| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 83.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 895 | | totalAiIsmAdverbs | 3 | | 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) | |
| 38.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 895 | | totalAiIsms | 11 | | found | | 0 | | | 1 | | word | "the last thing" | | count | 1 |
| | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | |
| | highlights | | 0 | "pulsed" | | 1 | "the last thing" | | 2 | "flicker" | | 3 | "silence" | | 4 | "scanned" | | 5 | "footsteps" | | 6 | "reminder" | | 7 | "whisper" | | 8 | "searing" | | 9 | "rhythmic" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "clenched jaw/fists" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 177 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 177 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 183 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 8 | | markdownWords | 18 | | totalWords | 884 | | ratio | 0.02 | | matches | | 0 | "present" | | 1 | "Come." | | 2 | "I found it, Rory. The grove. Just like in the stories." | | 3 | "Seams." | | 4 | "hum" | | 5 | "teeth." | | 6 | "there." | | 7 | "RUN." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 864 | | uniqueNames | 16 | | maxNameDensity | 0.93 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Heartstone | 3 | | Pembroke | 1 | | Lodge | 1 | | Isolde | 1 | | Eva | 5 | | Tuesday | 1 | | Rory | 8 | | Stories | 1 | | Dymas | 1 | | Fae | 1 | | Grove | 1 | | Evan | 1 | | Like | 5 | | Pale | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Isolde" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Evan" | | 5 | "Like" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Pembroke" | | 3 | "Stories" | | 4 | "Fae" | | 5 | "Grove" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 2.262 | | wordCount | 884 | | matches | | 0 | "No footprints but" | | 1 | "not wet, still but not quiet" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 183 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 92 | | mean | 9.61 | | std | 13.47 | | cv | 1.402 | | sampleLengths | | 0 | 7 | | 1 | 78 | | 2 | 3 | | 3 | 33 | | 4 | 7 | | 5 | 34 | | 6 | 55 | | 7 | 5 | | 8 | 37 | | 9 | 40 | | 10 | 3 | | 11 | 39 | | 12 | 5 | | 13 | 14 | | 14 | 1 | | 15 | 8 | | 16 | 3 | | 17 | 29 | | 18 | 2 | | 19 | 36 | | 20 | 3 | | 21 | 19 | | 22 | 3 | | 23 | 33 | | 24 | 2 | | 25 | 4 | | 26 | 2 | | 27 | 1 | | 28 | 4 | | 29 | 3 | | 30 | 7 | | 31 | 42 | | 32 | 5 | | 33 | 3 | | 34 | 2 | | 35 | 1 | | 36 | 2 | | 37 | 7 | | 38 | 14 | | 39 | 2 | | 40 | 1 | | 41 | 4 | | 42 | 24 | | 43 | 5 | | 44 | 1 | | 45 | 15 | | 46 | 9 | | 47 | 22 | | 48 | 5 | | 49 | 3 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 177 | | matches | | 0 | "been chained" | | 1 | "been made" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 152 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 183 | | ratio | 0.06 | | matches | | 0 | "The gate to Richmond Park had been chained and padlocked at ten sharp—she’d watched the warden do it herself from the back of her moped, headlights cutting through the drizzle." | | 1 | "The air thickened fast—damp but not wet, still but not quiet." | | 2 | "From the lullabies their nan used to sing—half-remembered verses about silver roots and stolen time." | | 3 | "The standing stones came into view—four ancient oaks, arranged in a rough square, their roots fused into a low ring of earth." | | 4 | "Wildflowers should have blanketed the ground—purple foxgloves, white starflowers, golden torch lilies—bloomed eternal under the grove’s magic." | | 5 | "The air smelled of iron and damp moss, but underneath—something sweet." | | 6 | "Then—a sound." | | 7 | "She clenched her fists, focused on the scar on her wrist—the crescent dent from when Evan shoved her into the glass coffee table two years ago." | | 8 | "Then—" | | 9 | "From the trees, a sound began—soft, rhythmic." | | 10 | "Then—" |
