| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 69 | | tagDensity | 0.072 | | leniency | 0.145 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1333 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "slightly" | | 1 | "suddenly" | | 2 | "really" | | 3 | "very" |
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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) | |
| 24.98% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1333 | | totalAiIsms | 20 | | found | | | highlights | | 0 | "standard" | | 1 | "silence" | | 2 | "etched" | | 3 | "intricate" | | 4 | "familiar" | | 5 | "predator" | | 6 | "perfect" | | 7 | "rhythmic" | | 8 | "scanning" | | 9 | "weight" | | 10 | "dancing" | | 11 | "echo" | | 12 | "silk" | | 13 | "structure" | | 14 | "could feel" | | 15 | "flickered" |
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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) | |
| 47.62% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 4 | | narrationSentences | 75 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "tended to" | | 2 | "began to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 139 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1333 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 32 | | wordCount | 904 | | uniqueNames | 10 | | maxNameDensity | 1.66 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 15 | | Camden | 1 | | Tube | 2 | | Morris | 1 | | British | 1 | | Museum | 1 | | Eva | 1 | | Veil | 1 | | Compass | 1 | | Miller | 8 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Eva" | | 3 | "Miller" |
| | places | (empty) | | globalScore | 0.67 | | windowScore | 0.667 | |
| 73.08% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 2 | | matches | | 0 | "patterns that seemed to shift when the light hit them" | | 1 | "space that seemed to pull the very air from Quinn's lungs" |
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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 | 1333 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 139 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 89 | | mean | 14.98 | | std | 15.19 | | cv | 1.014 | | sampleLengths | | 0 | 46 | | 1 | 13 | | 2 | 34 | | 3 | 1 | | 4 | 42 | | 5 | 52 | | 6 | 5 | | 7 | 1 | | 8 | 7 | | 9 | 29 | | 10 | 6 | | 11 | 40 | | 12 | 7 | | 13 | 9 | | 14 | 54 | | 15 | 13 | | 16 | 1 | | 17 | 2 | | 18 | 3 | | 19 | 50 | | 20 | 6 | | 21 | 2 | | 22 | 13 | | 23 | 42 | | 24 | 5 | | 25 | 6 | | 26 | 43 | | 27 | 6 | | 28 | 2 | | 29 | 26 | | 30 | 5 | | 31 | 4 | | 32 | 9 | | 33 | 41 | | 34 | 3 | | 35 | 3 | | 36 | 30 | | 37 | 12 | | 38 | 9 | | 39 | 3 | | 40 | 45 | | 41 | 4 | | 42 | 7 | | 43 | 7 | | 44 | 39 | | 45 | 5 | | 46 | 3 | | 47 | 6 | | 48 | 3 | | 49 | 19 |
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| 95.91% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 75 | | matches | | 0 | "been cauterised" | | 1 | "being dragged" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 149 | | matches | | 0 | "was already dancing" | | 1 | "wasn't just pointing" | | 2 | "was vibrating" | | 3 | "wasn't coming" | | 4 | "was coming" | | 5 | "was descending" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 139 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 907 | | adjectiveStacks | 2 | | stackExamples | | 0 | "frantic, high-pitched hum" | | 1 | "cold, grit-covered floor." |
| | adverbCount | 27 | | adverbRatio | 0.029768467475192944 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006615214994487321 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 139 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 139 | | mean | 9.59 | | std | 6.43 | | cv | 0.671 | | sampleLengths | | 0 | 20 | | 1 | 26 | | 2 | 13 | | 3 | 16 | | 4 | 18 | | 5 | 1 | | 6 | 28 | | 7 | 14 | | 8 | 11 | | 9 | 4 | | 10 | 9 | | 11 | 5 | | 12 | 23 | | 13 | 5 | | 14 | 1 | | 15 | 7 | | 16 | 10 | | 17 | 11 | | 18 | 8 | | 19 | 6 | | 20 | 27 | | 21 | 13 | | 22 | 7 | | 23 | 9 | | 24 | 12 | | 25 | 7 | | 26 | 13 | | 27 | 22 | | 28 | 7 | | 29 | 6 | | 30 | 1 | | 31 | 2 | | 32 | 3 | | 33 | 12 | | 34 | 15 | | 35 | 23 | | 36 | 6 | | 37 | 2 | | 38 | 13 | | 39 | 3 | | 40 | 7 | | 41 | 5 | | 42 | 3 | | 43 | 24 | | 44 | 5 | | 45 | 6 | | 46 | 22 | | 47 | 14 | | 48 | 7 | | 49 | 6 |
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| 39.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 19 | | diversityRatio | 0.31654676258992803 | | totalSentences | 139 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 84.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 74 | | matches | | 0 | "He wiped a bead of" | | 1 | "She ignored the ache." | | 2 | "Her eyes tracked the line" | | 3 | "He fumbled with the victim's" | | 4 | "He paused, pulling out a" | | 5 | "She moved toward the victim's" | | 6 | "It was a bone token," | | 7 | "It was the same sensation" | | 8 | "She leaned closer to the" | | 9 | "They were sigils." | | 10 | "They were the same symbols" | | 11 | "She straightened her jacket and" | | 12 | "It had hit the tiles" | | 13 | "She hadn't intended to use" | | 14 | "It snapped toward the dark" | | 15 | "It wasn't the distant rumble" | | 16 | "It was a wet, sliding" | | 17 | "It was large, dark, and" | | 18 | "It vanished before the light" | | 19 | "He stared at the device," |
| | ratio | 0.338 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 74 | | matches | | 0 | "The heavy, black, rubber seal" | | 1 | "Dust motes danced in the" | | 2 | "Miller stood over the body," | | 3 | "He wiped a bead of" | | 4 | "Miller gestured with a gloved" | | 5 | "Quinn knelt, the joints in" | | 6 | "She ignored the ache." | | 7 | "Her eyes tracked the line" | | 8 | "The wound didn't look clean." | | 9 | "The edges of the flesh" | | 10 | "Miller leaned in, his breathing" | | 11 | "He fumbled with the victim's" | | 12 | "He paused, pulling out a" | | 13 | "Quinn pointed to the heavy," | | 14 | "Quinn reached into her kit" | | 15 | "She moved toward the victim's" | | 16 | "It was a bone token," | | 17 | "Miller asked, stepping closer" | | 18 | "Quinn felt the familiar, cold" | | 19 | "It was the same sensation" |
| | ratio | 0.959 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 74 | | matches | (empty) | | ratio | 0 | |
| 79.37% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 4 | | matches | | 0 | "The edges of the flesh curled outward, jagged and blackened, as if the blade had been cauterised by something more volatile than steel." | | 1 | "It was a bone token, white and porous, etched with intricate, swirling patterns that seemed to shift when the light hit them." | | 2 | "It had no face, only a vertical slit that peeled open to reveal rows of needle-thin teeth." | | 3 | "The creature was descending, its limbs spreading wide like the legs of a massive, starving spider." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 2 | | matches | | 0 | "Quinn stood up, her military precision returning to her posture" | | 1 | "Miller whispered, his voice dropping an octave" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Miller whispered (whisper)" |
| | dialogueSentences | 69 | | tagDensity | 0.029 | | leniency | 0.058 | | rawRatio | 0.5 | | effectiveRatio | 0.029 | |