| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.48 | | leniency | 0.96 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 80.86% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1045 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "gently" | | 1 | "suddenly" | | 2 | "warily" | | 3 | "slightly" |
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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) | |
| 9.09% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1045 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "pounding" | | 1 | "flickered" | | 2 | "familiar" | | 3 | "eyebrow" | | 4 | "amiss" | | 5 | "scanning" | | 6 | "stark" | | 7 | "scanned" | | 8 | "echoing" | | 9 | "sanctuary" | | 10 | "ensuring" | | 11 | "whisper" | | 12 | "flicker" | | 13 | "raced" | | 14 | "resolved" | | 15 | "tapestry" | | 16 | "apprehension" | | 17 | "weight" |
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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 | 0 | | narrationSentences | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 81 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 94 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1043 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 49.29% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 844 | | uniqueNames | 10 | | maxNameDensity | 2.01 | | worstName | "Harlow" | | maxWindowNameDensity | 3 | | worstWindowName | "Tomás" | | discoveredNames | | Quinn | 1 | | Raven | 2 | | Nest | 2 | | Harlow | 17 | | Silas | 3 | | Morris | 2 | | Veil | 1 | | Market | 1 | | Tube | 1 | | Tomás | 6 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Harlow" | | 4 | "Silas" | | 5 | "Morris" | | 6 | "Tomás" |
| | places | (empty) | | globalScore | 0.493 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | 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 | 1043 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 28.19 | | std | 15.21 | | cv | 0.54 | | sampleLengths | | 0 | 57 | | 1 | 28 | | 2 | 54 | | 3 | 43 | | 4 | 4 | | 5 | 11 | | 6 | 10 | | 7 | 16 | | 8 | 22 | | 9 | 50 | | 10 | 46 | | 11 | 35 | | 12 | 41 | | 13 | 33 | | 14 | 29 | | 15 | 59 | | 16 | 12 | | 17 | 34 | | 18 | 44 | | 19 | 20 | | 20 | 40 | | 21 | 11 | | 22 | 16 | | 23 | 9 | | 24 | 23 | | 25 | 8 | | 26 | 29 | | 27 | 17 | | 28 | 51 | | 29 | 34 | | 30 | 14 | | 31 | 16 | | 32 | 28 | | 33 | 35 | | 34 | 9 | | 35 | 24 | | 36 | 31 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 81 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 168 | | matches | | |
| 51.67% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 2 | | flaggedSentences | 3 | | totalSentences | 94 | | ratio | 0.032 | | matches | | 0 | "The Raven's Nest wasn’t just any bar; it was Silas' place, and everyone knew it doubled as a haven for the city's more dubious characters." | | 1 | "Her fingers grazed the spines until she found the trigger - a worn copy of \"Treasures of the Lost Kingdoms.\" She pulled it, and the hidden door creaked open." | | 2 | "The implications of Tomás’ words meant more than just a simple chase; they hinted at corruption, hidden agendas, and a danger that went beyond her typical remit." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 234 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.017094017094017096 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 94 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 94 | | mean | 11.1 | | std | 6.25 | | cv | 0.563 | | sampleLengths | | 0 | 13 | | 1 | 16 | | 2 | 28 | | 3 | 7 | | 4 | 9 | | 5 | 12 | | 6 | 17 | | 7 | 12 | | 8 | 25 | | 9 | 14 | | 10 | 12 | | 11 | 7 | | 12 | 10 | | 13 | 4 | | 14 | 11 | | 15 | 9 | | 16 | 1 | | 17 | 7 | | 18 | 9 | | 19 | 7 | | 20 | 15 | | 21 | 4 | | 22 | 17 | | 23 | 29 | | 24 | 10 | | 25 | 9 | | 26 | 9 | | 27 | 18 | | 28 | 8 | | 29 | 18 | | 30 | 9 | | 31 | 11 | | 32 | 7 | | 33 | 15 | | 34 | 8 | | 35 | 5 | | 36 | 12 | | 37 | 16 | | 38 | 9 | | 39 | 11 | | 40 | 9 | | 41 | 3 | | 42 | 9 | | 43 | 16 | | 44 | 13 | | 45 | 18 | | 46 | 7 | | 47 | 5 | | 48 | 16 | | 49 | 18 |
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| 70.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4574468085106383 | | totalSentences | 94 | | uniqueOpeners | 43 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 79 | | matches | | 0 | "Her quarry, a nimble figure" | | 1 | "she snapped, scanning the dimly" | | 2 | "he admitted, nodding towards a" | | 3 | "She shoved past the few" | | 4 | "Her fingers grazed the spines" | | 5 | "She lunged, feeling the sting" | | 6 | "She paused, only for a" | | 7 | "She gripped the ladder and" | | 8 | "Her suspect weaved through the" | | 9 | "She spotted the hooded figure" | | 10 | "She drew her sidearm, holding" | | 11 | "She lowered her weapon, just" | | 12 | "He shrugged, the medallion around" | | 13 | "Her grip tightened on her" | | 14 | "he replied, his voice a" | | 15 | "She needed to think." | | 16 | "she said, lowering her gun" | | 17 | "He turned, leading her through" | | 18 | "They finally stopped at a" | | 19 | "She stepped into the dark" |
| | ratio | 0.253 | |
| 23.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 79 | | matches | | 0 | "Harlow Quinn's breath came in" | | 1 | "The rain had grown into" | | 2 | "Her quarry, a nimble figure" | | 3 | "Harlow yelled, though it was" | | 4 | "The hooded figure didn’t look" | | 5 | "A puddle splashed up, soaking" | | 6 | "The suspect veered towards the" | | 7 | "The Raven's Nest wasn’t just" | | 8 | "Harlow growled as she pushed" | | 9 | "The bar's familiar acrid scent" | | 10 | "The hooded figure was nowhere" | | 11 | "Silas, wiping a glass behind" | | 12 | "she snapped, scanning the dimly" | | 13 | "Silas pretended to inspect a" | | 14 | "Harlow stepped closer, her voice" | | 15 | "Silas sighed, setting the glass" | | 16 | "he admitted, nodding towards a" | | 17 | "Harlow wasted no time." | | 18 | "She shoved past the few" | | 19 | "Her fingers grazed the spines" |
| | ratio | 0.873 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 79 | | matches | | 0 | "If she was to apprehend" | | 1 | "To finally prove she wasn’t" |
| | ratio | 0.025 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 1 | | matches | | 0 | "Tomás replied, his voice devoid of surprise" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 5 | | fancyTags | | 0 | "Harlow yelled (yell)" | | 1 | "Harlow growled (growl)" | | 2 | "she snapped (snap)" | | 3 | "he admitted (admit)" | | 4 | "she demanded (demand)" |
| | dialogueSentences | 25 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |