| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 92.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1379 | | 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) | |
| 23.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1379 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "scanning" | | 1 | "stomach" | | 2 | "churned" | | 3 | "reminder" | | 4 | "silence" | | 5 | "rhythmic" | | 6 | "perfect" | | 7 | "could feel" | | 8 | "weight" | | 9 | "chill" | | 10 | "crystallized" | | 11 | "trembled" | | 12 | "pulsed" | | 13 | "warmth" | | 14 | "whisper" | | 15 | "silk" | | 16 | "loomed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 122 | | matches | (empty) | |
| 84.31% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 122 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 122 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1379 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1379 | | uniqueNames | 15 | | maxNameDensity | 0.58 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | London | 2 | | November | 1 | | Carter | 1 | | Isolde | 1 | | Richmond | 2 | | Park | 2 | | Heartstone | 4 | | Hel | 1 | | Grove | 1 | | Fae-touched | 1 | | Silas | 2 | | Eva | 1 | | Rory | 8 | | English | 1 | | Cardiff | 1 |
| | persons | | 0 | "Carter" | | 1 | "Isolde" | | 2 | "Heartstone" | | 3 | "Silas" | | 4 | "Eva" | | 5 | "Rory" |
| | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Hel" | | 4 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 93.82% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 89 | | glossingSentenceCount | 2 | | matches | | 0 | "as if sensing her fear" | | 1 | "silhouette that seemed to drink the faint light around it" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.175 | | wordCount | 1379 | | matches | | 0 | "Not the natural chill of the park, but a sudden, localized freeze" | | 1 | "Not the red of the stone, but a dark, hollowed-out eye staring back at her from the metal" | | 2 | "not with air, but with the feeling of dry paper dragging across silk" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 122 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 47.55 | | std | 27.99 | | cv | 0.589 | | sampleLengths | | 0 | 95 | | 1 | 69 | | 2 | 41 | | 3 | 123 | | 4 | 51 | | 5 | 45 | | 6 | 27 | | 7 | 75 | | 8 | 52 | | 9 | 3 | | 10 | 75 | | 11 | 23 | | 12 | 75 | | 13 | 20 | | 14 | 50 | | 15 | 58 | | 16 | 10 | | 17 | 52 | | 18 | 56 | | 19 | 88 | | 20 | 29 | | 21 | 3 | | 22 | 49 | | 23 | 40 | | 24 | 2 | | 25 | 54 | | 26 | 46 | | 27 | 28 | | 28 | 40 |
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| 96.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 122 | | matches | | 0 | "was gone" | | 1 | "was reattached" | | 2 | "was torn" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 12 | | totalVerbs | 229 | | matches | | 0 | "was tearing" | | 1 | "was shifting" | | 2 | "was twitching" | | 3 | "was screaming" | | 4 | "was reacting" | | 5 | "wasn't just reacting" | | 6 | "were wading" | | 7 | "were folding" | | 8 | "were spinning" | | 9 | "were passing" | | 10 | "weren't speaking" | | 11 | "were speaking" |
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| 72.60% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 3 | | flaggedSentences | 3 | | totalSentences | 122 | | ratio | 0.025 | | matches | | 0 | "The anomaly sat in the discrepancy; the wind moved around the trees but left the ground untouched." | | 1 | "It wasn't just reacting to the portal; it was reacting to a presence." | | 2 | "It didn't walk; it glided, sliding across the moss without disturbing the grass beneath it." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1383 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 38 | | adverbRatio | 0.0274765003615329 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.0072306579898770785 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 122 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 122 | | mean | 11.3 | | std | 7.74 | | cv | 0.685 | | sampleLengths | | 0 | 14 | | 1 | 35 | | 2 | 16 | | 3 | 30 | | 4 | 8 | | 5 | 16 | | 6 | 19 | | 7 | 26 | | 8 | 5 | | 9 | 22 | | 10 | 14 | | 11 | 4 | | 12 | 9 | | 13 | 13 | | 14 | 13 | | 15 | 36 | | 16 | 6 | | 17 | 16 | | 18 | 18 | | 19 | 8 | | 20 | 5 | | 21 | 13 | | 22 | 16 | | 23 | 4 | | 24 | 13 | | 25 | 5 | | 26 | 23 | | 27 | 17 | | 28 | 4 | | 29 | 10 | | 30 | 13 | | 31 | 17 | | 32 | 9 | | 33 | 17 | | 34 | 11 | | 35 | 4 | | 36 | 17 | | 37 | 10 | | 38 | 12 | | 39 | 15 | | 40 | 15 | | 41 | 3 | | 42 | 3 | | 43 | 3 | | 44 | 24 | | 45 | 32 | | 46 | 13 | | 47 | 4 | | 48 | 19 | | 49 | 6 |
