| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.441 | | leniency | 0.882 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1083 | | 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) | |
| 67.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1083 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "traced" | | 2 | "glint" | | 3 | "etched" | | 4 | "quivered" | | 5 | "pulse" |
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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 | 75 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 75 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1075 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 97.58% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 763 | | uniqueNames | 6 | | maxNameDensity | 1.05 | | worstName | "Reyes" | | maxWindowNameDensity | 2 | | worstWindowName | "Reyes" | | discoveredNames | | Quinn | 7 | | Tube | 1 | | Council | 1 | | Reyes | 8 | | London | 1 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Council" | | 2 | "Reyes" | | 3 | "Morris" |
| | places | | | globalScore | 0.976 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.93 | | wordCount | 1075 | | matches | | 0 | "Not the give-and-stay of fresh death but the resistance of something already half-mummified" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 29.05 | | std | 24.66 | | cv | 0.849 | | sampleLengths | | 0 | 40 | | 1 | 12 | | 2 | 69 | | 3 | 23 | | 4 | 19 | | 5 | 8 | | 6 | 39 | | 7 | 5 | | 8 | 51 | | 9 | 42 | | 10 | 12 | | 11 | 3 | | 12 | 4 | | 13 | 64 | | 14 | 6 | | 15 | 4 | | 16 | 54 | | 17 | 32 | | 18 | 20 | | 19 | 10 | | 20 | 13 | | 21 | 62 | | 22 | 65 | | 23 | 6 | | 24 | 3 | | 25 | 31 | | 26 | 7 | | 27 | 51 | | 28 | 77 | | 29 | 8 | | 30 | 7 | | 31 | 11 | | 32 | 67 | | 33 | 5 | | 34 | 54 | | 35 | 77 | | 36 | 14 |
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| 81.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 75 | | matches | | 0 | "been called" | | 1 | "been bricked" | | 2 | "been told" | | 3 | "been positioned" | | 4 | "were curled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 131 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 93 | | ratio | 0.075 | | matches | | 0 | "The smell hit Quinn before the cold did—copper and something older, like wet stone that had never seen sun." | | 1 | "Around him someone had arranged a ring of candles—nine of them, black wax, burned to even stubs." | | 2 | "The strokes ran the wrong direction—drawn outward, from the body to the candles, not inward." | | 3 | "The fingers were curled, and between them—she'd nearly missed it—a glint of dull metal." | | 4 | "The casing wore a crust of green corrosion, and across its face, instead of N-S-E-W, someone had etched a tangle of marks she didn't have words for—the same family of strokes as the chalk on the floor." | | 5 | "Three years she'd carried a question with no shape to it—Morris, gone in a stairwell with no blood and no body and no reason, a case the brass had quietly buried." | | 6 | "Reyes said nothing—which told her the boy had instincts after all." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 775 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.016774193548387096 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003870967741935484 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 11.56 | | std | 9.21 | | cv | 0.797 | | sampleLengths | | 0 | 19 | | 1 | 21 | | 2 | 9 | | 3 | 3 | | 4 | 13 | | 5 | 19 | | 6 | 9 | | 7 | 28 | | 8 | 10 | | 9 | 1 | | 10 | 12 | | 11 | 12 | | 12 | 7 | | 13 | 8 | | 14 | 30 | | 15 | 9 | | 16 | 3 | | 17 | 2 | | 18 | 16 | | 19 | 2 | | 20 | 6 | | 21 | 20 | | 22 | 6 | | 23 | 1 | | 24 | 17 | | 25 | 17 | | 26 | 8 | | 27 | 6 | | 28 | 6 | | 29 | 3 | | 30 | 2 | | 31 | 2 | | 32 | 21 | | 33 | 27 | | 34 | 16 | | 35 | 4 | | 36 | 2 | | 37 | 4 | | 38 | 28 | | 39 | 18 | | 40 | 8 | | 41 | 6 | | 42 | 17 | | 43 | 9 | | 44 | 11 | | 45 | 9 | | 46 | 10 | | 47 | 10 | | 48 | 3 | | 49 | 7 |
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| 79.93% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5053763440860215 | | totalSentences | 93 | | uniqueOpeners | 47 | |
| 54.64% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 61 | | matches | | 0 | "Then it twitched a quarter-turn" |
| | ratio | 0.016 | |
| 88.85% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 61 | | matches | | 0 | "She ducked under the strip" | | 1 | "She took it anyway, felt" | | 2 | "She nodded at the tiles" | | 3 | "She leaned closer" | | 4 | "She lifted the dead man's" | | 5 | "It came up light, too" | | 6 | "She turned her attention to" | | 7 | "She traced the lines with" | | 8 | "It wasn't a pentagram." | | 9 | "They'd been holding something back." | | 10 | "They overlapped at the points" | | 11 | "She stood, knees cracking" | | 12 | "She'd crouched again, this time" | | 13 | "She eased the hand open." | | 14 | "It quivered, swung, settled toward" | | 15 | "She didn't look up from" | | 16 | "It swung again, restless, like" | | 17 | "Her mouth had gone dry." | | 18 | "She closed his fingers back" | | 19 | "she went on, standing, She" |
| | ratio | 0.328 | |
| 33.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 52 | | totalSentences | 61 | | matches | | 0 | "The smell hit Quinn before" | | 1 | "She ducked under the strip" | | 2 | "She took it anyway, felt" | | 3 | "Camden Council had no record" | | 4 | "The door at street level" | | 5 | "DC Reyes met her at" | | 6 | "Reyes gestured down the platform," | | 7 | "Quinn said nothing." | | 8 | "The platform stretched into blackness" | | 9 | "That was the first wrong" | | 10 | "Every abandoned station in London" | | 11 | "This one looked sealed in" | | 12 | "The body lay at the" | | 13 | "Reyes crouched at the edge" | | 14 | "Quinn pulled a glove tight" | | 15 | "She nodded at the tiles" | | 16 | "Reyes opened his mouth." | | 17 | "She leaned closer" | | 18 | "The man's skin had a" | | 19 | "She lifted the dead man's" |
| | ratio | 0.852 | |
| 81.97% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 61 | | matches | | 0 | "Whoever made these marks hadn't" |
| | ratio | 0.016 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "The smell hit Quinn before the cold did—copper and something older, like wet stone that had never seen sun." |
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| 91.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 1 | | matches | | 0 | "She stood, knees cracking" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 34 | | tagDensity | 0.088 | | leniency | 0.176 | | rawRatio | 0.333 | | effectiveRatio | 0.059 | |