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| 96.09% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 877 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.04446978335233751 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004561003420752566 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 183 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 183 | | mean | 4.83 | | std | 4.87 | | cv | 1.008 | | sampleLengths | | 0 | 7 | | 1 | 10 | | 2 | 30 | | 3 | 14 | | 4 | 5 | | 5 | 14 | | 6 | 5 | | 7 | 3 | | 8 | 6 | | 9 | 11 | | 10 | 9 | | 11 | 2 | | 12 | 2 | | 13 | 2 | | 14 | 1 | | 15 | 7 | | 16 | 11 | | 17 | 8 | | 18 | 6 | | 19 | 2 | | 20 | 2 | | 21 | 2 | | 22 | 3 | | 23 | 3 | | 24 | 9 | | 25 | 18 | | 26 | 25 | | 27 | 5 | | 28 | 8 | | 29 | 9 | | 30 | 13 | | 31 | 2 | | 32 | 5 | | 33 | 3 | | 34 | 15 | | 35 | 8 | | 36 | 2 | | 37 | 3 | | 38 | 9 | | 39 | 3 | | 40 | 4 | | 41 | 16 | | 42 | 2 | | 43 | 8 | | 44 | 8 | | 45 | 1 | | 46 | 5 | | 47 | 8 | | 48 | 1 | | 49 | 3 |
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| 55.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.366120218579235 | | totalSentences | 183 | | uniqueOpeners | 67 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 103 | | matches | | 0 | "Just like in the stories.*" | | 1 | "Just the hum, rising a" | | 2 | "Just that *hum*, thrumming in" | | 3 | "Just stood, hands at her" | | 4 | "Then another sound." | | 5 | "Just beyond the ring of" |
| | ratio | 0.058 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 103 | | matches | | 0 | "She glanced over her shoulder." | | 1 | "She stepped through." | | 2 | "Her boots crunched on frost-brittle" | | 3 | "She touched it through her" | | 4 | "She hadn’t wanted to come." | | 5 | "She turned right." | | 6 | "She snatched her hand back." | | 7 | "She walked faster." | | 8 | "She scanned the trees." | | 9 | "Her breath came shallow." | | 10 | "She clenched her fists, focused" | | 11 | "She stepped into the grove." | | 12 | "She gasped, dropped it." | | 13 | "She bent to examine them." | | 14 | "She turned slowly." | | 15 | "Her ears popped." | | 16 | "Her phone buzzed in her" | | 17 | "She jerked, fumbled it out." |
| | ratio | 0.175 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 103 | | matches | | 0 | "The lock clicked open with" | | 1 | "Rory froze, the brass plate" | | 2 | "The gate to Richmond Park" | | 3 | "She glanced over her shoulder." | | 4 | "The road behind her was" | | 5 | "She stepped through." | | 6 | "Her boots crunched on frost-brittle" | | 7 | "The air thickened fast—damp but" | | 8 | "A hum ran under everything," | | 9 | "The Heartstone pendant warmed against" | | 10 | "She touched it through her" | | 11 | "The gem pulsed once, soft" | | 12 | "Crimson light bled through the" | | 13 | "The path forked." | | 14 | "The grove was south, past" | | 15 | "A scrap slipped under her" | | 16 | "She hadn’t wanted to come." | | 17 | "Stories from childhood." | | 18 | "She turned right." | | 19 | "The trees closed in." |
| | ratio | 0.592 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 103 | | matches | | 0 | "Now the chain hung slack," | | 1 | "Before the pendant." | | 2 | "Before she learned that some" | | 3 | "Now the soil was bare," | | 4 | "To her left." |
| | ratio | 0.049 | |
| 74.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 21 | | technicalSentenceCount | 2 | | matches | | 0 | "Oaks, massive and gnarled, their bark split with fissures that looked too deliberate to be natural." | | 1 | "The Heartstone’s glow intensified, casting long shadows that didn’t match the trees." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |