| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 23 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 52 | | tagDensity | 0.442 | | leniency | 0.885 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1587 | | totalAiIsmAdverbs | 1 | | 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) | |
| 59.04% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1587 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "fractured" | | 1 | "glint" | | 2 | "weight" | | 3 | "intricate" | | 4 | "scanned" | | 5 | "unravel" | | 6 | "stomach" | | 7 | "velvet" | | 8 | "shimmered" | | 9 | "footsteps" | | 10 | "echoed" | | 11 | "trembled" |
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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 | 1 | | narrationSentences | 143 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 143 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 172 | | 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 | 0 | | markdownWords | 0 | | totalWords | 1583 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1203 | | uniqueNames | 10 | | maxNameDensity | 1.91 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Quinn | 23 | | Morris | 3 | | Veil | 1 | | Market | 1 | | Metropolitan | 1 | | Police | 1 | | Saint | 1 | | Christopher | 1 | | Tomás | 13 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Market" | | 3 | "Police" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Tomás" |
| | places | | | globalScore | 0.544 | | windowScore | 0.5 | |
| 92.53% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 87 | | glossingSentenceCount | 2 | | matches | | 0 | "stone that seemed to absorb the light" | | 1 | "looked like a bat made of smoke" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.632 | | wordCount | 1583 | | matches | | 0 | "not like shadow, but like a living fluid" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 172 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 65 | | mean | 24.35 | | std | 15.14 | | cv | 0.622 | | sampleLengths | | 0 | 62 | | 1 | 35 | | 2 | 49 | | 3 | 17 | | 4 | 61 | | 5 | 42 | | 6 | 28 | | 7 | 43 | | 8 | 47 | | 9 | 54 | | 10 | 50 | | 11 | 24 | | 12 | 12 | | 13 | 15 | | 14 | 30 | | 15 | 42 | | 16 | 10 | | 17 | 19 | | 18 | 35 | | 19 | 13 | | 20 | 38 | | 21 | 19 | | 22 | 13 | | 23 | 23 | | 24 | 3 | | 25 | 38 | | 26 | 19 | | 27 | 32 | | 28 | 9 | | 29 | 34 | | 30 | 5 | | 31 | 19 | | 32 | 23 | | 33 | 4 | | 34 | 40 | | 35 | 11 | | 36 | 45 | | 37 | 35 | | 38 | 6 | | 39 | 40 | | 40 | 42 | | 41 | 6 | | 42 | 32 | | 43 | 17 | | 44 | 16 | | 45 | 5 | | 46 | 15 | | 47 | 23 | | 48 | 14 | | 49 | 15 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 143 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 233 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 172 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1207 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.02568351284175642 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0033140016570008283 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 172 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 172 | | mean | 9.2 | | std | 5.57 | | cv | 0.605 | | sampleLengths | | 0 | 19 | | 1 | 13 | | 2 | 18 | | 3 | 12 | | 4 | 4 | | 5 | 12 | | 6 | 5 | | 7 | 8 | | 8 | 6 | | 9 | 23 | | 10 | 7 | | 11 | 10 | | 12 | 6 | | 13 | 3 | | 14 | 17 | | 15 | 5 | | 16 | 14 | | 17 | 21 | | 18 | 3 | | 19 | 18 | | 20 | 16 | | 21 | 5 | | 22 | 21 | | 23 | 8 | | 24 | 12 | | 25 | 8 | | 26 | 11 | | 27 | 8 | | 28 | 3 | | 29 | 12 | | 30 | 9 | | 31 | 6 | | 32 | 5 | | 33 | 17 | | 34 | 19 | | 35 | 10 | | 36 | 22 | | 37 | 22 | | 38 | 11 | | 39 | 3 | | 40 | 3 | | 41 | 10 | | 42 | 13 | | 43 | 7 | | 44 | 3 | | 45 | 11 | | 46 | 13 | | 47 | 10 | | 48 | 2 | | 49 | 4 |
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| 58.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3953488372093023 | | totalSentences | 172 | | uniqueOpeners | 68 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 132 | | matches | | 0 | "Instead of climbing, he dropped" | | 1 | "Just like the files on" | | 2 | "Then resumed, faster." |
