| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.85% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1093 | | 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) | |
| 22.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1093 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "gloom" | | 1 | "echoing" | | 2 | "predictable" | | 3 | "maw" | | 4 | "firmly" | | 5 | "silence" | | 6 | "shimmered" | | 7 | "whisper" | | 8 | "charged" | | 9 | "echo" | | 10 | "cacophony" | | 11 | "dancing" | | 12 | "depths" | | 13 | "scanned" | | 14 | "intricate" | | 15 | "etched" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 101 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 101 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1089 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 1042 | | uniqueNames | 7 | | maxNameDensity | 0.67 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 7 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Camden | 1 | | Morris | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 16.35% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.837 | | wordCount | 1089 | | matches | | 0 | "not running anymore, but walking with purpose towards a section of the tunnel" | | 1 | "Not the echo of a tunnel, but voices" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 25 | | mean | 43.56 | | std | 26.77 | | cv | 0.615 | | sampleLengths | | 0 | 70 | | 1 | 85 | | 2 | 66 | | 3 | 33 | | 4 | 18 | | 5 | 17 | | 6 | 17 | | 7 | 5 | | 8 | 17 | | 9 | 26 | | 10 | 60 | | 11 | 63 | | 12 | 84 | | 13 | 48 | | 14 | 32 | | 15 | 2 | | 16 | 84 | | 17 | 17 | | 18 | 95 | | 19 | 27 | | 20 | 62 | | 21 | 38 | | 22 | 59 | | 23 | 35 | | 24 | 29 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 101 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 164 | | matches | | |
| 87.91% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 104 | | ratio | 0.019 | | matches | | 0 | "The case file left open, the single, inexplicable piece of evidence on his desk—a raven’s feather that was somehow cold to the touch." | | 1 | "She saw flickers of light—purple, gold, crimson—dancing in the depths." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 412 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.024271844660194174 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.007281553398058253 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 10.47 | | std | 6.16 | | cv | 0.588 | | sampleLengths | | 0 | 17 | | 1 | 17 | | 2 | 12 | | 3 | 5 | | 4 | 19 | | 5 | 16 | | 6 | 3 | | 7 | 10 | | 8 | 16 | | 9 | 18 | | 10 | 9 | | 11 | 7 | | 12 | 6 | | 13 | 10 | | 14 | 13 | | 15 | 9 | | 16 | 12 | | 17 | 16 | | 18 | 2 | | 19 | 3 | | 20 | 1 | | 21 | 8 | | 22 | 13 | | 23 | 9 | | 24 | 3 | | 25 | 18 | | 26 | 6 | | 27 | 11 | | 28 | 13 | | 29 | 4 | | 30 | 5 | | 31 | 17 | | 32 | 15 | | 33 | 11 | | 34 | 6 | | 35 | 29 | | 36 | 2 | | 37 | 1 | | 38 | 11 | | 39 | 11 | | 40 | 7 | | 41 | 20 | | 42 | 16 | | 43 | 3 | | 44 | 17 | | 45 | 12 | | 46 | 14 | | 47 | 24 | | 48 | 4 | | 49 | 16 |
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| 42.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3173076923076923 | | totalSentences | 104 | | uniqueOpeners | 33 | |
| 70.18% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 95 | | matches | | 0 | "Instead, he veered right, towards" | | 1 | "Maybe even answers about Morris." |
| | ratio | 0.021 | |
| 68.42% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 95 | | matches | | 0 | "He landed badly, his ankle" | | 1 | "She was closing the gap." | | 2 | "He darted across the street," | | 3 | "She weaved through the halted" | | 4 | "He knew the warren of" | | 5 | "It stank of stale beer" | | 6 | "Her quarry was halfway down," | | 7 | "She saw the distinctive green" | | 8 | "He fumbled with the handle," | | 9 | "He was trapped." | | 10 | "Her voice was steady, cutting" | | 11 | "He rattled the door again," | | 12 | "His eyes darted past her," | | 13 | "She took another step forward," | | 14 | "He laughed, a ragged, breathless" | | 15 | "He pushed off the door" | | 16 | "She’d boxed him in, and" | | 17 | "She let him go, knowing" | | 18 | "He hooked a sharp left," | | 19 | "Her suspect was halfway down" |
| | ratio | 0.379 | |
| 54.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 95 | | matches | | 0 | "The man’s black coat slapped" | | 1 | "He landed badly, his ankle" | | 2 | "Detective Harlow Quinn followed, her" | | 3 | "She was closing the gap." | | 4 | "The air, thick with the" | | 5 | "He darted across the street," | | 6 | "A horn blared." | | 7 | "Quinn didn’t break pace, her" | | 8 | "She weaved through the halted" | | 9 | "The man glanced back, his" | | 10 | "This was his third zig-zag" | | 11 | "He knew the warren of" | | 12 | "Quinn rounded the corner, her" | | 13 | "The alley was a tight" | | 14 | "It stank of stale beer" | | 15 | "Her quarry was halfway down," | | 16 | "She saw the distinctive green" | | 17 | "A known haunt." | | 18 | "He fumbled with the handle," | | 19 | "He was trapped." |
| | ratio | 0.811 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 95 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 2 | | matches | | 0 | "Her suspect was halfway down the platform, not running anymore, but walking with purpose towards a section of the tunnel that was completely dark." | | 1 | "The case file left open, the single, inexplicable piece of evidence on his desk—a raven’s feather that was somehow cold to the touch." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |