| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "She crouched again [again]" |
| | dialogueSentences | 41 | | tagDensity | 0.341 | | leniency | 0.683 | | rawRatio | 0.071 | | effectiveRatio | 0.049 | |
| 96.47% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1416 | | totalAiIsmAdverbs | 1 | | 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) | |
| 89.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1416 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "perfect" | | 1 | "etched" | | 2 | "echoing" |
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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 | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 70 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1427 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 843 | | uniqueNames | 10 | | maxNameDensity | 0.95 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Eva" | | discoveredNames | | Harlow | 1 | | Quinn | 8 | | Camden | 1 | | June | 1 | | February | 1 | | Morris | 1 | | Vance | 6 | | Freckles | 1 | | Eva | 5 | | Victorian | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Vance" | | 4 | "Freckles" | | 5 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1427 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 106 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 30.36 | | std | 22.24 | | cv | 0.733 | | sampleLengths | | 0 | 53 | | 1 | 6 | | 2 | 31 | | 3 | 44 | | 4 | 11 | | 5 | 69 | | 6 | 20 | | 7 | 47 | | 8 | 5 | | 9 | 7 | | 10 | 45 | | 11 | 20 | | 12 | 49 | | 13 | 64 | | 14 | 39 | | 15 | 20 | | 16 | 28 | | 17 | 29 | | 18 | 18 | | 19 | 51 | | 20 | 13 | | 21 | 30 | | 22 | 8 | | 23 | 69 | | 24 | 5 | | 25 | 35 | | 26 | 54 | | 27 | 32 | | 28 | 6 | | 29 | 28 | | 30 | 8 | | 31 | 24 | | 32 | 11 | | 33 | 5 | | 34 | 93 | | 35 | 11 | | 36 | 27 | | 37 | 10 | | 38 | 13 | | 39 | 61 | | 40 | 9 | | 41 | 75 | | 42 | 63 | | 43 | 23 | | 44 | 30 | | 45 | 24 | | 46 | 4 |
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| 96.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 79 | | matches | | 0 | "been etched" | | 1 | "been bricked" |
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| 99.75% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 133 | | matches | | 0 | "was photographing" | | 1 | "was already walking" |
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| 35.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 106 | | ratio | 0.038 | | matches | | 0 | "Detective Harlow Quinn counted the steps down the emergency stairwell — forty-two — and walked out of a Camden June into a February nobody had warned her about." | | 1 | "The casing wore its green patina like bark, and sigils had been etched into the face — the same spiral as the chalk marks." | | 2 | "A voice came down the stairwell, echoing off the tiles — a young woman with a leather satchel dragging one shoulder toward the floor, curly red hair escaping its clip, round glasses gone white with fog the moment she reached the cold." | | 3 | "The arch rose out of the tunnel mouth in Victorian brick, generations of soot blackening every joint — except one." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 850 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 12 | | adverbRatio | 0.01411764705882353 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001176470588235294 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 13.46 | | std | 12.05 | | cv | 0.895 | | sampleLengths | | 0 | 25 | | 1 | 28 | | 2 | 6 | | 3 | 16 | | 4 | 15 | | 5 | 6 | | 6 | 27 | | 7 | 11 | | 8 | 11 | | 9 | 69 | | 10 | 5 | | 11 | 7 | | 12 | 8 | | 13 | 6 | | 14 | 41 | | 15 | 5 | | 16 | 7 | | 17 | 7 | | 18 | 15 | | 19 | 9 | | 20 | 2 | | 21 | 2 | | 22 | 10 | | 23 | 5 | | 24 | 15 | | 25 | 20 | | 26 | 29 | | 27 | 3 | | 28 | 35 | | 29 | 26 | | 30 | 6 | | 31 | 5 | | 32 | 28 | | 33 | 20 | | 34 | 10 | | 35 | 12 | | 36 | 6 | | 37 | 25 | | 38 | 4 | | 39 | 18 | | 40 | 4 | | 41 | 24 | | 42 | 23 | | 43 | 8 | | 44 | 5 | | 45 | 13 | | 46 | 9 | | 47 | 8 | | 48 | 4 | | 49 | 4 |
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| 69.50% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.46226415094339623 | | totalSentences | 106 | | uniqueOpeners | 49 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 84.79% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 71 | | matches | | 0 | "Her breath fogged at the" | | 1 | "She pressed her thumb against" | | 2 | "His right fist was closed" | | 3 | "It lay over the platform" | | 4 | "She stood and levelled the" | | 5 | "He gestured at the crates" | | 6 | "She leaned over the body" | | 7 | "His watch had stopped at" | | 8 | "She checked her own watch" | | 9 | "She turned the compass in" | | 10 | "She set it flat on" | | 11 | "She crouched again and pulled" | | 12 | "His fingertips wore the same" | | 13 | "She followed the drag furrows." | | 14 | "She cleaned the lenses on" | | 15 | "She spotted the crates and" | | 16 | "She picked it up with" | | 17 | "She freed a hand from" | | 18 | "She held it level" | | 19 | "She stripped a glove and" |
| | ratio | 0.338 | |
| 2.25% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 71 | | matches | | 0 | "The chain on the service" | | 1 | "Detective Harlow Quinn counted the" | | 2 | "Her breath fogged at the" | | 3 | "The last time that had" | | 4 | "She pressed her thumb against" | | 5 | "Tripod lamps burned along the" | | 6 | "DS Vance lifted the tape" | | 7 | "Quinn crouched beside the body." | | 8 | "His right fist was closed" | | 9 | "The pathologist knelt on his" | | 10 | "Quinn swept her torch across" | | 11 | "It lay over the platform" | | 12 | "She stood and levelled the" | | 13 | "Vance's jaw worked." | | 14 | "He gestured at the crates" | | 15 | "Quinn crossed to the track" | | 16 | "Frost feathered the third rail." | | 17 | "Ice beaded the sleepers in" | | 18 | "The platform clock hung above" | | 19 | "She leaned over the body" |
| | ratio | 0.915 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Vance insisted (insist)" |
| | dialogueSentences | 41 | | tagDensity | 0.049 | | leniency | 0.098 | | rawRatio | 0.5 | | effectiveRatio | 0.049 | |