| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "Reyes offered already [already]" |
| | dialogueSentences | 27 | | tagDensity | 0.185 | | leniency | 0.37 | | rawRatio | 0.2 | | effectiveRatio | 0.074 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1028 | | 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) | |
| 95.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1028 | | totalAiIsms | 1 | | found | | | highlights | | |
| 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 | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 73 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1033 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 825 | | uniqueNames | 9 | | maxNameDensity | 0.85 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Detective | 1 | | Harlow | 1 | | Quinn | 7 | | Reyes | 5 | | Clean | 1 | | June | 2 | | Deptford | 1 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Reyes" | | 3 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 42 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.968 | | wordCount | 1033 | | matches | | 0 | "not for a second, but she filed the word away rather than argue" |
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| 29.68% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 73 | | matches | | 0 | "pull that colour" | | 1 | "seen that symbol" | | 2 | "learned that lesson" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 24.02 | | std | 22.47 | | cv | 0.935 | | sampleLengths | | 0 | 59 | | 1 | 7 | | 2 | 24 | | 3 | 11 | | 4 | 2 | | 5 | 11 | | 6 | 82 | | 7 | 5 | | 8 | 15 | | 9 | 30 | | 10 | 20 | | 11 | 8 | | 12 | 9 | | 13 | 26 | | 14 | 17 | | 15 | 3 | | 16 | 15 | | 17 | 42 | | 18 | 22 | | 19 | 3 | | 20 | 21 | | 21 | 8 | | 22 | 2 | | 23 | 3 | | 24 | 39 | | 25 | 59 | | 26 | 49 | | 27 | 6 | | 28 | 10 | | 29 | 5 | | 30 | 8 | | 31 | 13 | | 32 | 51 | | 33 | 21 | | 34 | 40 | | 35 | 85 | | 36 | 35 | | 37 | 4 | | 38 | 6 | | 39 | 7 | | 40 | 32 | | 41 | 79 | | 42 | 39 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 145 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 73 | | ratio | 0.055 | | matches | | 0 | "Clean, deep, precise — a blade that knew exactly where to go." | | 1 | "She'd stopped bothering to argue with people who needed the world to stay simple; it was easier to let them believe what let them sleep, and focus instead on the details that refused to fit." | | 2 | "Separately, each detail might explain itself away — bad luck, bad weather, bad memory." | | 3 | "He wrote it down, though his expression made clear he thought the request belonged in a different sort of file altogether — the kind stamped with words like fatigue and stress leave." |
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| 97.92% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 826 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.0423728813559322 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004842615012106538 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 73 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 73 | | mean | 14.15 | | std | 10.79 | | cv | 0.762 | | sampleLengths | | 0 | 33 | | 1 | 26 | | 2 | 7 | | 3 | 12 | | 4 | 12 | | 5 | 11 | | 6 | 2 | | 7 | 11 | | 8 | 14 | | 9 | 25 | | 10 | 14 | | 11 | 29 | | 12 | 5 | | 13 | 15 | | 14 | 8 | | 15 | 12 | | 16 | 10 | | 17 | 20 | | 18 | 8 | | 19 | 9 | | 20 | 26 | | 21 | 17 | | 22 | 3 | | 23 | 15 | | 24 | 16 | | 25 | 3 | | 26 | 23 | | 27 | 5 | | 28 | 17 | | 29 | 3 | | 30 | 6 | | 31 | 15 | | 32 | 8 | | 33 | 2 | | 34 | 3 | | 35 | 4 | | 36 | 35 | | 37 | 33 | | 38 | 19 | | 39 | 7 | | 40 | 6 | | 41 | 43 | | 42 | 6 | | 43 | 10 | | 44 | 5 | | 45 | 8 | | 46 | 7 | | 47 | 2 | | 48 | 2 | | 49 | 2 |
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| 89.04% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.6301369863013698 | | totalSentences | 73 | | uniqueOpeners | 46 | |
| 72.46% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 46 | | matches | | 0 | "Separately, each detail might explain" |
| | ratio | 0.022 | |
| 63.48% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 18 | | totalSentences | 46 | | matches | | 0 | "His skin held a grey" | | 1 | "She'd seen dead bodies pull" | | 2 | "She reached out, touched it." | | 3 | "Her fingers came away numb," | | 4 | "He didn't move to touch" | | 5 | "He glanced at it the" | | 6 | "She'd stopped bothering to argue" | | 7 | "She followed the frost's edge" | | 8 | "She'd seen that symbol once" | | 9 | "He crouched down, camera raised," | | 10 | "He turned the screen toward" | | 11 | "She reached out and touched" | | 12 | "She didn't believe it, not" | | 13 | "She'd learned that lesson too," | | 14 | "She turned back to the" | | 15 | "He wrote it down, though" | | 16 | "She thought about frost that" | | 17 | "She didn't have a name" |
| | ratio | 0.391 | |
| 46.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 46 | | matches | | 0 | "Rain had turned the alley" | | 1 | "Someone had strung police tape" | | 2 | "DC Reyes crouched by the" | | 3 | "Quinn crouched down across from" | | 4 | "The victim's eyes were open," | | 5 | "His skin held a grey" | | 6 | "She'd seen dead bodies pull" | | 7 | "Quinn looked at the wound" | | 8 | "Reyes shrugged, the practised shrug" | | 9 | "Neither of them had an" | | 10 | "Quinn straightened, joints protesting the" | | 11 | "Brick, damp, ordinary." | | 12 | "She reached out, touched it." | | 13 | "Her fingers came away numb," | | 14 | "He didn't move to touch" | | 15 | "He glanced at it the" | | 16 | "Quinn didn't answer that." | | 17 | "She'd stopped bothering to argue" | | 18 | "She followed the frost's edge" | | 19 | "A symbol scratched into the" |
| | ratio | 0.826 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 46 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 4 | | matches | | 0 | "Except for a faint discolouration near the drainpipe, a ring of frost that had no business existing on a June night, however wet." | | 1 | "She'd stopped bothering to argue with people who needed the world to stay simple; it was easier to let them believe what let them sleep, and focus instead on th…" | | 2 | "She'd learned that lesson too, the hard way, in front of a board that wanted answers she couldn't give without sounding unhinged." | | 3 | "Quinn crouched once more beside the body, staring into those fixed, grey eyes, and thought of a compass she'd bought two years ago from a stall she still couldn…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 27 | | tagDensity | 0.037 | | leniency | 0.074 | | rawRatio | 0 | | effectiveRatio | 0 | |