| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 89.82% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 982 | | 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) | |
| 64.36% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 982 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "warmth" | | 1 | "pulse" | | 2 | "footsteps" | | 3 | "pulsed" | | 4 | "silence" |
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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 | 77 | | matches | (empty) | |
| 87.20% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 94.09% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 52 | | totalWords | 982 | | ratio | 0.053 | | matches | | 0 | "Past the second bench, where the holly thickens. Keep the oaks on your left. You'll know the stones when you see them." | | 1 | "It only does that near a portal" | | 2 | "Near a Hel portal." | | 3 | "You came for answers" | | 4 | "Isolde said the grove would show you. Isolde said you'd know when it was time." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 975 | | uniqueNames | 9 | | maxNameDensity | 0.51 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Isolde" | | discoveredNames | | Sheen | 1 | | Gate | 1 | | Park | 1 | | Rory | 5 | | Isolde | 5 | | November | 1 | | Heartstone | 1 | | Hel | 1 | | Cardiff | 1 |
| | persons | | | places | | 0 | "Sheen" | | 1 | "Park" | | 2 | "Hel" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 98.17% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 1.018 | | wordCount | 982 | | matches | | 0 | "not with the warmth of her body but with something steadier, a slow faint pulse, like a heartbea" |
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| 81.20% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 78 | | matches | | 0 | "does that near" | | 1 | "waking, that there" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 40.92 | | std | 31.43 | | cv | 0.768 | | sampleLengths | | 0 | 108 | | 1 | 22 | | 2 | 17 | | 3 | 63 | | 4 | 50 | | 5 | 26 | | 6 | 9 | | 7 | 96 | | 8 | 6 | | 9 | 64 | | 10 | 36 | | 11 | 61 | | 12 | 4 | | 13 | 37 | | 14 | 3 | | 15 | 6 | | 16 | 90 | | 17 | 96 | | 18 | 16 | | 19 | 35 | | 20 | 22 | | 21 | 60 | | 22 | 23 | | 23 | 32 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 77 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 146 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 78 | | ratio | 0 | | matches | (empty) | |
| 84.53% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 978 | | adjectiveStacks | 2 | | stackExamples | | 0 | "blue star-shaped bloom" | | 1 | "warm pressed against her" |
| | adverbCount | 43 | | adverbRatio | 0.04396728016359918 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.015337423312883436 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 12.59 | | std | 10.41 | | cv | 0.827 | | sampleLengths | | 0 | 32 | | 1 | 13 | | 2 | 19 | | 3 | 44 | | 4 | 8 | | 5 | 6 | | 6 | 8 | | 7 | 11 | | 8 | 6 | | 9 | 3 | | 10 | 16 | | 11 | 31 | | 12 | 13 | | 13 | 13 | | 14 | 6 | | 15 | 14 | | 16 | 1 | | 17 | 4 | | 18 | 1 | | 19 | 11 | | 20 | 4 | | 21 | 17 | | 22 | 5 | | 23 | 9 | | 24 | 27 | | 25 | 6 | | 26 | 27 | | 27 | 7 | | 28 | 7 | | 29 | 22 | | 30 | 6 | | 31 | 9 | | 32 | 38 | | 33 | 17 | | 34 | 9 | | 35 | 18 | | 36 | 4 | | 37 | 5 | | 38 | 17 | | 39 | 6 | | 40 | 19 | | 41 | 9 | | 42 | 10 | | 43 | 4 | | 44 | 5 | | 45 | 27 | | 46 | 5 | | 47 | 3 | | 48 | 2 | | 49 | 4 |
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| 45.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.3815789473684211 | | totalSentences | 76 | | uniqueOpeners | 29 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 70 | | matches | | 0 | "Then another, and another, a" | | 1 | "Instead the flowers breathed a" | | 2 | "Somewhere high in the oaks" | | 3 | "Then that too was gone." | | 4 | "Then, very briefly, nine, a" | | 5 | "Only the faint, patient sound" |
| | ratio | 0.086 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 28 | | totalSentences | 70 | | matches | | 0 | "She followed the path until" | | 1 | "You'll know the stones when" | | 2 | "She had almost laughed at" | | 3 | "She didn't feel like laughing" | | 4 | "She turned the screen toward" | | 5 | "She tapped it again." | | 6 | "She waited, counted to thirty," | | 7 | "she said quietly" | | 8 | "Her voice came back to" | | 9 | "She put it away and" | | 10 | "It was the second week" | | 11 | "She drew a breath and" | | 12 | "*It only does that near" | | 13 | "It was the wrong time" | | 14 | "It was the wrong time" | | 15 | "She stopped and listened." | | 16 | "Her own footsteps had stopped." | | 17 | "She turned slowly in a" | | 18 | "She counted again." | | 19 | "She did not turn toward" |
| | ratio | 0.4 | |
| 74.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 54 | | totalSentences | 70 | | matches | | 0 | "The bus had dropped her" | | 1 | "Richmond Park at night was" | | 2 | "She followed the path until" | | 3 | "You'll know the stones when" | | 4 | "She had almost laughed at" | | 5 | "She didn't feel like laughing" | | 6 | "The holly thickened." | | 7 | "The oaks rose on her" | | 8 | "Rory stopped at the edge" | | 9 | "She turned the screen toward" | | 10 | "She tapped it again." | | 11 | "She waited, counted to thirty," | | 12 | "she said quietly" | | 13 | "Her voice came back to" | | 14 | "She put it away and" | | 15 | "The clearing opened in front" | | 16 | "The grass was thick and" | | 17 | "Wildflowers grew through it in" | | 18 | "It was the second week" | | 19 | "Frost should have been silvering" |
| | ratio | 0.771 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | 0 | "Even with the lamps along" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |