| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 90.26% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1027 | | 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) | |
| 31.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1027 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "pulse" | | 1 | "echo" | | 2 | "silence" | | 3 | "flickered" | | 4 | "stomach" | | 5 | "pulsed" | | 6 | "crystal" | | 7 | "traced" | | 8 | "footsteps" | | 9 | "gloom" | | 10 | "affection" | | 11 | "navigated" | | 12 | "structure" | | 13 | "perfect" |
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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 | 96 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 96 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 96 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1012 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 995 | | uniqueNames | 16 | | maxNameDensity | 0.7 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 3 | | Aldwych | 1 | | Yu-Fei | 2 | | Richmond | 1 | | Park | 1 | | Crown | 1 | | January | 1 | | Hel | 1 | | Fae | 1 | | London | 2 | | Cardiff | 2 | | University | 1 | | Golden | 1 | | Empress | 1 | | Aurora | 1 | | Rory | 7 |
| | persons | | 0 | "Heartstone" | | 1 | "University" | | 2 | "Rory" |
| | places | | 0 | "Aldwych" | | 1 | "Yu-Fei" | | 2 | "Richmond" | | 3 | "Park" | | 4 | "January" | | 5 | "London" | | 6 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.964 | | wordCount | 1012 | | matches | | 0 | "no sound but" | | 1 | "Not Aurora, not Rory, but the third name, the one the pendant had burned into her drea" | | 2 | "not Rory, but the third name, the one the pendant had burned into her drea" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 96 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 30.67 | | std | 23.71 | | cv | 0.773 | | sampleLengths | | 0 | 3 | | 1 | 54 | | 2 | 40 | | 3 | 58 | | 4 | 26 | | 5 | 5 | | 6 | 19 | | 7 | 59 | | 8 | 13 | | 9 | 4 | | 10 | 2 | | 11 | 66 | | 12 | 4 | | 13 | 7 | | 14 | 54 | | 15 | 3 | | 16 | 38 | | 17 | 49 | | 18 | 31 | | 19 | 45 | | 20 | 5 | | 21 | 74 | | 22 | 49 | | 23 | 43 | | 24 | 29 | | 25 | 7 | | 26 | 79 | | 27 | 36 | | 28 | 5 | | 29 | 8 | | 30 | 56 | | 31 | 4 | | 32 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 96 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 176 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 96 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 145 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.006896551724137931 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 96 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 96 | | mean | 10.54 | | std | 7.97 | | cv | 0.756 | | sampleLengths | | 0 | 3 | | 1 | 16 | | 2 | 17 | | 3 | 7 | | 4 | 14 | | 5 | 2 | | 6 | 8 | | 7 | 8 | | 8 | 7 | | 9 | 15 | | 10 | 20 | | 11 | 38 | | 12 | 11 | | 13 | 2 | | 14 | 2 | | 15 | 11 | | 16 | 5 | | 17 | 8 | | 18 | 2 | | 19 | 9 | | 20 | 14 | | 21 | 17 | | 22 | 28 | | 23 | 4 | | 24 | 2 | | 25 | 7 | | 26 | 3 | | 27 | 1 | | 28 | 2 | | 29 | 4 | | 30 | 12 | | 31 | 7 | | 32 | 2 | | 33 | 23 | | 34 | 18 | | 35 | 4 | | 36 | 7 | | 37 | 6 | | 38 | 8 | | 39 | 9 | | 40 | 8 | | 41 | 1 | | 42 | 1 | | 43 | 21 | | 44 | 3 | | 45 | 5 | | 46 | 23 | | 47 | 10 | | 48 | 4 | | 49 | 6 |
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| 55.56% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.4270833333333333 | | totalSentences | 96 | | uniqueOpeners | 41 | |
| 41.15% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 81 | | matches | | 0 | "Only the wildflowers, bobbing their" |
| | ratio | 0.012 | |
| 96.54% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 81 | | matches | | 0 | "She pressed her palm against" | | 1 | "It had warmed near the" | | 2 | "It had sung in Yu-Fei's" | | 3 | "She'd followed the address scrawled" | | 4 | "She checked her mobile." | | 5 | "She hadn't believed it then," | | 6 | "She believed it now." | | 7 | "It originated from everywhere simultaneously," | | 8 | "She whirled, but nothing stood" | | 9 | "They weren't flowers." | | 10 | "They were mouths, opening and" | | 11 | "She traced the crescent scar" | | 12 | "She understood that now." | | 13 | "Her hand found the zipper." | | 14 | "She'd see what had been" | | 15 | "Her fingers, trembling despite her" | | 16 | "She slid the zipper down" | | 17 | "It had been crouched, camouflaged" | | 18 | "Its features suggested a face" | | 19 | "It wore no clothes because" |
| | ratio | 0.309 | |
| 58.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 81 | | matches | | 0 | "The stone burned." | | 1 | "Rory snatched her hand back," | | 2 | "She pressed her palm against" | | 3 | "It had warmed near the" | | 4 | "It had sung in Yu-Fei's" | | 5 | "Here, in this clearing between" | | 6 | "She'd followed the address scrawled" | | 7 | "The insulated delivery bag slung" | | 8 | "The words died three feet" | | 9 | "The grove swallowed them, digesting" | | 10 | "Rory turned, five foot six" | | 11 | "The oaks stood shoulder-to-shoulder behind" | | 12 | "Pre-Law had taught her to" | | 13 | "She checked her mobile." | | 14 | "The screen flickered." | | 15 | "Time moved differently here." | | 16 | "The realization struck her stomach" | | 17 | "An hour inside could be" | | 18 | "The handwritten notes she'd found" | | 19 | "She hadn't believed it then," |
| | ratio | 0.802 | |
| 61.73% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 81 | | matches | | 0 | "Now the wildflowers crushed beneath" |
| | ratio | 0.012 | |
| 43.19% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 6 | | matches | | 0 | "Shouldn't pulse with a rhythm that matched the gemstone now blazing against her collarbone." | | 1 | "Pre-Law had taught her to analyze, to find the loophole in any contract, but there were no precedents for spaces that rewrote their own geography while you watc…" | | 2 | "The Golden Empress logo emblazoned on the fabric seemed to writhe, golden dragons winking with eyes that tracked her panic." | | 3 | "Cool-headed analysis reasserted itself, the quick thinking that had earned scholarships and navigated abusive temper." | | 4 | "It wore no clothes because it wore no skin, just bark-wet tissue that gleamed in the moonlight, desiccated and ancient, with eyes like standing water." | | 5 | "The roots reached for her scarred wrist, fitting into the crescent shape perfectly, like a key into a lock that had been waiting twenty-five years to turn." |
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| 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 | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |