| 75.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "The voice coiled around [around]" |
| | dialogueSentences | 15 | | tagDensity | 0.533 | | leniency | 1 | | rawRatio | 0.125 | | effectiveRatio | 0.125 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1090 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 44.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1090 | | totalAiIsms | 12 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | word | "down her spine" | | count | 1 |
| | 11 | |
| | highlights | | 0 | "silence" | | 1 | "pulse" | | 2 | "warmth" | | 3 | "footsteps" | | 4 | "echo" | | 5 | "pulsed" | | 6 | "trembled" | | 7 | "scanning" | | 8 | "navigating" | | 9 | "whisper" | | 10 | "down her spine" | | 11 | "flickered" |
| |
| 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 | 103 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 103 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1085 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.27% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1005 | | uniqueNames | 10 | | maxNameDensity | 1.09 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Grove" | | discoveredNames | | Fae | 2 | | Grove | 6 | | Richmond | 1 | | Park | 1 | | Heartstone | 1 | | Pendant | 1 | | Isolde | 2 | | Court | 1 | | Rory | 11 | | Eva | 1 |
| | persons | | 0 | "Pendant" | | 1 | "Isolde" | | 2 | "Court" | | 3 | "Rory" | | 4 | "Eva" |
| | places | | 0 | "Fae" | | 1 | "Grove" | | 2 | "Richmond" | | 3 | "Park" |
| | globalScore | 0.953 | | windowScore | 1 | |
| 20.13% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 4 | | matches | | 0 | "seemed deeper than they should be, refusing to yield when she stared directly at them" | | 1 | "felt like twenty seconds" | | 2 | "not quite" | | 3 | "felt like fingertips trailing down her" |
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| 15.67% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.843 | | wordCount | 1085 | | matches | | 0 | "Not temperature change, but something beneath" | | 1 | "Not like fog or mist, but like something alive turning its attention toward her" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 35 | | std | 18.17 | | cv | 0.519 | | sampleLengths | | 0 | 14 | | 1 | 62 | | 2 | 58 | | 3 | 50 | | 4 | 64 | | 5 | 12 | | 6 | 2 | | 7 | 47 | | 8 | 41 | | 9 | 34 | | 10 | 22 | | 11 | 66 | | 12 | 43 | | 13 | 38 | | 14 | 14 | | 15 | 61 | | 16 | 44 | | 17 | 31 | | 18 | 6 | | 19 | 45 | | 20 | 38 | | 21 | 30 | | 22 | 14 | | 23 | 53 | | 24 | 42 | | 25 | 22 | | 26 | 41 | | 27 | 40 | | 28 | 28 | | 29 | 5 | | 30 | 18 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 103 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 168 | | matches | | |
| 38.96% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 110 | | ratio | 0.036 | | matches | | 0 | "The city sounds—distant traffic, the hum of Richmond Park's nocturnal life—cut off as if someone had pressed a mute button." | | 1 | "Not that she'd expected one—time inside the Grove moved at its own rhythm, and technology refused to cooperate with whatever rules governed this place." | | 2 | "She'd marked it with a strip of red fabric tied to a branch—a trick Eva had taught her for navigating faerie-touched places." | | 3 | "The darkness took shape—not a figure, not quite." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1020 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.03431372549019608 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004901960784313725 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 9.86 | | std | 6.63 | | cv | 0.673 | | sampleLengths | | 0 | 14 | | 1 | 4 | | 2 | 20 | | 3 | 8 | | 4 | 21 | | 5 | 6 | | 6 | 1 | | 7 | 2 | | 8 | 10 | | 9 | 22 | | 10 | 2 | | 11 | 24 | | 12 | 18 | | 13 | 11 | | 14 | 10 | | 15 | 11 | | 16 | 12 | | 17 | 1 | | 18 | 9 | | 19 | 10 | | 20 | 10 | | 21 | 22 | | 22 | 10 | | 23 | 2 | | 24 | 2 | | 25 | 18 | | 26 | 7 | | 27 | 1 | | 28 | 9 | | 29 | 12 | | 30 | 3 | | 31 | 6 | | 32 | 7 | | 33 | 16 | | 34 | 9 | | 35 | 1 | | 36 | 1 | | 37 | 21 | | 38 | 11 | | 39 | 18 | | 40 | 4 | | 41 | 7 | | 42 | 2 | | 43 | 18 | | 44 | 3 | | 45 | 7 | | 46 | 13 | | 47 | 16 | | 48 | 4 | | 49 | 2 |
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| 55.76% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4 | | totalSentences | 110 | | uniqueOpeners | 44 | |
| 74.07% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 90 | | matches | | 0 | "Just bark and shadow and" | | 1 | "Then guttered like a candle" |
| | ratio | 0.022 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 90 | | matches | | 0 | "She'd come here because Isolde" | | 1 | "They jutted from the earth" | | 2 | "Her voice came out flat," | | 3 | "She ran her fingers along" | | 4 | "She said it louder this" | | 5 | "She'd entered at nine-thirty." | | 6 | "She waited, counting seconds in" | | 7 | "She jumped, spinning, but found" | | 8 | "She'd marked it with a" | | 9 | "She'd entered through a gap" | | 10 | "She'd walked through that gap" | | 11 | "She went down hard, the" | | 12 | "She clutched it in her" | | 13 | "Her voice cracked, but she" | | 14 | "It stood at the treeline," | | 15 | "It paused, and the darkness" | | 16 | "She had come alone because" | | 17 | "She should have known better." |
| | ratio | 0.2 | |
| 87.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 90 | | matches | | 0 | "Rory pushed through the last" | | 1 | "The air changed immediately." | | 2 | "The city sounds—distant traffic, the" | | 3 | "The Heartstone Pendant rested warm" | | 4 | "She'd come here because Isolde" | | 5 | "Something about the Fae Court's" | | 6 | "The moon hung fat and" | | 7 | "They jutted from the earth" | | 8 | "Wildflowers dotted the clearing, their" | | 9 | "A gentle breeze stirred the" | | 10 | "A hidden pocket where the" | | 11 | "The way her footsteps made" | | 12 | "The way the shadows between" | | 13 | "Her voice came out flat," | | 14 | "Rory walked to the center" | | 15 | "She ran her fingers along" | | 16 | "The pendant pulsed again, harder," | | 17 | "The air shifted." | | 18 | "A vibration she felt in" | | 19 | "The wildflowers at her feet" |
| | ratio | 0.744 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 4 | | totalSentences | 90 | | matches | | 0 | "Now, standing alone in the" | | 1 | "Now, though, some fundamental quality" | | 2 | "Now those two oaks stood" | | 3 | "Because she'd trusted the fae" |
| | ratio | 0.044 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 2 | | matches | | 0 | "The city sounds—distant traffic, the hum of Richmond Park's nocturnal life—cut off as if someone had pressed a mute button." | | 1 | "The moon above winked out as if cloud-covered, but no clouds had been there seconds ago." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "It paused, and the darkness seemed to swell" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 15 | | tagDensity | 0.067 | | leniency | 0.133 | | rawRatio | 0 | | effectiveRatio | 0 | |