| 50.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 3 | | adverbTags | | 0 | "Eva said quietly [quietly]" | | 1 | "Harlow crouched again [again]" | | 2 | "Eva said softly [softly]" |
| | dialogueSentences | 34 | | tagDensity | 0.588 | | leniency | 1 | | rawRatio | 0.15 | | effectiveRatio | 0.15 | |
| 90.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1079 | | 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) | |
| 76.83% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1079 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "shattered" | | 1 | "traced" | | 2 | "etched" | | 3 | "pulsed" |
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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 | 79 | | matches | (empty) | |
| 88.61% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 79 | | filterMatches | | | 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 | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1071 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 29.75% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 790 | | uniqueNames | 11 | | maxNameDensity | 2.41 | | worstName | "Harlow" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 19 | | Quinn | 1 | | Camden | 2 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Eva | 15 | | Morris | 1 | | Veil | 2 | | Compass | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Camden" | | 3 | "Kowalski" | | 4 | "Museum" | | 5 | "Eva" | | 6 | "Morris" | | 7 | "Compass" |
| | places | | | globalScore | 0.297 | | windowScore | 0.5 | |
| 95.65% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 46 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a key to that door, cold and" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.934 | | wordCount | 1071 | | matches | | 0 | "not at the rift above, but at a second, hidden fissure behind a support beam" |
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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 | 42 | | mean | 25.5 | | std | 17.83 | | cv | 0.699 | | sampleLengths | | 0 | 72 | | 1 | 8 | | 2 | 55 | | 3 | 8 | | 4 | 12 | | 5 | 45 | | 6 | 27 | | 7 | 32 | | 8 | 10 | | 9 | 10 | | 10 | 24 | | 11 | 52 | | 12 | 22 | | 13 | 29 | | 14 | 15 | | 15 | 38 | | 16 | 52 | | 17 | 8 | | 18 | 10 | | 19 | 57 | | 20 | 6 | | 21 | 36 | | 22 | 28 | | 23 | 23 | | 24 | 5 | | 25 | 1 | | 26 | 27 | | 27 | 35 | | 28 | 5 | | 29 | 12 | | 30 | 64 | | 31 | 6 | | 32 | 11 | | 33 | 9 | | 34 | 45 | | 35 | 22 | | 36 | 16 | | 37 | 16 | | 38 | 41 | | 39 | 24 | | 40 | 28 | | 41 | 25 |
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| 96.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 79 | | matches | | 0 | "were blackened" | | 1 | "been flipped" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 141 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 93 | | ratio | 0.065 | | matches | | 0 | "The air downstairs tasted of wet limestone, copper, and something older—something that made the leather watch on her left wrist feel too light against her skin." | | 1 | "Her gloved fingers traced the victim’s pocket, pulling out a bone token—pale, polished, wrong for human anatomy." | | 2 | "The needle did not point north; it pointed straight up, toward the rift." | | 3 | "No footprints led to the body, but a second set—smaller, barefoot, with clawed impressions—circled the corpse and vanished into the rift above." | | 4 | "The sigils on the compass matched the burn marks on the victim’s clothes—protective, then turned aggressive." | | 5 | "The needle pointed not at the rift above, but at a second, hidden fissure behind a support beam—one that did not reveal itself to casual observation." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 799 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 19 | | adverbRatio | 0.023779724655819776 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010012515644555695 | |
| 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 | 11.52 | | std | 7.16 | | cv | 0.622 | | sampleLengths | | 0 | 19 | | 1 | 26 | | 2 | 27 | | 3 | 5 | | 4 | 3 | | 5 | 22 | | 6 | 18 | | 7 | 15 | | 8 | 8 | | 9 | 6 | | 10 | 6 | | 11 | 4 | | 12 | 5 | | 13 | 14 | | 14 | 3 | | 15 | 3 | | 16 | 16 | | 17 | 12 | | 18 | 15 | | 19 | 5 | | 20 | 17 | | 21 | 10 | | 22 | 10 | | 23 | 6 | | 24 | 4 | | 25 | 9 | | 26 | 15 | | 27 | 7 | | 28 | 10 | | 29 | 19 | | 30 | 3 | | 31 | 13 | | 32 | 8 | | 33 | 14 | | 34 | 7 | | 35 | 12 | | 36 | 10 | | 37 | 8 | | 38 | 7 | | 39 | 7 | | 40 | 9 | | 41 | 22 | | 42 | 12 | | 43 | 16 | | 44 | 24 | | 45 | 8 | | 46 | 6 | | 47 | 4 | | 48 | 27 | | 49 | 14 |
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| 42.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3010752688172043 | | totalSentences | 93 | | uniqueOpeners | 28 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 99.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 63 | | matches | | 0 | "Her close-cropped salt-and-pepper hair clung" | | 1 | "It was waiting." | | 2 | "Her worn leather satchel sagged" | | 3 | "She tucked a strand of" | | 4 | "She reached the crime scene." | | 5 | "Her gloved fingers traced the" | | 6 | "She turned it over, and" | | 7 | "She lifted it." | | 8 | "She turned the compass slowly," | | 9 | "She stood, sweeping her light" | | 10 | "She traced the scorch patterns" | | 11 | "She held the compass up," | | 12 | "She moved to the beam," | | 13 | "She pulled aside a loose" | | 14 | "She held up the Veil" | | 15 | "Its needle pointed to the" | | 16 | "She turned toward the hidden" | | 17 | "She understood now: the crime" | | 18 | "It was a receipt." |
| | ratio | 0.302 | |
| 7.62% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 63 | | matches | | 0 | "Detective Harlow Quinn pushed through" | | 1 | "The air downstairs tasted of" | | 2 | "Her close-cropped salt-and-pepper hair clung" | | 3 | "The station was not dead." | | 4 | "It was waiting." | | 5 | "Eva Kowalski stood beneath a" | | 6 | "Her worn leather satchel sagged" | | 7 | "She tucked a strand of" | | 8 | "Harlow's sharp jaw tightened." | | 9 | "She reached the crime scene." | | 10 | "A body lay crumpled against" | | 11 | "The victim’s fingers were blackened," | | 12 | "Eva stepped closer, her green" | | 13 | "Harlow dropped to one knee." | | 14 | "Her gloved fingers traced the" | | 15 | "She turned it over, and" | | 16 | "The tunnel roof had split" | | 17 | "Harlow pulled out her notebook," | | 18 | "A small brass compass lay" | | 19 | "The casing showed a patina" |
| | ratio | 0.905 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 65.64% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 4 | | matches | | 0 | "The air downstairs tasted of wet limestone, copper, and something older—something that made the leather watch on her left wrist feel too light against her skin." | | 1 | "The victim’s fingers were blackened, as if he had gripped something that burned colder than fire." | | 2 | "The casing showed a patina of verdigris, the face etched with protective sigils that shimmied in her flashlight’s beam." | | 3 | "The market’s schedule meant this station was a ghost now, abandoned by vendors who had moved to a new location beneath the full moon." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | 0 | "Harlow crouched again, her military precision turning every movement into measurement" |
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| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 2 | | fancyTags | | 0 | "Harlow snapped (snap)" | | 1 | "Harlow admitted (admit)" |
| | dialogueSentences | 34 | | tagDensity | 0.529 | | leniency | 1 | | rawRatio | 0.111 | | effectiveRatio | 0.111 | |