| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "she asked quietly [quietly]" |
| | dialogueSentences | 58 | | tagDensity | 0.224 | | leniency | 0.448 | | rawRatio | 0.077 | | effectiveRatio | 0.034 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1214 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 46.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1214 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "glinting" | | 1 | "etched" | | 2 | "silence" | | 3 | "traced" | | 4 | "tension" | | 5 | "flicked" | | 6 | "flickered" | | 7 | "weight" | | 8 | "trembled" | | 9 | "charged" | | 10 | "pulse" | | 11 | "calculating" |
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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 | 102 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 102 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 146 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 9 | | totalWords | 1212 | | ratio | 0.007 | | matches | | 0 | "Local Man Found Dead in Alleway—Police Suspect Foul Play." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 879 | | uniqueNames | 16 | | maxNameDensity | 1.14 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Blackwood | 1 | | Rory | 1 | | Cardiff | 1 | | Raven | 1 | | Nest | 1 | | Man | 1 | | Found | 1 | | Dead | 1 | | Alleway | 1 | | Police | 1 | | Suspect | 1 | | Foul | 1 | | Silas | 10 | | Evan | 4 | | Aurora | 4 | | Knew | 3 |
| | persons | | 0 | "Blackwood" | | 1 | "Rory" | | 2 | "Raven" | | 3 | "Man" | | 4 | "Silas" | | 5 | "Evan" | | 6 | "Aurora" |
| | places | | | globalScore | 0.931 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "tune that seemed to mock the tension coiling between them" |
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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 | 1212 | | matches | (empty) | |
| 75.34% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 4 | | totalSentences | 146 | | matches | | 0 | "knew that voice" | | 1 | "know that face" | | 2 | "knew that look" | | 3 | "knew that voice" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 18.36 | | std | 12.7 | | cv | 0.692 | | sampleLengths | | 0 | 37 | | 1 | 10 | | 2 | 34 | | 3 | 43 | | 4 | 18 | | 5 | 21 | | 6 | 36 | | 7 | 22 | | 8 | 43 | | 9 | 5 | | 10 | 9 | | 11 | 7 | | 12 | 13 | | 13 | 32 | | 14 | 5 | | 15 | 9 | | 16 | 20 | | 17 | 8 | | 18 | 5 | | 19 | 16 | | 20 | 17 | | 21 | 37 | | 22 | 35 | | 23 | 11 | | 24 | 24 | | 25 | 2 | | 26 | 30 | | 27 | 47 | | 28 | 26 | | 29 | 2 | | 30 | 1 | | 31 | 47 | | 32 | 16 | | 33 | 44 | | 34 | 17 | | 35 | 17 | | 36 | 9 | | 37 | 22 | | 38 | 13 | | 39 | 31 | | 40 | 33 | | 41 | 4 | | 42 | 7 | | 43 | 40 | | 44 | 10 | | 45 | 11 | | 46 | 30 | | 47 | 27 | | 48 | 5 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 102 | | matches | (empty) | |
| 75.78% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 161 | | matches | | 0 | "was pressing" | | 1 | "weren’t saying" | | 2 | "was itching" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 146 | | ratio | 0.014 | | matches | | 0 | "The years had etched lines around his hazel eyes, but they still held the same sharpness—like a blade kept sheathed but never dull." | | 1 | "The headline read: *Local Man Found Dead in Alleway—Police Suspect Foul Play.*" |
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| 97.26% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 881 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.043132803632236094 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.00681044267877412 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 146 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 146 | | mean | 8.3 | | std | 5.77 | | cv | 0.695 | | sampleLengths | | 0 | 11 | | 1 | 11 | | 2 | 15 | | 3 | 10 | | 4 | 12 | | 5 | 4 | | 6 | 10 | | 7 | 8 | | 8 | 20 | | 9 | 23 | | 10 | 18 | | 11 | 16 | | 12 | 5 | | 13 | 9 | | 14 | 6 | | 15 | 18 | | 16 | 3 | | 17 | 10 | | 18 | 12 | | 19 | 5 | | 20 | 24 | | 21 | 3 | | 22 | 6 | | 23 | 5 | | 24 | 5 | | 25 | 9 | | 26 | 7 | | 27 | 10 | | 28 | 3 | | 29 | 11 | | 30 | 15 | | 31 | 2 | | 32 | 4 | | 33 | 5 | | 34 | 3 | | 35 | 6 | | 36 | 11 | | 37 | 9 | | 38 | 8 | | 39 | 5 | | 40 | 9 | | 41 | 7 | | 42 | 11 | | 43 | 6 | | 44 | 12 | | 45 | 25 | | 46 | 18 | | 47 | 10 | | 48 | 7 | | 49 | 11 |
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| 51.14% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.3561643835616438 | | totalSentences | 146 | | uniqueOpeners | 52 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 88 | | matches | | 0 | "Of course he’d ended up" | | 1 | "Of course she had too." | | 2 | "Of course he noticed." | | 3 | "Just for a second." | | 4 | "Then his mask slid back" | | 5 | "Instead, he reached into his" | | 6 | "Then, from the shadows behind" | | 7 | "Even the smoke seemed to" |
| | ratio | 0.091 | |
| 83.64% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 88 | | matches | | 0 | "She knew that voice." | | 1 | "Her spine straightened before her" | | 2 | "she said, setting the glass" | | 3 | "He took a sip, watching" | | 4 | "His beard twitched, the ghost" | | 5 | "She exhaled through her nose." | | 6 | "He set his glass down," | | 7 | "She traced the crescent scar" | | 8 | "Her fingers stilled." | | 9 | "He scoffed, as if the" | | 10 | "She tasted the word like" | | 11 | "His jaw tightened, the only" | | 12 | "His voice dropped, the gravel" | | 13 | "She wanted to snap at" | | 14 | "He rolled his shoulder, the" | | 15 | "She opened her mouth to" | | 16 | "she asked quietly" | | 17 | "He didn’t answer right away." | | 18 | "She unfolded it." | | 19 | "Her breath caught." |
| | ratio | 0.341 | |
| 67.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 88 | | matches | | 0 | "The glass slipped from her" | | 1 | "Aurora barely caught it, the" | | 2 | "The piano’s discordant note hung" | | 3 | "The voice cut through the" | | 4 | "She knew that voice." | | 5 | "Her spine straightened before her" | | 6 | "Silas Blackwood leaned against the" | | 7 | "The years had etched lines" | | 8 | "she said, setting the glass" | | 9 | "He took a sip, watching" | | 10 | "The name hit like a" | | 11 | "His beard twitched, the ghost" | | 12 | "She exhaled through her nose." | | 13 | "The bar smelled of aged" | | 14 | "The Raven’s Nest." | | 15 | "He set his glass down," | | 16 | "The words settled between them," | | 17 | "She traced the crescent scar" | | 18 | "Her fingers stilled." | | 19 | "He scoffed, as if the" |
| | ratio | 0.784 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "His beard twitched, the ghost of a smirk" | | 1 | "He scoffed, as if the question were beneath them both" | | 2 | "He rolled, the old injury flaring under the movement" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 58 | | tagDensity | 0.086 | | leniency | 0.172 | | rawRatio | 0.2 | | effectiveRatio | 0.034 | |