| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 9 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.45 | | leniency | 0.9 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 86.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1091 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slightly" | | 1 | "lazily" | | 2 | "sharply" |
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| 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) | |
| 35.84% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1091 | | totalAiIsms | 14 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | word | "the last thing" | | count | 1 |
| | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "shattered" | | 1 | "perfect" | | 2 | "shimmered" | | 3 | "etched" | | 4 | "the last thing" | | 5 | "traced" | | 6 | "glinting" | | 7 | "pulse" | | 8 | "flickered" | | 9 | "searing" | | 10 | "silence" | | 11 | "pulsed" | | 12 | "whisper" |
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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 | 118 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 118 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 13 | | totalWords | 1084 | | ratio | 0.012 | | matches | | 0 | "Something’s not right down there, ma’am. Not right at all." | | 1 | "compass" | | 2 | "“Find me.”" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 95.05% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 1001 | | uniqueNames | 5 | | maxNameDensity | 1.1 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Tube | 2 | | Quinn | 11 | | London | 1 | | Carter | 10 | | Adam | 1 |
| | persons | | | places | | | globalScore | 0.951 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 68 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like dried mud—or ash" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.768 | | wordCount | 1084 | | matches | | 0 | "not with the usual London underground vibration, but with something else" | | 1 | "not north, but directly at the body" | | 2 | "not darkness, but a market" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 129 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 42 | | mean | 25.81 | | std | 24.55 | | cv | 0.951 | | sampleLengths | | 0 | 69 | | 1 | 42 | | 2 | 75 | | 3 | 75 | | 4 | 4 | | 5 | 21 | | 6 | 47 | | 7 | 5 | | 8 | 6 | | 9 | 75 | | 10 | 6 | | 11 | 41 | | 12 | 48 | | 13 | 15 | | 14 | 58 | | 15 | 1 | | 16 | 58 | | 17 | 8 | | 18 | 5 | | 19 | 46 | | 20 | 4 | | 21 | 2 | | 22 | 69 | | 23 | 12 | | 24 | 1 | | 25 | 25 | | 26 | 10 | | 27 | 15 | | 28 | 9 | | 29 | 17 | | 30 | 22 | | 31 | 2 | | 32 | 32 | | 33 | 65 | | 34 | 19 | | 35 | 1 | | 36 | 29 | | 37 | 25 | | 38 | 4 | | 39 | 2 | | 40 | 12 | | 41 | 2 |
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| 84.45% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 118 | | matches | | 0 | "was loosened" | | 1 | "was unmarred" | | 2 | "was gone" | | 3 | "were curled" | | 4 | "was jagged" | | 5 | "been snapped" | | 6 | "were clenched" | | 7 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 173 | | matches | (empty) | |
| 54.26% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 129 | | ratio | 0.031 | | matches | | 0 | "The abandoned Tube station reeked of damp concrete and something older—something that clung to the back of Quinn’s throat like rust." | | 1 | "She scraped at it with her pen, catching a flake of what looked like dried mud—or ash." | | 2 | "The beam caught on something glinting in the dark—a scattering of small, white objects half-buried in the grime." | | 3 | "Figures moved between the stalls—some human, some not." |
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| 85.60% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1008 | | adjectiveStacks | 1 | | stackExamples | | 0 | "lay abandoned beside him," |
| | adverbCount | 50 | | adverbRatio | 0.0496031746031746 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.010912698412698412 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 8.4 | | std | 5.75 | | cv | 0.684 | | sampleLengths | | 0 | 21 | | 1 | 19 | | 2 | 14 | | 3 | 15 | | 4 | 13 | | 5 | 15 | | 6 | 14 | | 7 | 12 | | 8 | 3 | | 9 | 32 | | 10 | 18 | | 11 | 6 | | 12 | 4 | | 13 | 12 | | 14 | 13 | | 15 | 13 | | 16 | 12 | | 17 | 4 | | 18 | 3 | | 19 | 18 | | 20 | 4 | | 21 | 18 | | 22 | 3 | | 23 | 11 | | 24 | 10 | | 25 | 5 | | 26 | 4 | | 27 | 11 | | 28 | 6 | | 29 | 5 | | 30 | 4 | | 31 | 2 | | 32 | 3 | | 33 | 4 | | 34 | 9 | | 35 | 14 | | 36 | 17 | | 37 | 1 | | 38 | 10 | | 39 | 17 | | 40 | 6 | | 41 | 3 | | 42 | 24 | | 43 | 14 | | 44 | 11 | | 45 | 7 | | 46 | 14 | | 47 | 12 | | 48 | 4 | | 49 | 5 |
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| 43.41% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.3023255813953488 | | totalSentences | 129 | | uniqueOpeners | 39 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 102 | | matches | | 0 | "Just a single, neat puncture" | | 1 | "Just that single, perfect hole." | | 2 | "Instead, she shifted her gaze" | | 3 | "Just the faintest smudge of" | | 4 | "Too small, too delicate." | | 5 | "Then she saw it." | | 6 | "Then she heard it." |
| | ratio | 0.069 | |
| 90.59% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 102 | | matches | | 0 | "Her torch cut through the" | | 1 | "His torch lay abandoned beside" | | 2 | "She didn’t answer." | | 3 | "She crouched beside Carter, her" | | 4 | "His tie was loosened, his" | | 5 | "She reached out, her gloved" | | 6 | "She leaned in closer." | | 7 | "She blinked, and it was" | | 8 | "She didn’t repeat herself." | | 9 | "His fingers were curled slightly," | | 10 | "She reached into her pocket," | | 11 | "She scraped at it with" | | 12 | "He held up a small," | | 13 | "She’d seen enough forgeries in" | | 14 | "She followed its direction with" | | 15 | "She stood, her boots splashing" | | 16 | "She crouched again, picking one" | | 17 | "It was light, almost hollow." | | 18 | "She turned it over." | | 19 | "she asked, holding it up" |
| | ratio | 0.324 | |
| 62.94% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 102 | | matches | | 0 | "The abandoned Tube station reeked" | | 1 | "Her torch cut through the" | | 2 | "The air hummed, not with" | | 3 | "A low, persistent thrum, like" | | 4 | "The voice came from the" | | 5 | "DS Carter didn’t turn around," | | 6 | "His torch lay abandoned beside" | | 7 | "Quinn stepped over a shattered" | | 8 | "She didn’t answer." | | 9 | "*Something’s not right down there," | | 10 | "She crouched beside Carter, her" | | 11 | "The body lay sprawled across" | | 12 | "A man, mid-thirties, dressed in" | | 13 | "His tie was loosened, his" | | 14 | "Carter exhaled through his nose," | | 15 | "She reached out, her gloved" | | 16 | "The skin around it was" | | 17 | "She leaned in closer." | | 18 | "The air above the body" | | 19 | "She blinked, and it was" |
| | ratio | 0.794 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 102 | | matches | (empty) | | ratio | 0 | |
| 99.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 3 | | matches | | 0 | "The abandoned Tube station reeked of damp concrete and something older—something that clung to the back of Quinn’s throat like rust." | | 1 | "Stalls lined a cavernous space, their awnings strung with lanterns that cast a sickly, greenish light." | | 2 | "A man with skin like cracked leather hissed, baring teeth that were too sharp, too numerous." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 9 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.35 | | leniency | 0.7 | | rawRatio | 0 | | effectiveRatio | 0 | |