| 91.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 2 | | adverbTags | | 0 | "Evan gestured around [around]" | | 1 | "Evan said quietly [quietly]" |
| | dialogueSentences | 37 | | tagDensity | 0.405 | | leniency | 0.811 | | rawRatio | 0.133 | | effectiveRatio | 0.108 | |
| 88.38% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1291 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "really" | | 2 | "truly" |
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| 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) | |
| 41.91% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1291 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "tracing" | | 1 | "chill" | | 2 | "rhythmic" | | 3 | "familiar" | | 4 | "intensity" | | 5 | "echoed" | | 6 | "whisper" | | 7 | "fleeting" | | 8 | "facade" | | 9 | "silence" | | 10 | "comfortable" | | 11 | "firmly" | | 12 | "warmth" |
| |
| 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 | 57 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 57 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 81 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1291 | | ratio | 0 | | matches | (empty) | |
| 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 | 46 | | wordCount | 847 | | uniqueNames | 9 | | maxNameDensity | 1.77 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Evan" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 2 | | Silas | 5 | | London | 2 | | Rory | 15 | | Cardiff | 3 | | Scotch | 2 | | Evan | 15 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Silas" | | 3 | "Rory" | | 4 | "Evan" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Cardiff" |
| | globalScore | 0.615 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | 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 | 1291 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 39 | | mean | 33.1 | | std | 20.24 | | cv | 0.611 | | sampleLengths | | 0 | 86 | | 1 | 21 | | 2 | 44 | | 3 | 8 | | 4 | 1 | | 5 | 17 | | 6 | 65 | | 7 | 15 | | 8 | 37 | | 9 | 41 | | 10 | 23 | | 11 | 27 | | 12 | 8 | | 13 | 60 | | 14 | 28 | | 15 | 48 | | 16 | 44 | | 17 | 40 | | 18 | 5 | | 19 | 74 | | 20 | 23 | | 21 | 29 | | 22 | 18 | | 23 | 8 | | 24 | 54 | | 25 | 34 | | 26 | 25 | | 27 | 44 | | 28 | 9 | | 29 | 75 | | 30 | 34 | | 31 | 29 | | 32 | 38 | | 33 | 15 | | 34 | 29 | | 35 | 34 | | 36 | 10 | | 37 | 41 | | 38 | 50 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 57 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 129 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 81 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 494 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.030364372469635626 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.012145748987854251 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 81 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 81 | | mean | 15.94 | | std | 9.23 | | cv | 0.579 | | sampleLengths | | 0 | 23 | | 1 | 19 | | 2 | 22 | | 3 | 22 | | 4 | 21 | | 5 | 6 | | 6 | 9 | | 7 | 8 | | 8 | 21 | | 9 | 8 | | 10 | 1 | | 11 | 13 | | 12 | 4 | | 13 | 3 | | 14 | 15 | | 15 | 22 | | 16 | 25 | | 17 | 9 | | 18 | 5 | | 19 | 1 | | 20 | 21 | | 21 | 16 | | 22 | 15 | | 23 | 26 | | 24 | 18 | | 25 | 5 | | 26 | 10 | | 27 | 17 | | 28 | 8 | | 29 | 39 | | 30 | 21 | | 31 | 6 | | 32 | 17 | | 33 | 5 | | 34 | 15 | | 35 | 33 | | 36 | 25 | | 37 | 19 | | 38 | 19 | | 39 | 21 | | 40 | 5 | | 41 | 34 | | 42 | 40 | | 43 | 23 | | 44 | 8 | | 45 | 6 | | 46 | 15 | | 47 | 13 | | 48 | 5 | | 49 | 8 |
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| 51.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.345679012345679 | | totalSentences | 81 | | uniqueOpeners | 28 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 57 | | matches | | 0 | "She kept her collar popped," | | 1 | "She had learned to read" | | 2 | "He didn't tense, but his" | | 3 | "She turned her head." | | 4 | "He dripped water onto the" | | 5 | "He looked older, the boyish" | | 6 | "He carried himself with a" | | 7 | "She didn't offer a smile." | | 8 | "He lingered for a moment," | | 9 | "He leaned in closer, bringing" | | 10 | "He didn't look at her." | | 11 | "It was flat, empty of" | | 12 | "She had gotten it at" | | 13 | "He swallowed hard, the corners" | | 14 | "She stepped out into the" |
| | ratio | 0.263 | |
| 3.86% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 57 | | matches | | 0 | "Rory sat at the far" | | 1 | "She kept her collar popped," | | 2 | "The bell above the heavy" | | 3 | "Rory did not look up" | | 4 | "She had learned to read" | | 5 | "The old operative’s hands paused" | | 6 | "He didn't tense, but his" | | 7 | "A shadow fell over the" | | 8 | "The voice triggered an immediate," | | 9 | "She turned her head." | | 10 | "Evan stood there." | | 11 | "He dripped water onto the" | | 12 | "He looked older, the boyish" | | 13 | "He carried himself with a" | | 14 | "Rory mirrored his gaze, her" | | 15 | "She didn't offer a smile." | | 16 | "Evan slid onto the leather-backed" | | 17 | "Silas set down a tumbler" | | 18 | "He lingered for a moment," | | 19 | "Rory rested her left wrist" |
| | ratio | 0.912 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 44.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 4 | | matches | | 0 | "He carried himself with a polished assurance that hadn't existed back in Cardiff, a veneer of success that screamed of high-end offices and hollow victories." | | 1 | "He lingered for a moment, his gaze shifting between Rory’s impassive face and Evan’s oblivious grin, before retreating to the till, his left leg dragging slight…" | | 2 | "Evan stared into his Scotch, his fingers tracing the rim of his glass, mimicking her earlier movement." | | 3 | "Rory pulled her arm back, adjusting her coat, placing her hands firmly in her pockets." |
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| 58.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 2 | | matches | | 0 | "Evan countered, his voice dropping to a harsh whisper" | | 1 | "Evan continued, his eyes still fixed on the amber liquid" |
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| 95.95% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Evan laughed (laugh)" | | 1 | "Evan continued (continue)" |
| | dialogueSentences | 37 | | tagDensity | 0.108 | | leniency | 0.216 | | rawRatio | 0.5 | | effectiveRatio | 0.108 | |