| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 7 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1408 | | 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) | |
| 36.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1408 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "pulsed" | | 1 | "throb" | | 2 | "warmth" | | 3 | "velvet" | | 4 | "electric" | | 5 | "silence" | | 6 | "footsteps" | | 7 | "weight" | | 8 | "whisper" | | 9 | "rhythmic" | | 10 | "could feel" | | 11 | "familiar" |
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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 | 149 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 149 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 153 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1390 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 35 | | wordCount | 1367 | | uniqueNames | 17 | | maxNameDensity | 0.95 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Carter | 1 | | December | 2 | | Eva | 4 | | Grove | 2 | | Fae | 1 | | Evan | 1 | | Aurora | 13 | | Stretched | 1 | | Cardiff | 1 | | Brecon | 1 | | Beacons | 1 | | Orion | 1 | | Plough | 1 | | Cassiopeia | 1 | | One | 2 |
| | persons | | 0 | "Carter" | | 1 | "December" | | 2 | "Eva" | | 3 | "Evan" | | 4 | "Aurora" | | 5 | "Stretched" | | 6 | "Orion" | | 7 | "Cassiopeia" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Grove" | | 3 | "Cardiff" | | 4 | "Brecon" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | 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 | 1390 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 153 | | matches | | 0 | "was that she’d" | | 1 | "slide that her" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 23.56 | | std | 20.13 | | cv | 0.855 | | sampleLengths | | 0 | 13 | | 1 | 54 | | 2 | 28 | | 3 | 5 | | 4 | 29 | | 5 | 74 | | 6 | 7 | | 7 | 63 | | 8 | 3 | | 9 | 1 | | 10 | 31 | | 11 | 25 | | 12 | 57 | | 13 | 10 | | 14 | 46 | | 15 | 14 | | 16 | 27 | | 17 | 7 | | 18 | 44 | | 19 | 4 | | 20 | 16 | | 21 | 3 | | 22 | 59 | | 23 | 1 | | 24 | 18 | | 25 | 8 | | 26 | 36 | | 27 | 34 | | 28 | 14 | | 29 | 21 | | 30 | 4 | | 31 | 43 | | 32 | 8 | | 33 | 43 | | 34 | 12 | | 35 | 44 | | 36 | 11 | | 37 | 17 | | 38 | 7 | | 39 | 44 | | 40 | 3 | | 41 | 43 | | 42 | 6 | | 43 | 44 | | 44 | 40 | | 45 | 57 | | 46 | 14 | | 47 | 2 | | 48 | 42 | | 49 | 59 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 149 | | matches | | |
| 52.51% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 226 | | matches | | 0 | "were drinking" | | 1 | "were gathering" | | 2 | "was coming" | | 3 | "were turning" | | 4 | "were watching" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 19 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 153 | | ratio | 0.092 | | matches | | 0 | "Not the clean bite of December air—something else." | | 1 | "Grass bent under her weight, released when she lifted her foot—but the rustle she expected never came." | | 2 | "Every instinct she’d honed through twenty-five years—through Evan’s tightening grip, through narrow alleys at midnight with a delivery bag slung over her shoulder—told her to turn around." | | 3 | "Wildflowers nodded in a breeze she couldn’t feel—foxgloves and nightshade and pale blooms she had no name for, all of them turned toward her like spectators in a darkened theatre." | | 4 | "Not a voice—too thin, too many notes layered over each other." | | 5 | "Not moving—she would have seen movement." | | 6 | "She knew the constellations her mother had pointed out on camping trips in the Brecon Beacons—Orion’s belt, the Plough, Cassiopeia’s crooked throne." | | 7 | "Aurora’s brain fumbled for a comparison and landed on film cuts—jump scares where the monster teleports—but this was slow." | | 8 | "“Eva!” she shouted, and this time the word carried further—three feet, maybe four—before the silence crushed it." | | 9 | "But another sound joined the harp-whisper now—a low, rhythmic scraping." | | 10 | "She noticed the condensation now—her own exhale, hanging suspended instead of dispersing." | | 11 | "The ground caught her—too soft, too giving—and the pendant swung up and hit her chin." | | 12 | "Footsteps—real footsteps, human footsteps, the crunch of gravel under