| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.387 | | leniency | 0.774 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 950 | | 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) | |
| 78.95% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 950 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "chill" | | 1 | "stomach" | | 2 | "etched" | | 3 | "quivered" |
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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 | 48 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 48 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 950 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.85% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 665 | | uniqueNames | 8 | | maxNameDensity | 1.2 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Town | 1 | | Quinn | 8 | | Tom | 1 | | Hadley | 7 | | Hackney | 1 | | Dan | 1 | | Morris | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Tom" | | 2 | "Hadley" | | 3 | "Dan" | | 4 | "Morris" |
| | places | | 0 | "Camden" | | 1 | "Town" | | 2 | "Hackney" |
| | globalScore | 0.898 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 36 | | 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 | 950 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 32.76 | | std | 28.99 | | cv | 0.885 | | sampleLengths | | 0 | 71 | | 1 | 50 | | 2 | 3 | | 3 | 20 | | 4 | 74 | | 5 | 45 | | 6 | 3 | | 7 | 40 | | 8 | 42 | | 9 | 1 | | 10 | 1 | | 11 | 4 | | 12 | 27 | | 13 | 29 | | 14 | 3 | | 15 | 17 | | 16 | 61 | | 17 | 10 | | 18 | 8 | | 19 | 11 | | 20 | 64 | | 21 | 76 | | 22 | 7 | | 23 | 42 | | 24 | 26 | | 25 | 113 | | 26 | 13 | | 27 | 72 | | 28 | 17 |
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| 54.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 48 | | matches | | 0 | "been wrenched" | | 1 | "been closed" | | 2 | "been turned" | | 3 | "been scorched" | | 4 | "was etched" | | 5 | "been bricked" | | 6 | "been written" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 108 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 667 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 22 | | adverbRatio | 0.03298350824587706 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004497751124437781 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 14.18 | | std | 10.37 | | cv | 0.731 | | sampleLengths | | 0 | 20 | | 1 | 26 | | 2 | 25 | | 3 | 20 | | 4 | 14 | | 5 | 16 | | 6 | 3 | | 7 | 14 | | 8 | 6 | | 9 | 23 | | 10 | 13 | | 11 | 14 | | 12 | 24 | | 13 | 13 | | 14 | 14 | | 15 | 18 | | 16 | 3 | | 17 | 18 | | 18 | 22 | | 19 | 4 | | 20 | 14 | | 21 | 19 | | 22 | 5 | | 23 | 1 | | 24 | 1 | | 25 | 4 | | 26 | 8 | | 27 | 19 | | 28 | 6 | | 29 | 23 | | 30 | 3 | | 31 | 14 | | 32 | 3 | | 33 | 4 | | 34 | 16 | | 35 | 4 | | 36 | 22 | | 37 | 15 | | 38 | 3 | | 39 | 7 | | 40 | 8 | | 41 | 9 | | 42 | 2 | | 43 | 26 | | 44 | 7 | | 45 | 21 | | 46 | 10 | | 47 | 2 | | 48 | 21 | | 49 | 24 |
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| 79.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.5373134328358209 | | totalSentences | 67 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 83.64% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 44 | | matches | | 0 | "He was twenty-nine and kept" | | 1 | "He waved his pen down" | | 2 | "His face had been turned" | | 3 | "She stood at the correct" | | 4 | "She tilted her head toward" | | 5 | "It was not soot." | | 6 | "He opened his mouth, shut" | | 7 | "She looked at the man's" | | 8 | "She eased it free with" | | 9 | "She held it flat on" | | 10 | "It did not drift back." | | 11 | "It stayed fixed on the" | | 12 | "She pushed the memory aside" | | 13 | "She stopped in front of" | | 14 | "It was warm." |
| | ratio | 0.341 | |
| 5.45% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 44 | | matches | | 0 | "The Camden Town platform smelled" | | 1 | "Harlow Quinn stopped at the" | | 2 | "Someone had strung blue tape" | | 3 | "DC Tom Hadley came down" | | 4 | "He was twenty-nine and kept" | | 5 | "He waved his pen down" | | 6 | "Quinn followed him past the" | | 7 | "The station had been closed" | | 8 | "Someone had kept it clean" | | 9 | "The body lay on the" | | 10 | "A man in his fifties," | | 11 | "His face had been turned" | | 12 | "Hadley crouched beside the body" | | 13 | "Quinn did not crouch." | | 14 | "She stood at the correct" | | 15 | "The water pooled in dips" | | 16 | "The man's shoes were dry." | | 17 | "Hadley leaned in, then straightened" | | 18 | "Quinn moved along the platform" | | 19 | "She tilted her head toward" |
| | ratio | 0.909 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 44 | | matches | | 0 | "Now the walls were bare," |
| | ratio | 0.023 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 1 | | matches | | 0 | "A thin line of dried residue marked the back of the casing, pale and flaky, the same colour as the bone dust she'd seen once in a crime scene three years ago, i…" |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 2 | | matches | | 0 | "DC Tom Hadley came, his notebook already open" | | 1 | "Hadley said, the way a man tests ice" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0 | | effectiveRatio | 0 | |