| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 75.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1007 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "tightly" | | 1 | "slowly" | | 2 | "utterly" | | 3 | "completely" | | 4 | "very" |
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| 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) | |
| 55.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1007 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "weight" | | 1 | "pulse" | | 2 | "warmth" | | 3 | "pulsed" | | 4 | "absolutely" |
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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 | 98 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 98 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 98 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 6 | | totalWords | 1015 | | ratio | 0.006 | | matches | | 0 | "The grove. Midnight. The pendant matters." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 1014 | | uniqueNames | 6 | | maxNameDensity | 0.49 | | worstName | "Grove" | | maxWindowNameDensity | 1 | | worstWindowName | "Grove" | | discoveredNames | | Park | 1 | | Grove | 5 | | Heartstone | 4 | | February | 1 | | Hel | 1 | | Fae | 1 |
| | persons | (empty) | | places | | 0 | "Park" | | 1 | "Grove" | | 2 | "February" | | 3 | "Hel" |
| | globalScore | 1 | | windowScore | 1 | |
| 13.64% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 3 | | matches | | 0 | "something between honey and rain" | | 1 | "quite name" | | 2 | "Something between the two — a soft, deliberate" |
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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 | 1015 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 98 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 30.76 | | std | 28.19 | | cv | 0.917 | | sampleLengths | | 0 | 10 | | 1 | 53 | | 2 | 3 | | 3 | 67 | | 4 | 79 | | 5 | 51 | | 6 | 14 | | 7 | 3 | | 8 | 101 | | 9 | 16 | | 10 | 4 | | 11 | 38 | | 12 | 53 | | 13 | 53 | | 14 | 2 | | 15 | 40 | | 16 | 1 | | 17 | 4 | | 18 | 44 | | 19 | 10 | | 20 | 9 | | 21 | 5 | | 22 | 69 | | 23 | 7 | | 24 | 3 | | 25 | 30 | | 26 | 12 | | 27 | 80 | | 28 | 18 | | 29 | 3 | | 30 | 69 | | 31 | 20 | | 32 | 44 |
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| 90.94% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 98 | | matches | | 0 | "were locked" | | 1 | "been left" | | 2 | "been stretched" | | 3 | "been ridged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 155 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 98 | | ratio | 0.061 | | matches | | 0 | "The park gates were locked at dusk — she'd scaled the iron fence at the eastern edge, dropped down into the wet grass, and walked." | | 1 | "The wildflowers were there — she could make them out in the pale grass around her boots, impossible in February, small and white and open — and the clearing looked exactly as she remembered it." | | 2 | "Time moved strangely here — she knew that too, in the abstract way she knew things about the Fae, the way you know the rules of a game you have never played." | | 3 | "Something between the two — a soft, deliberate pressure against the ground, like a weight settled and lifted in a single practised motion." | | 4 | "The warmth was unmistakeable — a single beat of heat, like a coal glowing briefly back to life, and then nothing." | | 5 | "The tree — the thing that stood where the tree had been — did not move." |
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| 98.54% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1008 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.041666666666666664 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.016865079365079364 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 98 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 98 | | mean | 10.36 | | std | 9.78 | | cv | 0.944 | | sampleLengths | | 0 | 10 | | 1 | 3 | | 2 | 38 | | 3 | 7 | | 4 | 5 | | 5 | 3 | | 6 | 19 | | 7 | 1 | | 8 | 30 | | 9 | 9 | | 10 | 1 | | 11 | 7 | | 12 | 25 | | 13 | 29 | | 14 | 15 | | 15 | 10 | | 16 | 11 | | 17 | 33 | | 18 | 7 | | 19 | 4 | | 20 | 10 | | 21 | 3 | | 22 | 23 | | 23 | 3 | | 24 | 1 | | 25 | 13 | | 26 | 35 | | 27 | 6 | | 28 | 8 | | 29 | 12 | | 30 | 11 | | 31 | 3 | | 32 | 2 | | 33 | 4 | | 34 | 7 | | 35 | 3 | | 36 | 4 | | 37 | 4 | | 38 | 20 | | 39 | 8 | | 40 | 2 | | 41 | 26 | | 42 | 17 | | 43 | 9 | | 44 | 32 | | 45 | 12 | | 46 | 2 | | 47 | 4 | | 48 | 17 | | 49 | 1 |
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| 41.84% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.336734693877551 | | totalSentences | 98 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 87 | | matches | | 0 | "Too quiet, she realised after" | | 1 | "Just smooth stone and the" | | 2 | "Only that they now seemed" |
| | ratio | 0.034 | |
| 95.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 87 | | matches | | 0 | "She'd known it each of" | | 1 | "She went anyway." | | 2 | "She'd dressed, laced her boots," | | 3 | "She kept it low, watching" | | 4 | "She found the standing stones" | | 5 | "She stopped at the threshold" | | 6 | "She stepped through." | | 7 | "She crossed to the flat" | | 8 | "She turned the Heartstone over" | | 9 | "She'd half-expected it to pulse" | | 10 | "She kept her breathing even" | | 11 | "She turned her head." | | 12 | "She held the light steady" | | 13 | "She lowered the phone." | | 14 | "She turned slowly." | | 15 | "Her voice came out smaller" | | 16 | "She stood from the stone" | | 17 | "She couldn't say how." | | 18 | "She took two steps toward" | | 19 | "She'd never heard of a" |
| | ratio | 0.31 | |
| 69.20% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 87 | | matches | | 0 | "Richmond Park after dark did" | | 1 | "Rory knew that." | | 2 | "She'd known it each of" | | 3 | "Daylight forgave the strangeness of" | | 4 | "Night, she suspected, would not." | | 5 | "She went anyway." | | 6 | "The text had arrived at" | | 7 | "The pendant matters.* She'd stood" | | 8 | "The deep crimson stone sat" | | 9 | "She'd dressed, laced her boots," | | 10 | "The park gates were locked" | | 11 | "The torch on her phone" | | 12 | "She kept it low, watching" | | 13 | "She found the standing stones" | | 14 | "The old oaks marked the" | | 15 | "She stopped at the threshold" | | 16 | "The distant snarl of a" | | 17 | "She stepped through." | | 18 | "The air changed immediately, the" | | 19 | "The wildflowers were there —" |
| | ratio | 0.782 | |
| 57.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 87 | | matches | | 0 | "Now the city behind her" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "Behind the tree to her left, a slow press of weight against soft earth, and she turned and raised the torch in one movement and the light fell on a tree that wa…" | | 1 | "She stood very still and looked at the shape that wore the oak tree's outline, and she understood with a clarity that arrived complete and without drama that wh…" |
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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 | |