| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 68 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1720 | | 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) | |
| 73.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1720 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "pulsed" | | 1 | "trembled" | | 2 | "whisper" | | 3 | "pulse" | | 4 | "warmth" | | 5 | "stomach" | | 6 | "porcelain" |
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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 | 192 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 192 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 243 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1719 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 69 | | wordCount | 1432 | | uniqueNames | 10 | | maxNameDensity | 1.82 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Heartstone | 3 | | Isolde | 9 | | Aurora | 26 | | Fae-forged | 1 | | Veil | 1 | | Eva | 16 | | Nyx | 7 | | Fae | 2 |
| | persons | | 0 | "Heartstone" | | 1 | "Isolde" | | 2 | "Aurora" | | 3 | "Veil" | | 4 | "Eva" | | 5 | "Nyx" |
| | places | | | globalScore | 0.592 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 116 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.582 | | wordCount | 1719 | | matches | | 0 | "not only the space between buildings but the air above" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 243 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 140 | | mean | 12.28 | | std | 12.48 | | cv | 1.016 | | sampleLengths | | 0 | 16 | | 1 | 30 | | 2 | 4 | | 3 | 47 | | 4 | 15 | | 5 | 6 | | 6 | 22 | | 7 | 16 | | 8 | 11 | | 9 | 6 | | 10 | 1 | | 11 | 14 | | 12 | 36 | | 13 | 3 | | 14 | 19 | | 15 | 7 | | 16 | 12 | | 17 | 23 | | 18 | 9 | | 19 | 6 | | 20 | 7 | | 21 | 8 | | 22 | 10 | | 23 | 2 | | 24 | 7 | | 25 | 13 | | 26 | 1 | | 27 | 3 | | 28 | 33 | | 29 | 37 | | 30 | 4 | | 31 | 6 | | 32 | 7 | | 33 | 51 | | 34 | 47 | | 35 | 4 | | 36 | 4 | | 37 | 8 | | 38 | 6 | | 39 | 3 | | 40 | 4 | | 41 | 6 | | 42 | 9 | | 43 | 46 | | 44 | 22 | | 45 | 6 | | 46 | 5 | | 47 | 1 | | 48 | 2 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 192 | | matches | | 0 | "been carved" | | 1 | "been replaced" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 238 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 243 | | ratio | 0.004 | | matches | | 0 | "A sharp scent filled the air—pepper, rain, and hot metal." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1438 | | adjectiveStacks | 1 | | stackExamples | | 0 | "slender, leaf-shaped edge." |
| | adverbCount | 40 | | adverbRatio | 0.027816411682892908 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.004867872044506259 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 243 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 243 | | mean | 7.07 | | std | 4.69 | | cv | 0.663 | | sampleLengths | | 0 | 16 | | 1 | 14 | | 2 | 11 | | 3 | 5 | | 4 | 4 | | 5 | 3 | | 6 | 2 | | 7 | 9 | | 8 | 15 | | 9 | 9 | | 10 | 9 | | 11 | 3 | | 12 | 12 | | 13 | 6 | | 14 | 10 | | 15 | 12 | | 16 | 8 | | 17 | 8 | | 18 | 4 | | 19 | 7 | | 20 | 6 | | 21 | 1 | | 22 | 8 | | 23 | 6 | | 24 | 8 | | 25 | 7 | | 26 | 9 | | 27 | 12 | | 28 | 3 | | 29 | 14 | | 30 | 5 | | 31 | 7 | | 32 | 3 | | 33 | 9 | | 34 | 10 | | 35 | 13 | | 36 | 9 | | 37 | 6 | | 38 | 7 | | 39 | 8 | | 40 | 10 | | 41 | 2 | | 42 | 6 | | 43 | 1 | | 44 | 13 | | 45 | 1 | | 46 | 3 | | 47 | 3 | | 48 | 6 | | 49 | 14 |
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| 55.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.36213991769547327 | | totalSentences | 243 | | uniqueOpeners | 88 | |
| 80.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 166 | | matches | | 0 | "Then the air split." | | 1 | "Somewhere on the far side," | | 2 | "Then the smell of wet" | | 3 | "Instead, two enormous stone hounds" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 166 | | matches | | 0 | "Its crimson centre pulsed once." | | 1 | "Their tall silhouette thinned at" | | 2 | "their wind-borne voice murmured" | | 3 | "Her silver hair drifted around" | | 4 | "She held it out and" | | 5 | "They crossed together." | | 6 | "She looked back once." | | 7 | "They twisted around ivory arches," | | 8 | "Their skins reflected faces that" | | 9 | "It flexed in places, as" | | 10 | "Their petals unfolded one by" | | 11 | "Their shoulder passed through a" | | 12 | "It had a man’s shape," | | 13 | "Its mouth opened too wide," | | 14 | "Its teeth were small, square," | | 15 | "It vanished between one breath" | | 16 | "Their roofs curved like folded" | | 17 | "Her mouth watered before she" | | 18 | "Their bodies had been carved" | | 19 | "Their eyes held tiny flames." |
| | ratio | 0.157 | |
| 50.36% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 136 | | totalSentences | 166 | | matches | | 0 | "The standing stones rose from" | | 1 | "Aurora stopped between them, one" | | 2 | "The Heartstone pressed against her" | | 3 | "Its crimson centre pulsed once." | | 4 | "The world simply drew a" | | 5 | "Vines curled through the opening," | | 6 | "Nyx leaned closer." | | 7 | "Their tall silhouette thinned at" | | 8 | "their wind-borne voice murmured" | | 9 | "Isolde touched one of the" | | 10 | "Her silver hair drifted around" | | 11 | "Aurora glanced at her." | | 12 | "Isolde’s pale lavender eyes rested" | | 13 | "Aurora drew the Fae-forged blade" | | 14 | "Moonlight gathered along the slender," | | 15 | "She held it out and" | | 16 | "The Veil shuddered." | | 17 | "A thin crack of silver" | | 18 | "The rift opened another foot." | | 19 | "Aurora looked back." |
| | ratio | 0.819 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 166 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 52 | | technicalSentenceCount | 2 | | matches | | 0 | "The sky stretched above them in a vast sheet of warm amber, darker near the horizon and bright overhead, as if the heavens held a sun beneath their surface." | | 1 | "The trees bore unfamiliar fruit: pale spheres dusted with frost, long red pods that twitched when the wind touched them, and clusters of translucent berries fil…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 32.35% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 8 | | fancyTags | | 0 | "their wind-borne voice murmured (murmur)" | | 1 | "she murmured (murmur)" | | 2 | "it croaked (croak)" | | 3 | "Nyx whispered (whisper)" | | 4 | "Eva muttered (mutter)" | | 5 | "she murmured (murmur)" | | 6 | "Eva muttered (mutter)" | | 7 | "she murmured (murmur)" |
| | dialogueSentences | 68 | | tagDensity | 0.235 | | leniency | 0.471 | | rawRatio | 0.5 | | effectiveRatio | 0.235 | |