sneakers—coming from beyond the circle." | | 13 | "She took a step toward the figure, her hand raised, her mouth opening to call out—" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1393 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.028715003589375447 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.005025125628140704 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 153 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 153 | | mean | 9.08 | | std | 6.84 | | cv | 0.753 | | sampleLengths | | 0 | 13 | | 1 | 18 | | 2 | 20 | | 3 | 16 | | 4 | 3 | | 5 | 3 | | 6 | 13 | | 7 | 2 | | 8 | 7 | | 9 | 5 | | 10 | 5 | | 11 | 15 | | 12 | 2 | | 13 | 7 | | 14 | 4 | | 15 | 8 | | 16 | 11 | | 17 | 15 | | 18 | 14 | | 19 | 10 | | 20 | 12 | | 21 | 7 | | 22 | 5 | | 23 | 11 | | 24 | 17 | | 25 | 10 | | 26 | 1 | | 27 | 19 | | 28 | 3 | | 29 | 1 | | 30 | 12 | | 31 | 4 | | 32 | 15 | | 33 | 4 | | 34 | 3 | | 35 | 18 | | 36 | 3 | | 37 | 27 | | 38 | 4 | | 39 | 1 | | 40 | 22 | | 41 | 10 | | 42 | 20 | | 43 | 3 | | 44 | 15 | | 45 | 8 | | 46 | 1 | | 47 | 6 | | 48 | 7 | | 49 | 13 |
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| 54.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3790849673202614 | | totalSentences | 153 | | uniqueOpeners | 58 | |
| 27.10% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 123 | | matches | | 0 | "Imperceptibly slow, grinding against the" |
| | ratio | 0.008 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 123 | | matches | | 0 | "She’d driven her delivery scooter" | | 1 | "She didn’t speak." | | 2 | "She’d been to the Grove" | | 3 | "Her footsteps made no sound." | | 4 | "She noticed that on the" | | 5 | "She scuffed her heel against" | | 6 | "Her voice came out flat" | | 7 | "It dropped from her lips" | | 8 | "She pressed her fingers to" | | 9 | "She should leave." | | 10 | "She pulled her hand back" | | 11 | "Her voice still wouldn’t travel." | | 12 | "It rose and fell and" | | 13 | "She backed into the center" | | 14 | "She didn’t dare pull it" | | 15 | "She lifted her chin." | | 16 | "She’d grown up in Cardiff," | | 17 | "She knew city stars and" | | 18 | "She knew the constellations her" | | 19 | "She dropped her gaze." |
| | ratio | 0.26 | |
| 86.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 123 | | matches | | 0 | "The gate at the edge" | | 1 | "Aurora Carter stepped through, her" | | 2 | "She’d driven her delivery scooter" | | 3 | "The pendant around her neck" | | 4 | "She didn’t speak." | | 5 | "The message from Eva had" | | 6 | "Something she couldn’t explain over" | | 7 | "Streetlamps ended fifty yards back." | | 8 | "Aurora pulled her jacket tighter" | | 9 | "The cold had teeth." | | 10 | "Something that crept beneath her" | | 11 | "She’d been to the Grove" | | 12 | "The standing stones had worn" | | 13 | "The air had hummed with" | | 14 | "Her footsteps made no sound." | | 15 | "She noticed that on the" | | 16 | "Grass bent under her weight," | | 17 | "She scuffed her heel against" | | 18 | "The sound existed in her" | | 19 | "Aurora stopped walking." |
| | ratio | 0.748 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 123 | | matches | | 0 | "Now the silence pressed against" | | 1 | "Because they were gathering." | | 2 | "Because the figure waved back." |
| | ratio | 0.024 | |
| 85.25% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 5 | | matches | | 0 | "Aurora Carter stepped through, her boots sinking into grass that felt too soft, too giving for December frost." | | 1 | "Ahead, the ancient oaks that marked the Grove’s boundary stood black against a star-scrubbed sky." | | 2 | "Aurora looked down and saw the pendant swinging free of her shirt, its crimson gem casting a light that slipped across the ground in oily tendrils." | | 3 | "The wildflowers on the clearing’s edge had stretched their stems to impossible lengths, their blooms craning toward her like faces straining for a better look." | | 4 | "Imperceptibly slow, grinding against the earth in a rotation that should have been impossible, their flat faces reorienting until every one of them pointed inwa…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 7 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.333 | | effectiveRatio | 0.286 | |