| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 27 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 56 | | tagDensity | 0.482 | | leniency | 0.964 | | rawRatio | 0.037 | | effectiveRatio | 0.036 | |
| 84.04% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1253 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slightly" | | 1 | "softly" | | 2 | "really" |
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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) | |
| 32.16% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1253 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "weight" | | 1 | "flickered" | | 2 | "echoed" | | 3 | "scanning" | | 4 | "flicked" | | 5 | "trembled" | | 6 | "echoing" | | 7 | "silence" | | 8 | "whisper" | | 9 | "pulse" | | 10 | "quickened" | | 11 | "loomed" | | 12 | "reverberated" | | 13 | "echo" | | 14 | "footsteps" |
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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 | 77 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 77 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1253 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 767 | | uniqueNames | 4 | | maxNameDensity | 1.96 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | | persons | | | places | (empty) | | globalScore | 0.522 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "crack that seemed to split the night" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1253 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 84.11% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 40 | | mean | 31.33 | | std | 13.92 | | cv | 0.444 | | sampleLengths | | 0 | 80 | | 1 | 63 | | 2 | 11 | | 3 | 25 | | 4 | 20 | | 5 | 30 | | 6 | 41 | | 7 | 24 | | 8 | 35 | | 9 | 35 | | 10 | 36 | | 11 | 37 | | 12 | 34 | | 13 | 40 | | 14 | 37 | | 15 | 33 | | 16 | 13 | | 17 | 20 | | 18 | 33 | | 19 | 30 | | 20 | 45 | | 21 | 39 | | 22 | 40 | | 23 | 8 | | 24 | 15 | | 25 | 21 | | 26 | 33 | | 27 | 20 | | 28 | 19 | | 29 | 36 | | 30 | 36 | | 31 | 12 | | 32 | 34 | | 33 | 36 | | 34 | 26 | | 35 | 27 | | 36 | 23 | | 37 | 51 | | 38 | 43 | | 39 | 12 |
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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 | 139 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 109 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 496 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 15 | | adverbRatio | 0.03024193548387097 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.004032258064516129 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 11.5 | | std | 6.33 | | cv | 0.55 | | sampleLengths | | 0 | 16 | | 1 | 18 | | 2 | 23 | | 3 | 23 | | 4 | 30 | | 5 | 12 | | 6 | 21 | | 7 | 3 | | 8 | 8 | | 9 | 11 | | 10 | 14 | | 11 | 14 | | 12 | 6 | | 13 | 2 | | 14 | 21 | | 15 | 7 | | 16 | 17 | | 17 | 24 | | 18 | 10 | | 19 | 14 | | 20 | 12 | | 21 | 15 | | 22 | 8 | | 23 | 20 | | 24 | 15 | | 25 | 11 | | 26 | 15 | | 27 | 10 | | 28 | 3 | | 29 | 22 | | 30 | 12 | | 31 | 3 | | 32 | 10 | | 33 | 21 | | 34 | 8 | | 35 | 18 | | 36 | 14 | | 37 | 14 | | 38 | 16 | | 39 | 7 | | 40 | 8 | | 41 | 7 | | 42 | 11 | | 43 | 7 | | 44 | 13 | | 45 | 5 | | 46 | 10 | | 47 | 5 | | 48 | 3 | | 49 | 18 |
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| 43.58% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.28440366972477066 | | totalSentences | 109 | | uniqueOpeners | 31 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 61.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 73 | | matches | | 0 | "She brushed a damp strand" | | 1 | "He polished a glass with" | | 2 | "He glanced up as she" | | 3 | "She laughed, a short, sharp" | | 4 | "She slipped onto a stool," | | 5 | "He set the glass down" | | 6 | "She stared at the scar" | | 7 | "He let the name hang" | | 8 | "She lifted the glass, took" | | 9 | "He leaned in, lowering his" | | 10 | "She stared at the wall" | | 11 | "He tapped his signet ring" | | 12 | "He turned back to Rory" | | 13 | "She stood, the chair scraping" | | 14 | "He gestured toward the hidden" | | 15 | "She pressed a palm against" | | 16 | "He sighed, the sound like" | | 17 | "He hesitated, then slipped on" | | 18 | "He lifted his glass again" | | 19 | "She lifted her own glass," |
| | ratio | 0.397 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 72 | | totalSentences | 73 | | matches | | 0 | "Rory shoved the heavy door" | | 1 | "The neon sign above the" | | 2 | "A low hum of chatter" | | 3 | "She brushed a damp strand" | | 4 | "Silas stood behind the bar," | | 5 | "He polished a glass with" | | 6 | "He glanced up as she" | | 7 | "She laughed, a short, sharp" | | 8 | "Silas tapped the rim of" | | 9 | "She slipped onto a stool," | | 10 | "Silas leaned against the bar," | | 11 | "Rory replied, her voice flat" | | 12 | "Silas poured a measure of" | | 13 | "He set the glass down" | | 14 | "She stared at the scar" | | 15 | "He let the name hang" | | 16 | "Rory’s jaw tightened." | | 17 | "She lifted the glass, took" | | 18 | "He leaned in, lowering his" | | 19 | "Rory’s fingers drummed a rhythm" |
| | ratio | 0.986 | |
| 68.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 73 | | matches | | 0 | "Before she could reply, a" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "The sound reverberated off the brick walls, a deafening crack that seemed to split the night." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 27 | | uselessAdditionCount | 8 | | matches | | 0 | "She slipped, the wood creaking under her weight" | | 1 | "Rory replied, her voice flat" | | 2 | "She stood, the chair scraping the floor" | | 3 | "She lifted, but her hand trembled" | | 4 | "Silas asked, his voice low" | | 5 | "He leaned, voice dropping to a whisper" | | 6 | "Silas reached, his fingers brushing the edge of a leather-bound envelope" | | 7 | "she hissed, eyes darting to the door" |
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| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 7 | | fancyTags | | 0 | "a voice muttered (mutter)" | | 1 | "She pressed (press)" | | 2 | "He sighed (sigh)" | | 3 | "Silas snapped (snap)" | | 4 | "Silas shouted (shout)" | | 5 | "she hissed (hiss)" | | 6 | "he whispered (whisper)" |
| | dialogueSentences | 56 | | tagDensity | 0.196 | | leniency | 0.393 | | rawRatio | 0.636 | | effectiveRatio | 0.25 | |