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| 25.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 30 | | diversityRatio | 0.22950819672131148 | | totalSentences | 122 | | uniqueOpeners | 28 | |
| 28.25% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 118 | | matches | | 0 | "Then, the temperature dropped." |
| | ratio | 0.008 | |
| 36.95% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 118 | | matches | | 0 | "She adjusted the silver chain" | | 1 | "She knew the stone’s behavior" | | 2 | "They glowed faintly, their petals" | | 3 | "She checked her watch." | | 4 | "She wasn’t sure how long" | | 5 | "She had come for answers," | | 6 | "She looked at her left" | | 7 | "It was a physical anchor," | | 8 | "She rubbed the smooth skin" | | 9 | "It wasn't the snap of" | | 10 | "It was the sound of" | | 11 | "It was too even." | | 12 | "She took another step." | | 13 | "It wasn't just reacting to" | | 14 | "It didn't move like a" | | 15 | "It unspooled, stretching out along" | | 16 | "She swallowed hard, the taste" | | 17 | "She thought of Eva, how" | | 18 | "She thought of the flat" | | 19 | "She tried to recall the" |
| | ratio | 0.458 | |
| 23.56% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 103 | | totalSentences | 118 | | matches | | 0 | "The wind died the moment" | | 1 | "One second, the bite of" | | 2 | "Aurora Carter pulled her scarf" | | 3 | "This was Isolde’s grove, though" | | 4 | "She adjusted the silver chain" | | 5 | "The Heartstone pendant pressed against" | | 6 | "She knew the stone’s behavior" | | 7 | "The Grove was Fae-touched, a" | | 8 | "Rory took a step forward." | | 9 | "The grass beneath her boots" | | 10 | "They glowed faintly, their petals" | | 11 | "She checked her watch." | | 12 | "The second hand was twitching," | | 13 | "An hour inside could be" | | 14 | "She wasn’t sure how long" | | 15 | "She had come for answers," | | 16 | "She looked at her left" | | 17 | "The small crescent-shaped scar from" | | 18 | "It was a physical anchor," | | 19 | "She rubbed the smooth skin" |
| | ratio | 0.873 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 118 | | matches | | 0 | "Now she felt exposed, her" | | 1 | "If she moved, would it" | | 2 | "If she stood still, would" |
| | ratio | 0.025 | |
| 65.93% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 7 | | matches | | 0 | "One second, the bite of a London November was tearing at the collar of her coat, and the next, the air was still, thick with a humidity that smelled of wet eart…" | | 1 | "She had come for answers, a favor for Silas regarding the delivery route that led to this place, but the rational part of her mind, the pre-law part, was scream…" | | 2 | "She tried to recall the path back to the boundary, but the trees looked the same on every side, identical oaks twisting their branches toward a sky that had los…" | | 3 | "It had no face, but she felt its gaze boring into her, assessing, judging." | | 4 | "She kicked off the ground, scrambling backward, her hand finding the silver chain." | | 5 | "She scrambled through the moss, her coat tangling around her legs, her breath tearing at her throat." | | 6 | "She stayed on her knees until dawn, the cold seeping into her bones, waiting for the sensation of not being alone to fade, though she knew, with a certainty tha…" |
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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 | |