| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1285 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 49.42% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1285 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "silence" | | 3 | "trembled" | | 4 | "echoed" | | 5 | "echo" | | 6 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 126 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 126 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 163 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1278 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.44% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1063 | | uniqueNames | 11 | | maxNameDensity | 1.41 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Park | 1 | | London | 2 | | Eva | 7 | | Follow | 1 | | Silas | 2 | | Cardiff | 1 | | Welsh | 1 | | Rory | 15 | | Service | 1 | | Unknown | 1 | | Caller | 1 |
| | persons | | | places | | 0 | "Park" | | 1 | "London" | | 2 | "Cardiff" |
| | globalScore | 0.794 | | windowScore | 0.833 | |
| 79.58% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like a face, or a handprint" | | 1 | "sounded like her own voice whispered" |
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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 | 1278 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 163 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 83 | | mean | 15.4 | | std | 19.77 | | cv | 1.284 | | sampleLengths | | 0 | 74 | | 1 | 52 | | 2 | 8 | | 3 | 21 | | 4 | 8 | | 5 | 3 | | 6 | 9 | | 7 | 8 | | 8 | 27 | | 9 | 7 | | 10 | 2 | | 11 | 19 | | 12 | 20 | | 13 | 21 | | 14 | 4 | | 15 | 4 | | 16 | 3 | | 17 | 2 | | 18 | 53 | | 19 | 5 | | 20 | 69 | | 21 | 6 | | 22 | 1 | | 23 | 18 | | 24 | 4 | | 25 | 14 | | 26 | 73 | | 27 | 12 | | 28 | 9 | | 29 | 7 | | 30 | 15 | | 31 | 23 | | 32 | 54 | | 33 | 18 | | 34 | 1 | | 35 | 5 | | 36 | 4 | | 37 | 13 | | 38 | 5 | | 39 | 81 | | 40 | 3 | | 41 | 5 | | 42 | 21 | | 43 | 1 | | 44 | 19 | | 45 | 6 | | 46 | 3 | | 47 | 3 | | 48 | 84 | | 49 | 5 |
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| 99.69% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 126 | | matches | | 0 | "been stacked" | | 1 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 173 | | matches | (empty) | |
| 20.16% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 1 | | flaggedSentences | 7 | | totalSentences | 163 | | ratio | 0.043 | | matches | | 0 | "Richmond Park held its usual night-time hush, but the air tasted wrong—metal and old pennies." | | 1 | "The silver chain caught the light from a distant streetlamp; the crimson gemstone held a faint inner glow, thumbnail-sized, warm as living skin." | | 2 | "Wildflowers crowded their bases, absurd in the cold—daisies, bluebells, foxgloves, all blooming out of season." | | 3 | "The distant hum of traffic from the A3 cut off, not faded—gone, as if a switch had flipped." | | 4 | "Something moved at the edge of her vision—a pale shape, tall and narrow, slipping behind a trunk." | | 5 | "Her scar—the small crescent on her left wrist—itched." | | 6 | "From the corner of her eye, another shape moved—then another." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1075 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.025116279069767444 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004651162790697674 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 163 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 163 | | mean | 7.84 | | std | 6.05 | | cv | 0.772 | | sampleLengths | | 0 | 13 | | 1 | 7 | | 2 | 15 | | 3 | 16 | | 4 | 7 | | 5 | 16 | | 6 | 4 | | 7 | 23 | | 8 | 17 | | 9 | 8 | | 10 | 8 | | 11 | 15 | | 12 | 2 | | 13 | 4 | | 14 | 8 | | 15 | 3 | | 16 | 9 | | 17 | 8 | | 18 | 27 | | 19 | 7 | | 20 | 2 | | 21 | 2 | | 22 | 17 | | 23 | 20 | | 24 | 4 | | 25 | 17 | | 26 | 4 | | 27 | 4 | | 28 | 3 | | 29 | 2 | | 30 | 4 | | 31 | 8 | | 32 | 20 | | 33 | 15 | | 34 | 6 | | 35 | 5 | | 36 | 14 | | 37 | 3 | | 38 | 18 | | 39 | 2 | | 40 | 2 | | 41 | 2 | | 42 | 6 | | 43 | 5 | | 44 | 12 | | 45 | 5 | | 46 | 6 | | 47 | 1 | | 48 | 18 | | 49 | 4 |
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| 42.02% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.2822085889570552 | | totalSentences | 163 | | uniqueOpeners | 46 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 111 | | matches | | 0 | "Then, beneath it, a sound." | | 1 | "Only an oak, its bark" | | 2 | "Then, from her right, Eva's" | | 3 | "Then her own voice, from" | | 4 | "Pale, tall, mimicked human shapes," |
| | ratio | 0.045 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 111 | | matches | | 0 | "She touched the pendant beneath" | | 1 | "She pulled it free." | | 2 | "It had arrived in a" | | 3 | "She shoved the pendant back" | | 4 | "She thumbed Silas's number." | | 5 | "She started walking, gravel crunching" | | 6 | "She ended the call." | | 7 | "She shoved the phone into" | | 8 | "She stepped between two stones." | | 9 | "It rang twice, then stopped." | | 10 | "Her voice sounded too loud," | | 11 | "She moved deeper." | | 12 | "She turned her head." | | 13 | "Her own words echoed back," | | 14 | "It had come from behind" | | 15 | "She turned, one hand out," | | 16 | "She snatched her hand back." | | 17 | "She drew it out." | | 18 | "Her throat closed." | | 19 | "She called louder this time." |
| | ratio | 0.288 | |
| 27.57% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 96 | | totalSentences | 111 | | matches | | 0 | "The bike lock clicked shut" | | 1 | "Rory straightened, breath smoking in" | | 2 | "Richmond Park held its usual" | | 3 | "She touched the pendant beneath" | | 4 | "The heartstone pulsed against her" | | 5 | "She pulled it free." | | 6 | "The silver chain caught the" | | 7 | "It had arrived in a" | | 8 | "The card inside had read:" | | 9 | "She shoved the pendant back" | | 10 | "She thumbed Silas's number." | | 11 | "Rory's mouth twitched." | | 12 | "She started walking, gravel crunching" | | 13 | "Rory reached the treeline." | | 14 | "The oaks ahead twisted into" | | 15 | "The line crackled." | | 16 | "She ended the call." | | 17 | "She shoved the phone into" | | 18 | "The ancient oak standing stones" | | 19 | "Wildflowers crowded their bases, absurd" |
| | ratio | 0.865 | |
| 45.05% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 111 | | matches | | 0 | "Now the warmth tugged, insistent," |
| | ratio | 0.009 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "The heartstone pulsed against her sternum, a steady heat that hadn't been there ten minutes ago." | | 1 | "Her voice sounded too loud, too flat, as if the grove had swallowed the soft edges of sound." | | 2 | "Rory followed, stepping over roots that felt too much like knuckles under her boots." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |