| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Silas finally said [finally]" |
| | dialogueSentences | 44 | | tagDensity | 0.386 | | leniency | 0.773 | | rawRatio | 0.059 | | effectiveRatio | 0.045 | |
| 76.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1054 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "slowly" | | 2 | "gently" |
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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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1054 | | totalAiIsms | 24 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "scanning" | | 1 | "familiar" | | 2 | "chill" | | 3 | "furrowing" | | 4 | "unspoken" | | 5 | "weight" | | 6 | "silence" | | 7 | "stark" | | 8 | "flicked" | | 9 | "dancing" | | 10 | "depths" | | 11 | "flickered" | | 12 | "reminder" | | 13 | "perfect" | | 14 | "tension" | | 15 | "unwavering" | | 16 | "flicker" | | 17 | "tinged" |
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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 | 58 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 58 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1049 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 27.72% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 39 | | wordCount | 736 | | uniqueNames | 8 | | maxNameDensity | 2.45 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Friday | 1 | | Blackwood | 1 | | Aurora | 1 | | Carter | 1 | | Rory | 15 | | Silas | 18 |
| | persons | | 0 | "Raven" | | 1 | "Blackwood" | | 2 | "Aurora" | | 3 | "Carter" | | 4 | "Rory" | | 5 | "Silas" |
| | places | (empty) | | globalScore | 0.277 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | 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 | 1049 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 84 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 31.79 | | std | 16.39 | | cv | 0.516 | | sampleLengths | | 0 | 80 | | 1 | 20 | | 2 | 54 | | 3 | 24 | | 4 | 18 | | 5 | 31 | | 6 | 30 | | 7 | 20 | | 8 | 64 | | 9 | 9 | | 10 | 25 | | 11 | 27 | | 12 | 28 | | 13 | 28 | | 14 | 34 | | 15 | 25 | | 16 | 23 | | 17 | 19 | | 18 | 22 | | 19 | 23 | | 20 | 17 | | 21 | 36 | | 22 | 28 | | 23 | 22 | | 24 | 68 | | 25 | 26 | | 26 | 37 | | 27 | 27 | | 28 | 33 | | 29 | 23 | | 30 | 31 | | 31 | 26 | | 32 | 71 |
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| 93.16% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 58 | | matches | | 0 | "been replaced" | | 1 | "was tinged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 126 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 84 | | ratio | 0 | | matches | (empty) | |
| 65.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 296 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.08783783783783784 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.010135135135135136 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 12.49 | | std | 6.08 | | cv | 0.487 | | sampleLengths | | 0 | 10 | | 1 | 22 | | 2 | 21 | | 3 | 27 | | 4 | 20 | | 5 | 16 | | 6 | 22 | | 7 | 16 | | 8 | 6 | | 9 | 15 | | 10 | 3 | | 11 | 12 | | 12 | 6 | | 13 | 14 | | 14 | 9 | | 15 | 8 | | 16 | 9 | | 17 | 18 | | 18 | 3 | | 19 | 19 | | 20 | 1 | | 21 | 17 | | 22 | 9 | | 23 | 25 | | 24 | 13 | | 25 | 9 | | 26 | 15 | | 27 | 10 | | 28 | 7 | | 29 | 20 | | 30 | 18 | | 31 | 10 | | 32 | 16 | | 33 | 12 | | 34 | 7 | | 35 | 18 | | 36 | 9 | | 37 | 15 | | 38 | 10 | | 39 | 10 | | 40 | 13 | | 41 | 7 | | 42 | 12 | | 43 | 9 | | 44 | 13 | | 45 | 10 | | 46 | 10 | | 47 | 3 | | 48 | 10 | | 49 | 7 |
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| 72.22% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.44047619047619047 | | totalSentences | 84 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 95.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 58 | | matches | | 0 | "Her voice was steady, guarded" | | 1 | "She moved towards the bar," | | 2 | "She paused, her brow furrowing" | | 3 | "He poured a generous measure" | | 4 | "They lapsed into silence, the" | | 5 | "Her face, once open and" | | 6 | "She paused, her gaze drifting" | | 7 | "He paused, his gaze searching" | | 8 | "He poured himself a measure" | | 9 | "She drained the last of" | | 10 | "She shook her head, her" | | 11 | "She trailed off, her shoulders" | | 12 | "She managed a faint smile," | | 13 | "He squeezed her arm gently," | | 14 | "She paused, her gaze flicking" | | 15 | "She hesitated, her eyes searching" | | 16 | "He paused, his lips curving" | | 17 | "It was good to see" |
| | ratio | 0.31 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 58 | | matches | | 0 | "The Raven's Nest was unusually" | | 1 | "Silas Blackwood surveyed the room" | | 2 | "The familiar creak of the" | | 3 | "The name left" | | 4 | "Aurora Carter froze, her bright" | | 5 | "Her voice was steady, guarded" | | 6 | "She moved towards the bar," | | 7 | "Silas studied her, the wheels" | | 8 | "Rory shrugged, her gaze flicking" | | 9 | "She paused, her brow furrowing" | | 10 | "Silas nodded, understanding the unspoken" | | 11 | "He poured a generous measure" | | 12 | "Rory's lips curved into a" | | 13 | "They lapsed into silence, the" | | 14 | "Silas watched her, noting the" | | 15 | "The straight, shoulder-length black hair" | | 16 | "Her face, once open and" | | 17 | "Silas finally said, breaking the" | | 18 | "Rory's eyes flicked up to" | | 19 | "Silas chuckled, the sound low" |
| | ratio | 0.931 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 58 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 1 | | matches | | 0 | "For a moment, she was that same twenty-year-old girl who had stumbled into his bar all those years ago, terrified and alone." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 12 | | matches | | 0 | "The name left, a hint of surprise colouring his low, gravelly voice" | | 1 | "She paused, her brow furrowing slightly" | | 2 | "Rory took, the liquid amber catching the soft light" | | 3 | "She paused, her gaze drifting towards the grimy windows" | | 4 | "Silas followed, his own thoughts drifting back to the past" | | 5 | "He paused, his gaze searching her face" | | 6 | "She drained, the amber liquid burning down her throat" | | 7 | "She trailed, her shoulders sagging slightly" | | 8 | "He squeezed, his own eyes softening" | | 9 | "She paused, her gaze flicking towards the door" | | 10 | "She hesitated, her eyes searching his face" | | 11 | "He paused, his lips curving into a faint smile" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.023 | | leniency | 0.045 | | rawRatio | 0 | | effectiveRatio | 0 | |