| | ratio | 0.023 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 132 | | matches | | 0 | "She wasn't letting this one" | | 1 | "she shouted, the command lost" | | 2 | "He reached a dead end" | | 3 | "She peered into the gap." | | 4 | "His face remained shadowed, but" | | 5 | "He gestured downward, then vanished" | | 6 | "She stepped onto the first" | | 7 | "She kept her chin high," | | 8 | "He held up a small" | | 9 | "he rasped, his voice sounding" | | 10 | "He extended the bone again" | | 11 | "She scanned the crowd." | | 12 | "she said, her voice steady" | | 13 | "His breath smelled of rotting" | | 14 | "She could draw." | | 15 | "She could clear a path." | | 16 | "She spun, arm cocked back," | | 17 | "he said, his accent thick" | | 18 | "He glanced at the vendor," | | 19 | "He pressed it into the" |
| | ratio | 0.22 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 110 | | totalSentences | 132 | | matches | | 0 | "Harlow Quinn sprinted, her boots" | | 1 | "The air smelled of wet" | | 2 | "Quinn checked her watch." | | 3 | "The worn leather strap slapped" | | 4 | "She wasn't letting this one" | | 5 | "The suspect, a lean man" | | 6 | "Quinn followed, her breath ragged" | | 7 | "Military precision kept her stride" | | 8 | "Trash bins toppled in her" | | 9 | "Glass crunched underfoot." | | 10 | "she shouted, the command lost" | | 11 | "The man didn't look back." | | 12 | "He reached a dead end" | | 13 | "Darkness yawned beneath." | | 14 | "A draft rose from the" | | 15 | "Quinn skidded to a halt," | | 16 | "She peered into the gap." | | 17 | "The suspect paused at the" | | 18 | "His face remained shadowed, but" | | 19 | "He gestured downward, then vanished" |
| | ratio | 0.833 | |
| 75.76% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 132 | | matches | | 0 | "If she lost him now," | | 1 | "If they didn't move fast," |
| | ratio | 0.015 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 8 | | matches | | 0 | "Rain hammered the pavement, turning the Soho streets into slick mirrors that fractured the neon glow of shop signs." | | 1 | "Harlow Quinn sprinted, her boots splashing through puddles that swallowed her reflection whole." | | 2 | "Rough-hewn stone steps descended into the earth, lit by flickering blue flames that danced in wall sconces without consuming any fuel." | | 3 | "As she descended, the architecture shifted from crumbling brick to smooth, obsidian-like stone that seemed to absorb the light." | | 4 | "Figures in tattered cloaks brushed past vendors selling jars of glowing liquid and bundles of dried roots that twitched in their bindings." | | 5 | "A woman with skin like polished obsidian haggled over a cage containing a creature that looked like a bat made of smoke." | | 6 | "The suspect had moved deeper into the market, pushing past a stall selling mirrors that showed reflections of people who weren't there." | | 7 | "The suspect was already climbing, his feet slipping on the wet rungs." |
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| 38.04% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 23 | | uselessAdditionCount | 4 | | matches | | 0 | "he rasped, his voice sounding like grinding stones" | | 1 | "she said, her voice steady" | | 2 | "he said, his accent thick but understandable" | | 3 | "Quinn yelled, her voice booming in the confined space" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 8 | | fancyTags | | 0 | "she shouted (shout)" | | 1 | "the vendor insisted (insist)" | | 2 | "Tomás whispered (whisper)" | | 3 | "she ordered (order)" | | 4 | "Quinn yelled (yell)" | | 5 | "he screamed (scream)" | | 6 | "Tomás urged (urge)" | | 7 | "Tomás shouted (shout)" |
| | dialogueSentences | 52 | | tagDensity | 0.288 | | leniency | 0.577 | | rawRatio | 0.533 | | effectiveRatio | 0.308 | |