| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.154 | | leniency | 0.308 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 897 | | totalAiIsmAdverbs | 2 | | 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) | |
| 27.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 897 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "glistening" | | 1 | "flickered" | | 2 | "pulse" | | 3 | "quickened" | | 4 | "weight" | | 5 | "familiar" | | 6 | "could feel" | | 7 | "flicker" | | 8 | "shattered" | | 9 | "flicked" | | 10 | "echoing" | | 11 | "whisper" |
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| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
| | 1 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "blood ran cold" | | 1 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 86 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 5 | | totalWords | 883 | | ratio | 0.006 | | matches | | 0 | "Raven’s Nest" | | 1 | "wrong" | | 2 | "Veil Market" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 811 | | uniqueNames | 6 | | maxNameDensity | 1.97 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 16 | | Elias | 2 | | Voss | 9 | | Herrera | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Elias" | | 3 | "Voss" | | 4 | "Herrera" |
| | places | | | globalScore | 0.514 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | 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 | 883 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 86 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 26 | | mean | 33.96 | | std | 29.7 | | cv | 0.875 | | sampleLengths | | 0 | 114 | | 1 | 86 | | 2 | 54 | | 3 | 62 | | 4 | 49 | | 5 | 74 | | 6 | 5 | | 7 | 79 | | 8 | 24 | | 9 | 9 | | 10 | 6 | | 11 | 6 | | 12 | 18 | | 13 | 10 | | 14 | 51 | | 15 | 29 | | 16 | 59 | | 17 | 20 | | 18 | 7 | | 19 | 13 | | 20 | 6 | | 21 | 39 | | 22 | 24 | | 23 | 26 | | 24 | 11 | | 25 | 2 |
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| 86.80% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 76 | | matches | | 0 | "was gone" | | 1 | "were lined" | | 2 | "were lined" | | 3 | "was gone" |
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| 60.14% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 143 | | matches | | 0 | "was running" | | 1 | "was waiting" | | 2 | "wasn’t looking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 86 | | ratio | 0.116 | | matches | | 0 | "She had been tailing the suspect for twenty minutes now—someone who moved like a ghost through the shadows, slipping in and out of alleys with unsettling ease." | | 1 | "Then—movement." | | 2 | "Then, another turn—this time into a narrow passage that smelled of damp stone and something older, something *wrong*." | | 3 | "Then she saw it—a flicker of movement in the distance." | | 4 | "And worse—she’d lose the chance to avenge her partner." | | 5 | "The walls themselves were lined with strange artifacts—bones, jars of black liquid, maps with symbols carved into them." | | 6 | "Quinn turned just in time to see a figure step out of the shadows—a man with a scar running down his forearm, his dark hair damp from the rain." | | 7 | "Herrera’s eyes locked onto hers, and for a moment, Quinn saw something raw in them—fear, guilt, something worse." | | 8 | "And in the center of the room, beneath the table, something glinted in the candlelight—a bone token, the kind that granted access to places like this." | | 9 | "In its place was a vast, underground market—stalls lined with goods she didn’t recognize, people moving in the shadows, their faces half-hidden by hoods or masks." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 824 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.024271844660194174 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.007281553398058253 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 86 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 86 | | mean | 10.27 | | std | 6.93 | | cv | 0.675 | | sampleLengths | | 0 | 16 | | 1 | 25 | | 2 | 23 | | 3 | 27 | | 4 | 18 | | 5 | 5 | | 6 | 12 | | 7 | 22 | | 8 | 14 | | 9 | 20 | | 10 | 3 | | 11 | 15 | | 12 | 9 | | 13 | 16 | | 14 | 1 | | 15 | 11 | | 16 | 6 | | 17 | 11 | | 18 | 18 | | 19 | 18 | | 20 | 4 | | 21 | 22 | | 22 | 10 | | 23 | 4 | | 24 | 14 | | 25 | 21 | | 26 | 10 | | 27 | 13 | | 28 | 4 | | 29 | 2 | | 30 | 4 | | 31 | 11 | | 32 | 12 | | 33 | 9 | | 34 | 9 | | 35 | 5 | | 36 | 8 | | 37 | 16 | | 38 | 17 | | 39 | 18 | | 40 | 20 | | 41 | 11 | | 42 | 5 | | 43 | 8 | | 44 | 6 | | 45 | 3 | | 46 | 5 | | 47 | 1 | | 48 | 6 | | 49 | 3 |
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| 37.21% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.2441860465116279 | | totalSentences | 86 | | uniqueOpeners | 21 | |
| 93.90% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 71 | | matches | | 0 | "Then, another turn—this time into" | | 1 | "Then she saw it—a flicker" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 71 | | matches | | 0 | "She had been tailing the" | | 1 | "She adjusted her grip on" | | 2 | "He was waiting." | | 3 | "She could feel it in" | | 4 | "She stepped forward, her boots" | | 5 | "She took off after him," | | 6 | "She didn’t like this." | | 7 | "She didn’t like the way" | | 8 | "She didn’t like the way" | | 9 | "She knew the rules." | | 10 | "She knew the dangers of" | | 11 | "She pushed the door open." | | 12 | "He turned as she entered," | | 13 | "His smile was slow, knowing." | | 14 | "He leaned forward, resting his" | | 15 | "he said, his voice rough" | | 16 | "She was too busy taking" | | 17 | "She whirled around, her gun" | | 18 | "She had no idea where" | | 19 | "She had one choice left." |
| | ratio | 0.282 | |
| 44.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 71 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn’s boots splashed" | | 2 | "The neon glow of the" | | 3 | "She had been tailing the" | | 4 | "The man’s name was Elias" | | 5 | "A sharp turn down a" | | 6 | "The rain hammered against her" | | 7 | "She adjusted her grip on" | | 8 | "The suspect had vanished into" | | 9 | "He was waiting." | | 10 | "She could feel it in" | | 11 | "She stepped forward, her boots" | | 12 | "The alley was a labyrinth" | | 13 | "A flicker of dark fabric," | | 14 | "Quinn’s muscles coiled, ready to" | | 15 | "She took off after him," | | 16 | "The suspect led her past" | | 17 | "The air grew colder." | | 18 | "The rain above them had" | | 19 | "Quinn’s fingers brushed against the" |
| | ratio | 0.831 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 3 | | matches | | 0 | "She had been tailing the suspect for twenty minutes now—someone who moved like a ghost through the shadows, slipping in and out of alleys with unsettling ease." | | 1 | "Then, another turn—this time into a narrow passage that smelled of damp stone and something older, something *wrong*." | | 2 | "There were symbols carved into the stone, symbols that made her skin prickle." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, his voice rough" |
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| 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 | |