| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 7 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 24 | | tagDensity | 0.292 | | leniency | 0.583 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1235 | | 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) | |
| 63.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1235 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "throbbed" | | 1 | "uncanny" | | 2 | "silence" | | 3 | "echo" | | 4 | "searing" | | 5 | "could feel" | | 6 | "weight" | | 7 | "pulse" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 106 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 106 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 35 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 7 | | totalWords | 1235 | | ratio | 0.006 | | matches | | 0 | "The grove." | | 1 | "Time moves differently here." | | 2 | "You" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 14 | | wordCount | 1081 | | uniqueNames | 8 | | maxNameDensity | 0.65 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 7 | | Silas | 1 | | Park | 1 | | Light | 1 | | Britain | 1 | | Less | 1 | | London | 1 | | Thames | 1 |
| | persons | | 0 | "Aurora" | | 1 | "Silas" | | 2 | "Light" |
| | places | | 0 | "Park" | | 1 | "London" | | 2 | "Thames" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 1 | | matches | | 0 | "tasted like copper in her mouth" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.81 | | wordCount | 1235 | | matches | | 0 | "Not out loud, but in her bones" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 124 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 22.05 | | std | 19.48 | | cv | 0.883 | | sampleLengths | | 0 | 52 | | 1 | 15 | | 2 | 30 | | 3 | 7 | | 4 | 43 | | 5 | 51 | | 6 | 3 | | 7 | 25 | | 8 | 21 | | 9 | 43 | | 10 | 2 | | 11 | 16 | | 12 | 5 | | 13 | 46 | | 14 | 19 | | 15 | 5 | | 16 | 8 | | 17 | 56 | | 18 | 4 | | 19 | 48 | | 20 | 12 | | 21 | 28 | | 22 | 5 | | 23 | 1 | | 24 | 51 | | 25 | 3 | | 26 | 50 | | 27 | 1 | | 28 | 7 | | 29 | 48 | | 30 | 3 | | 31 | 4 | | 32 | 35 | | 33 | 29 | | 34 | 31 | | 35 | 7 | | 36 | 5 | | 37 | 76 | | 38 | 31 | | 39 | 4 | | 40 | 45 | | 41 | 4 | | 42 | 4 | | 43 | 4 | | 44 | 46 | | 45 | 4 | | 46 | 35 | | 47 | 4 | | 48 | 51 | | 49 | 6 |
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| 92.02% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 106 | | matches | | 0 | "was supposed" | | 1 | "been closed" | | 2 | "was gone" | | 3 | "been gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 184 | | matches | | 0 | "was standing" | | 1 | "was begging" | | 2 | "was glowing" | | 3 | "was falling" | | 4 | "was breaking" | | 5 | "were blooming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 124 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 492 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.028455284552845527 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.008130081300813009 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 9.96 | | std | 7.79 | | cv | 0.782 | | sampleLengths | | 0 | 13 | | 1 | 17 | | 2 | 6 | | 3 | 16 | | 4 | 15 | | 5 | 23 | | 6 | 7 | | 7 | 7 | | 8 | 9 | | 9 | 1 | | 10 | 5 | | 11 | 28 | | 12 | 10 | | 13 | 24 | | 14 | 13 | | 15 | 2 | | 16 | 2 | | 17 | 3 | | 18 | 12 | | 19 | 2 | | 20 | 7 | | 21 | 4 | | 22 | 4 | | 23 | 17 | | 24 | 9 | | 25 | 5 | | 26 | 16 | | 27 | 13 | | 28 | 2 | | 29 | 4 | | 30 | 3 | | 31 | 9 | | 32 | 5 | | 33 | 15 | | 34 | 23 | | 35 | 8 | | 36 | 2 | | 37 | 7 | | 38 | 10 | | 39 | 5 | | 40 | 8 | | 41 | 5 | | 42 | 28 | | 43 | 23 | | 44 | 4 | | 45 | 19 | | 46 | 9 | | 47 | 5 | | 48 | 15 | | 49 | 10 |
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| 47.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3467741935483871 | | totalSentences | 124 | | uniqueOpeners | 43 | |
| 74.07% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 90 | | matches | | 0 | "Maybe thirty feet away." | | 1 | "Instead, the space between the" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 90 | | matches | | 0 | "It had been doing that" | | 1 | "She'd tried taking it off" | | 2 | "he'd said, his voice carrying" | | 3 | "She stepped through the treeline" | | 4 | "she said, her voice flat" | | 5 | "It should have been simple." | | 6 | "She dropped her hands." | | 7 | "They swayed in a wind" | | 8 | "She'd read that in one" | | 9 | "She'd thought it was metaphor." | | 10 | "She planted her feet." | | 11 | "She could feel it, their" | | 12 | "She didn't know who she" | | 13 | "It had no face, but" | | 14 | "It was the sound of" | | 15 | "She saw a forest older" | | 16 | "She saw a woman with" | | 17 | "She tasted iron and honey" | | 18 | "She was outside the circle." | | 19 | "She looked at her wrist." |
| | ratio | 0.233 | |
| 37.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 76 | | totalSentences | 90 | | matches | | 0 | "The pendant burned against Aurora's" | | 1 | "It had been doing that" | | 2 | "She'd tried taking it off" | | 3 | "Both times she'd woken up" | | 4 | "*The grove.* That's what Silas" | | 5 | "he'd said, his voice carrying" | | 6 | "She stepped through the treeline" | | 7 | "Richmond Park at night was" | | 8 | "The gates locked at dusk." | | 9 | "The standing stones rose from" | | 10 | "Moss covered their surfaces, but" | | 11 | "The pendant throbbed." | | 12 | "she said, her voice flat" | | 13 | "The words fell dead at" | | 14 | "The grove didn't answer." | | 15 | "Aurora's fingers found the clasp" | | 16 | "It should have been simple." | | 17 | "A basic clasp, the kind" | | 18 | "She dropped her hands." | | 19 | "The chain cooled." |
| | ratio | 0.844 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 20.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 7 | | matches | | 0 | "Nine of them, arranged in a circle that felt wrong in her peripheral vision, like looking at a photograph with the proportions slightly off." | | 1 | "A low frequency that made her vision blur at the edges, that pulled at something deep in her chest, something that had nothing to do with the pendant." | | 2 | "The resistance made the humming intensify, made the flowers around her bleed into the earth, their colours seeping into the soil like watercolours dissolving." | | 3 | "The ground beneath her shoes grew wet, then slick, and she realised with distant horror that she was standing on something that breathed." | | 4 | "Became a figure that was not a figure, a silhouette against deeper black, its edges fraying like burnt paper." | | 5 | "She saw a forest older than Britain, older than humans, where creatures made of moonlight danced between trees that touched the sky." | | 6 | "The flowers had all died now, their colours drained, leaving only grey stems that crumbled at the slightest touch." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 7 | | uselessAdditionCount | 2 | | matches | | 0 | "he'd, his voice carrying that edge she'd learned meant danger" | | 1 | "she said, her voice flat in the uncanny silence" |
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| 66.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 2 | | fancyTags | | 0 | "he'd (would)" | | 1 | "Aurora pressed (press)" |
| | dialogueSentences | 24 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0.667 | | effectiveRatio | 0.167 | |