| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.556 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.15% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1756 | | totalAiIsmAdverbs | 1 | | 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) | |
| 62.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1756 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "warmth" | | 1 | "flicked" | | 2 | "footsteps" | | 3 | "weight" | | 4 | "silence" | | 5 | "pulsed" | | 6 | "echo" | | 7 | "whisper" | | 8 | "vibrated" | | 9 | "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 | 176 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 176 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 180 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1758 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 92.56% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1741 | | uniqueNames | 7 | | maxNameDensity | 1.15 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Park | 2 | | London | 2 | | Heartstone | 1 | | Eva | 1 | | Thursday | 1 | | Rory | 20 |
| | persons | | | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" |
| | globalScore | 0.926 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 120 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like voices speaking behind a clos" |
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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 | 1758 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 180 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 87 | | mean | 20.21 | | std | 21.89 | | cv | 1.083 | | sampleLengths | | 0 | 11 | | 1 | 52 | | 2 | 18 | | 3 | 22 | | 4 | 7 | | 5 | 80 | | 6 | 16 | | 7 | 68 | | 8 | 81 | | 9 | 9 | | 10 | 8 | | 11 | 8 | | 12 | 1 | | 13 | 40 | | 14 | 7 | | 15 | 71 | | 16 | 7 | | 17 | 45 | | 18 | 4 | | 19 | 2 | | 20 | 26 | | 21 | 11 | | 22 | 26 | | 23 | 51 | | 24 | 1 | | 25 | 5 | | 26 | 7 | | 27 | 10 | | 28 | 7 | | 29 | 61 | | 30 | 5 | | 31 | 10 | | 32 | 12 | | 33 | 16 | | 34 | 6 | | 35 | 13 | | 36 | 5 | | 37 | 8 | | 38 | 4 | | 39 | 43 | | 40 | 12 | | 41 | 1 | | 42 | 46 | | 43 | 4 | | 44 | 58 | | 45 | 5 | | 46 | 4 | | 47 | 39 | | 48 | 5 | | 49 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 176 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 267 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 180 | | ratio | 0.011 | | matches | | 0 | "Richmond Park usually held some noise even this late — a fox crunching underbrush, a car on the road beyond the trees, the low rumble of a plane climbing over London." | | 1 | "It matched the dark too cleanly at first for her eyes to catch it, then the torch picked a pale edge — a shoulder, a face, or the idea of one." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1742 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 69 | | adverbRatio | 0.03960964408725603 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.003444316877152698 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 180 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 180 | | mean | 9.77 | | std | 6.95 | | cv | 0.711 | | sampleLengths | | 0 | 11 | | 1 | 29 | | 2 | 6 | | 3 | 3 | | 4 | 14 | | 5 | 18 | | 6 | 22 | | 7 | 7 | | 8 | 24 | | 9 | 24 | | 10 | 1 | | 11 | 1 | | 12 | 1 | | 13 | 8 | | 14 | 21 | | 15 | 16 | | 16 | 14 | | 17 | 6 | | 18 | 6 | | 19 | 23 | | 20 | 19 | | 21 | 3 | | 22 | 14 | | 23 | 10 | | 24 | 13 | | 25 | 31 | | 26 | 10 | | 27 | 9 | | 28 | 8 | | 29 | 8 | | 30 | 1 | | 31 | 17 | | 32 | 2 | | 33 | 2 | | 34 | 19 | | 35 | 7 | | 36 | 15 | | 37 | 15 | | 38 | 25 | | 39 | 16 | | 40 | 7 | | 41 | 9 | | 42 | 6 | | 43 | 20 | | 44 | 10 | | 45 | 4 | | 46 | 2 | | 47 | 7 | | 48 | 19 | | 49 | 6 |
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| 42.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.2737430167597765 | | totalSentences | 179 | | uniqueOpeners | 49 | |
| 43.01% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 155 | | matches | | 0 | "Just bark and roots and" | | 1 | "Then, from somewhere just beyond" |
| | ratio | 0.013 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 40 | | totalSentences | 155 | | matches | | 0 | "She kept one hand on" | | 1 | "she muttered, and opened the" | | 2 | "She checked the bag by" | | 3 | "They floated through the light" | | 4 | "She stopped near a clump" | | 5 | "She angled her shoulders and" | | 6 | "It sat thick on her" | | 7 | "Her pendant pulsed once, a" | | 8 | "She lifted her phone." | | 9 | "She clicked the torch off" | | 10 | "she said to the clearing" | | 11 | "It vanished at the boundary" | | 12 | "She set the bag down" | | 13 | "She drew her hand away." | | 14 | "It skimmed behind a trunk" | | 15 | "She kept the light there." | | 16 | "Her pendant heated again." | | 17 | "She let it drop against" | | 18 | "She turned toward it." | | 19 | "She stepped back and the" |
| | ratio | 0.258 | |
| 34.19% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 132 | | totalSentences | 155 | | matches | | 0 | "Rory cut the engine and" | | 1 | "The car sat crooked on" | | 2 | "The park looked sealed shut," | | 3 | "She kept one hand on" | | 4 | "The gem sat cool against" | | 5 | "she muttered, and opened the" | | 6 | "The air outside carried damp" | | 7 | "Rory shoved her phone into" | | 8 | "A bottle of water she" | | 9 | "She checked the bag by" | | 10 | "The pendant warmed once more" | | 11 | "A narrow path cut through" | | 12 | "The grove sat tucked behind" | | 13 | "Isolde’s grove, Eva had called" | | 14 | "Rory walked on." | | 15 | "The beam from her phone" | | 16 | "The beam picked out moths" | | 17 | "They floated through the light" | | 18 | "Richmond Park usually held some" | | 19 | "Tonight the park took her" |
| | ratio | 0.852 | |
| 32.26% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 155 | | matches | | 0 | "Even at night they looked" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 71 | | technicalSentenceCount | 3 | | matches | | 0 | "Yet the stems bent in a path that curved away from her, each head nodding as if a person had just passed through, careful and unhurried." | | 1 | "The grooves shone pale and wet, as if something sharp had just passed over them." | | 2 | "It had stood low to the ground, too low for a person, with a sharp pale cheek and an eye that reflected the light like glass." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 9 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.5 | | effectiveRatio | 0.444 | |