| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.176 | | leniency | 0.353 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 702 | | 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) | |
| 14.53% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 702 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flickered" | | 1 | "scanned" | | 2 | "weight" | | 3 | "familiar" | | 4 | "footsteps" | | 5 | "echoed" | | 6 | "electric" | | 7 | "glint" | | 8 | "shattered" | | 9 | "glinting" |
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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 | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 81 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 95 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 29 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 686 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 46.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 627 | | uniqueNames | 8 | | maxNameDensity | 2.07 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | God | 1 | | Quinn | 13 | | Raven | 1 | | Nest | 1 | | Veil | 1 | | Market | 1 | | Herrera | 1 | | Tomás | 3 |
| | persons | | 0 | "God" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Nest" | | 4 | "Market" | | 5 | "Herrera" | | 6 | "Tomás" |
| | places | (empty) | | globalScore | 0.463 | | windowScore | 0.667 | |
| 33.72% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 2 | | matches | | 0 | "smelled like decay, bones strung together" | | 1 | "looked like jars of eyeballs" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 686 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 95 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 16.73 | | std | 15.44 | | cv | 0.923 | | sampleLengths | | 0 | 52 | | 1 | 47 | | 2 | 38 | | 3 | 37 | | 4 | 4 | | 5 | 53 | | 6 | 2 | | 7 | 12 | | 8 | 21 | | 9 | 46 | | 10 | 3 | | 11 | 43 | | 12 | 5 | | 13 | 32 | | 14 | 18 | | 15 | 17 | | 16 | 9 | | 17 | 9 | | 18 | 8 | | 19 | 4 | | 20 | 25 | | 21 | 6 | | 22 | 14 | | 23 | 36 | | 24 | 14 | | 25 | 3 | | 26 | 10 | | 27 | 5 | | 28 | 6 | | 29 | 2 | | 30 | 2 | | 31 | 33 | | 32 | 11 | | 33 | 10 | | 34 | 7 | | 35 | 3 | | 36 | 9 | | 37 | 11 | | 38 | 9 | | 39 | 5 | | 40 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 81 | | matches | (empty) | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 114 | | matches | | 0 | "wasn’t letting" | | 1 | "was waiting" | | 2 | "was pressing" | | 3 | "was weaving" | | 4 | "was running" | | 5 | "wasn’t backing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 95 | | ratio | 0.095 | | matches | | 0 | "The suspect—some wiry bloke in a too-long coat—had ducked inside moments before her, but Quinn wasn’t letting him slip through her fingers again." | | 1 | "She pushed through the sticky door, the scent of stale beer and something metallic—copper, maybe—hitting her first." | | 2 | "Then—a movement near the back." | | 3 | "She knocked twice—sharp, military precision—and the shelf swung inward like it was waiting." | | 4 | "The walls were slick with moisture, the torchlight revealing graffiti—symbols she didn’t recognise, some looking like claw marks, others like twisted sigils." | | 5 | "Stalls lined the edges, their wares glowing faintly in the dim light—bottles of swirling liquid, bundles of herbs that smelled like decay, bones strung together like wind chimes." | | 6 | "The suspect—face pale, eyes darting—was weaving through the crowd, shoving past a stall selling what looked like jars of eyeballs." | | 7 | "And he was running from something—or someone." | | 8 | "Quinn spun, torch swinging up—just in time to see the glint of a knife." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 642 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.037383177570093455 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.003115264797507788 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 95 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 95 | | mean | 7.22 | | std | 5.66 | | cv | 0.783 | | sampleLengths | | 0 | 12 | | 1 | 18 | | 2 | 19 | | 3 | 3 | | 4 | 23 | | 5 | 7 | | 6 | 17 | | 7 | 15 | | 8 | 8 | | 9 | 4 | | 10 | 5 | | 11 | 2 | | 12 | 2 | | 13 | 2 | | 14 | 12 | | 15 | 10 | | 16 | 1 | | 17 | 1 | | 18 | 13 | | 19 | 4 | | 20 | 19 | | 21 | 11 | | 22 | 12 | | 23 | 11 | | 24 | 2 | | 25 | 4 | | 26 | 1 | | 27 | 1 | | 28 | 6 | | 29 | 11 | | 30 | 10 | | 31 | 15 | | 32 | 22 | | 33 | 9 | | 34 | 3 | | 35 | 28 | | 36 | 8 | | 37 | 7 | | 38 | 5 | | 39 | 20 | | 40 | 12 | | 41 | 12 | | 42 | 6 | | 43 | 5 | | 44 | 5 | | 45 | 7 | | 46 | 6 | | 47 | 3 | | 48 | 5 | | 49 | 4 |
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| 57.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.37894736842105264 | | totalSentences | 95 | | uniqueOpeners | 36 | |
| 99.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 67 | | matches | | 0 | "Then—a movement near the back." | | 1 | "Then Tomás exhaled, slow and" |
| | ratio | 0.03 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 67 | | matches | | 0 | "She didn’t slow." | | 1 | "She pushed through the sticky" | | 2 | "She strode toward it, her" | | 3 | "She knocked twice—sharp, military precision—and" | | 4 | "She holstered the gun, unsnapped" | | 5 | "she barked, her voice cutting" | | 6 | "He froze, then turned slowly." | | 7 | "she shot back" | | 8 | "His smirk faltered." | | 9 | "She didn’t buy it." | | 10 | "She sidestepped, the edge grazing" | | 11 | "She drove her elbow into" | | 12 | "His eyes rolled back." | | 13 | "His dark eyes locked onto" | | 14 | "She knew he was right." |
| | ratio | 0.224 | |
| 19.70% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 67 | | matches | | 0 | "The rain hammered down like" | | 1 | "Harlow Quinn pulled her collar" | | 2 | "The neon glow of The" | | 3 | "She didn’t slow." | | 4 | "The suspect—some wiry bloke in" | | 5 | "She pushed through the sticky" | | 6 | "The bar was half-empty, the" | | 7 | "Quinn scanned the room, her" | | 8 | "She strode toward it, her" | | 9 | "The wood groaned as she" | | 10 | "She knocked twice—sharp, military precision—and" | | 11 | "Darkness swallowed her whole." | | 12 | "A draft rushed out, carrying" | | 13 | "Quinn drew her service revolver," | | 14 | "The hidden room yawned before" | | 15 | "A single flickering bulb cast" | | 16 | "Footsteps echoed from below." | | 17 | "The suspect was already down" | | 18 | "Quinn exhaled through her nose," | | 19 | "She holstered the gun, unsnapped" |
| | ratio | 0.881 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 67 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 2 | | matches | | 0 | "A draft rushed out, carrying the stink of damp earth and something older, something that made her skin prickle." | | 1 | "Stalls lined the edges, their wares glowing faintly in the dim light—bottles of swirling liquid, bundles of herbs that smelled like decay, bones strung together…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 1 | | matches | | 0 | "she barked, her voice cutting through the murmur of haggling voices" |
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| 32.35% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she barked (bark)" | | 1 | "she growled (growl)" |
| | dialogueSentences | 17 | | tagDensity | 0.118 | | leniency | 0.235 | | rawRatio | 1 | | effectiveRatio | 0.235 | |