| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 29 | | tagDensity | 0.655 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1127 | | 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) | |
| 68.94% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1127 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pulsed" | | 1 | "stomach" | | 2 | "perfect" | | 3 | "chill" | | 4 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 104 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1128 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 77.46% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 965 | | uniqueNames | 8 | | maxNameDensity | 1.45 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 1 | | Richmond | 1 | | Park | 1 | | Rory | 14 | | Nyx | 7 | | Isolde | 6 | | Fae | 1 | | Past | 1 |
| | persons | | 0 | "Heartstone" | | 1 | "Rory" | | 2 | "Nyx" | | 3 | "Isolde" |
| | places | | | globalScore | 0.775 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1128 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 22.56 | | std | 19.23 | | cv | 0.853 | | sampleLengths | | 0 | 12 | | 1 | 41 | | 2 | 23 | | 3 | 10 | | 4 | 18 | | 5 | 11 | | 6 | 8 | | 7 | 47 | | 8 | 37 | | 9 | 14 | | 10 | 37 | | 11 | 4 | | 12 | 5 | | 13 | 26 | | 14 | 42 | | 15 | 3 | | 16 | 25 | | 17 | 7 | | 18 | 20 | | 19 | 3 | | 20 | 72 | | 21 | 10 | | 22 | 29 | | 23 | 55 | | 24 | 3 | | 25 | 2 | | 26 | 68 | | 27 | 7 | | 28 | 8 | | 29 | 3 | | 30 | 49 | | 31 | 5 | | 32 | 16 | | 33 | 56 | | 34 | 29 | | 35 | 15 | | 36 | 4 | | 37 | 3 | | 38 | 38 | | 39 | 20 | | 40 | 8 | | 41 | 47 | | 42 | 4 | | 43 | 29 | | 44 | 10 | | 45 | 44 | | 46 | 61 | | 47 | 13 | | 48 | 4 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 170 | | matches | | 0 | "were walking" | | 1 | "were moving" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 114 | | ratio | 0.009 | | matches | | 0 | "Past the trees, the terraces broke into gardens — long beds of herbs she half-recognised, tied in bundles the height of her chest, root vegetables turned up out of the soil in spirals, a field of peppers in colours that hurt to look at directly." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 965 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.029015544041450778 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0031088082901554403 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 9.89 | | std | 8.16 | | cv | 0.825 | | sampleLengths | | 0 | 12 | | 1 | 7 | | 2 | 17 | | 3 | 6 | | 4 | 11 | | 5 | 14 | | 6 | 9 | | 7 | 10 | | 8 | 3 | | 9 | 15 | | 10 | 5 | | 11 | 6 | | 12 | 8 | | 13 | 9 | | 14 | 8 | | 15 | 3 | | 16 | 27 | | 17 | 2 | | 18 | 2 | | 19 | 16 | | 20 | 17 | | 21 | 9 | | 22 | 5 | | 23 | 2 | | 24 | 6 | | 25 | 1 | | 26 | 2 | | 27 | 8 | | 28 | 18 | | 29 | 2 | | 30 | 2 | | 31 | 5 | | 32 | 17 | | 33 | 9 | | 34 | 3 | | 35 | 18 | | 36 | 15 | | 37 | 6 | | 38 | 3 | | 39 | 5 | | 40 | 20 | | 41 | 7 | | 42 | 20 | | 43 | 3 | | 44 | 9 | | 45 | 29 | | 46 | 24 | | 47 | 7 | | 48 | 3 | | 49 | 3 |
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| 78.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.49122807017543857 | | totalSentences | 114 | | uniqueOpeners | 56 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 76 | | matches | | 0 | "Then her boots struck ground" | | 1 | "Somewhere below, water moved in" | | 2 | "Then at the pendant." |
| | ratio | 0.039 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 76 | | matches | | 0 | "She stopped at the tear" | | 1 | "Their arm thinned to smoke," | | 2 | "Her ears popped." | | 3 | "Her lungs took it in" | | 4 | "She reached for the nearest" | | 5 | "She pulled her hand back." | | 6 | "They went down." | | 7 | "Her mouth watered." | | 8 | "She kept her hands at" | | 9 | "She laid a palm over" | | 10 | "They walked on." | | 11 | "They bent to the vines" | | 12 | "She looked at Rory for" | | 13 | "Her voice was flat, unhurried," | | 14 | "Her eyes narrowed, then widened," | | 15 | "She picked up her basket" | | 16 | "She bent back to the" | | 17 | "Her stomach hurt with a" | | 18 | "She took the pendant in" |
| | ratio | 0.25 | |
| 6.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 76 | | matches | | 0 | "The rift split the air" | | 1 | "Rory felt it first through" | | 2 | "The Heartstone warmed against her" | | 3 | "Crimson light pooled in her" | | 4 | "The gem pulsed in time" | | 5 | "Isolde crossed the wet grass" | | 6 | "She stopped at the tear" | | 7 | "Nyx reached first." | | 8 | "Their arm thinned to smoke," | | 9 | "Rory gripped the shade's wrist" | | 10 | "The crossing took no time" | | 11 | "A pressure folded around her" | | 12 | "Her ears popped." | | 13 | "The whole vault above her" | | 14 | "Shapes drifted in it, too" | | 15 | "Isolde said, landing beside her" | | 16 | "Rory's first breath came like" | | 17 | "Her lungs took it in" | | 18 | "Nyx settled into full form," | | 19 | "Rory looked down." |
| | ratio | 0.908 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 76 | | matches | (empty) | | ratio | 0 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 35 | | technicalSentenceCount | 5 | | matches | | 0 | "Her lungs took it in and her stomach answered with a hunger that folded her at the waist." | | 1 | "Somewhere below, water moved in a stone channel, and when Rory looked down at it, the water ran the wrong way, sliding uphill toward a cistern that had no top." | | 2 | "Pale linen, wide hats, bare arms brown from a sun that did not exist." | | 3 | "A woman, old and broad, with soil packed under her fingernails and a face that had stopped moving a long time ago." | | 4 | "The gardens ran on and down, and below the gardens there was a low, wide building of pale stone, and beyond that a colonnade, and beyond that something that gli…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 1 | | fancyTags | | 0 | "they whispered (whisper)" |
| | dialogueSentences | 29 | | tagDensity | 0.517 | | leniency | 1 | | rawRatio | 0.067 | | effectiveRatio | 0.067 | |