | | 2 | "A faint pulse of murmured" | | 3 | "This was the Veil Market" | | 4 | "Quinn’s mastiff posture remained rigid," | | 5 | "She inhaled, tasting damp stone" | | 6 | "Eva Kowalski adjusted her round" | | 7 | "Quinn didn’t wait for an" | | 8 | "She descended the final steps" | | 9 | "Vendors had packed away most" | | 10 | "A yellow police cordon bisected" | | 11 | "The body lay face-down in" | | 12 | "The man’s cloak—a midnight blue" | | 13 | "Quinn crouched, scanning." | | 14 | "The tunnel roof curved low" | | 15 | "Blood had pooled along the" | | 16 | "She dropped to one knee," | | 17 | "The man’s hair shone black," | | 18 | "She touched the nape of" | | 19 | "Ligature marks circled like a" |
| | ratio | 0.89 | |
| 50.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 100 | | matches | | | ratio | 0.01 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "She tipped, the dust settling into filigree on her palm" |
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| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 3 | | fancyTags | | 0 | "Eva murmured (murmur)" | | 1 | "Gently Quinn pressed (press)" | | 2 | "she whispered (whisper)" |
| | dialogueSentences | 33 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.5 | | effectiveRatio | 0.182 | |