| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 26 | | adverbTagCount | 2 | | adverbTags | | 0 | "Harlow ordered sharply [sharply]" | | 1 | "Eva said softly [softly]" |
| | dialogueSentences | 57 | | tagDensity | 0.456 | | leniency | 0.912 | | rawRatio | 0.077 | | effectiveRatio | 0.07 | |
| 73.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1310 | | totalAiIsmAdverbs | 7 | | found | | | highlights | | 0 | "slightly" | | 1 | "carefully" | | 2 | "sharply" | | 3 | "quickly" | | 4 | "softly" | | 5 | "completely" |
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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) | |
| 54.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1310 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "glistening" | | 2 | "stark" | | 3 | "weight" | | 4 | "eyebrow" | | 5 | "gloom" | | 6 | "glint" | | 7 | "etched" | | 8 | "vibrated" |
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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 | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 107 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1308 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 11.73% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 56 | | wordCount | 904 | | uniqueNames | 12 | | maxNameDensity | 2.77 | | worstName | "Harlow" | | maxWindowNameDensity | 4 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 1 | | Quinn | 1 | | Sergeant | 1 | | Vance | 14 | | Harlow | 25 | | Victorian | 2 | | Tube | 1 | | Dry | 1 | | Eva | 7 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Sergeant" | | 2 | "Vance" | | 3 | "Harlow" | | 4 | "Eva" | | 5 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" |
| | globalScore | 0.117 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 47.09% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.529 | | wordCount | 1308 | | matches | | 0 | "not police clearance, but historical access" | | 1 | "not guilt, but terror" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 107 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 55 | | mean | 23.78 | | std | 15.23 | | cv | 0.64 | | sampleLengths | | 0 | 53 | | 1 | 14 | | 2 | 42 | | 3 | 44 | | 4 | 45 | | 5 | 12 | | 6 | 38 | | 7 | 10 | | 8 | 31 | | 9 | 9 | | 10 | 37 | | 11 | 7 | | 12 | 6 | | 13 | 34 | | 14 | 15 | | 15 | 18 | | 16 | 2 | | 17 | 11 | | 18 | 8 | | 19 | 57 | | 20 | 36 | | 21 | 15 | | 22 | 27 | | 23 | 4 | | 24 | 2 | | 25 | 47 | | 26 | 17 | | 27 | 27 | | 28 | 11 | | 29 | 19 | | 30 | 5 | | 31 | 16 | | 32 | 49 | | 33 | 55 | | 34 | 9 | | 35 | 22 | | 36 | 13 | | 37 | 24 | | 38 | 22 | | 39 | 31 | | 40 | 27 | | 41 | 26 | | 42 | 47 | | 43 | 8 | | 44 | 20 | | 45 | 13 | | 46 | 37 | | 47 | 47 | | 48 | 25 | | 49 | 9 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 148 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 107 | | ratio | 0.009 | | matches | | 0 | "The twitch in Eva's finger, the nervous shifting of her feet—not guilt, but terror." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 910 | | adjectiveStacks | 1 | | stackExamples | | 0 | "thick, leather-bound volume" |
| | adverbCount | 26 | | adverbRatio | 0.02857142857142857 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.017582417582417582 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 107 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 107 | | mean | 12.22 | | std | 6.96 | | cv | 0.569 | | sampleLengths | | 0 | 24 | | 1 | 12 | | 2 | 17 | | 3 | 10 | | 4 | 4 | | 5 | 21 | | 6 | 21 | | 7 | 3 | | 8 | 19 | | 9 | 22 | | 10 | 10 | | 11 | 35 | | 12 | 12 | | 13 | 34 | | 14 | 4 | | 15 | 10 | | 16 | 19 | | 17 | 5 | | 18 | 7 | | 19 | 9 | | 20 | 16 | | 21 | 16 | | 22 | 5 | | 23 | 7 | | 24 | 6 | | 25 | 8 | | 26 | 16 | | 27 | 10 | | 28 | 15 | | 29 | 14 | | 30 | 4 | | 31 | 2 | | 32 | 11 | | 33 | 8 | | 34 | 19 | | 35 | 18 | | 36 | 20 | | 37 | 6 | | 38 | 30 | | 39 | 7 | | 40 | 8 | | 41 | 7 | | 42 | 20 | | 43 | 4 | | 44 | 2 | | 45 | 14 | | 46 | 4 | | 47 | 21 | | 48 | 8 | | 49 | 4 |
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| 86.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5514018691588785 | | totalSentences | 107 | | uniqueOpeners | 59 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 74 | | matches | | 0 | "She checked the worn leather" | | 1 | "She walked the edge of" | | 2 | "Her voice cut through the" | | 3 | "His clothes were soaked, but" | | 4 | "She picked up a wooden" | | 5 | "She tipped the victim's chin" | | 6 | "Her posture locked, shoulders back," | | 7 | "She clutched a heavy, worn" | | 8 | "Her green eyes wide, her" | | 9 | "She stepped past the yellow" | | 10 | "She knelt once more, ignoring" | | 11 | "She reached inside the inner" | | 12 | "Her fingers brushed against cold" | | 13 | "She pulled out a small" |
| | ratio | 0.189 | |
| 7.30% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 74 | | matches | | 0 | "Water dripped from a rusted" | | 1 | "Harlow Quinn adjusted the collar" | | 2 | "Moisture clung to her closely" | | 3 | "She checked the worn leather" | | 4 | "Detective Sergeant Vance pointed a" | | 5 | "Harlow didn't answer." | | 6 | "She walked the edge of" | | 7 | "Victorian white enamel, yellowed by" | | 8 | "Vance continued, following her heels" | | 9 | "Harlow crouched by the rails," | | 10 | "Her voice cut through the" | | 11 | "Vance squinted up into the" | | 12 | "Harlow reached out, running a" | | 13 | "Harlow pointed toward the heavy" | | 14 | "The heavy padlock hung intact," | | 15 | "Vance clicked his tongue, shifting" | | 16 | "Harlow turned her focus back" | | 17 | "The dead man lay faceup" | | 18 | "His clothes were soaked, but" | | 19 | "Harlow touched the hem of" |
| | ratio | 0.905 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 79.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 3 | | matches | | 0 | "The heavy padlock hung intact, coated in thick, grey cobwebs that stretched continuously across the jamb." | | 1 | "No ligature marks, but three fine, parallel scratches ran along the curve of his throat, glowing with a faint, iridescent film that caught the blue tint of the …" | | 2 | "A faint hum vibrated through the metal, vibrating against the skin of her palm, mirroring the steady, rhythmic dripping of the water overhead." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 26 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva took, her satchel clanking with the weight of heavy books inside" | | 1 | "Harlow said, her voice dropping an octave, completely devoid of doubt" |
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| 44.74% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 13 | | fancyCount | 6 | | fancyTags | | 0 | "Vance continued (continue)" | | 1 | "Vance barked (bark)" | | 2 | "Harlow ordered sharply (order)" | | 3 | "Vance laughed (laugh)" | | 4 | "Harlow demanded (demand)" | | 5 | "Eva whispered (whisper)" |
| | dialogueSentences | 57 | | tagDensity | 0.228 | | leniency | 0.456 | | rawRatio | 0.462 | | effectiveRatio | 0.211 | |