| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | 0 | "She crouched again [again]" |
| | dialogueSentences | 43 | | tagDensity | 0.372 | | leniency | 0.744 | | rawRatio | 0.063 | | effectiveRatio | 0.047 | |
| 90.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1037 | | 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) | |
| 80.71% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1037 | | totalAiIsms | 4 | | 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 | 84 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 84 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | 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 | 1037 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 760 | | uniqueNames | 6 | | maxNameDensity | 1.58 | | worstName | "Pell" | | maxWindowNameDensity | 3 | | worstWindowName | "Pell" | | discoveredNames | | Tube | 1 | | Pell | 12 | | Quinn | 10 | | Male | 1 | | Deptford | 1 | | Morris | 3 |
| | persons | | | places | | | globalScore | 0.711 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.964 | | wordCount | 1037 | | matches | | 0 | "not the ordinary cold of underground, but something with weight to it, something" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 22.54 | | std | 19.9 | | cv | 0.883 | | sampleLengths | | 0 | 17 | | 1 | 56 | | 2 | 20 | | 3 | 3 | | 4 | 24 | | 5 | 6 | | 6 | 43 | | 7 | 19 | | 8 | 3 | | 9 | 12 | | 10 | 5 | | 11 | 54 | | 12 | 8 | | 13 | 5 | | 14 | 69 | | 15 | 15 | | 16 | 30 | | 17 | 2 | | 18 | 50 | | 19 | 1 | | 20 | 16 | | 21 | 52 | | 22 | 5 | | 23 | 8 | | 24 | 6 | | 25 | 49 | | 26 | 21 | | 27 | 62 | | 28 | 16 | | 29 | 71 | | 30 | 5 | | 31 | 1 | | 32 | 31 | | 33 | 8 | | 34 | 5 | | 35 | 20 | | 36 | 14 | | 37 | 5 | | 38 | 22 | | 39 | 46 | | 40 | 24 | | 41 | 3 | | 42 | 46 | | 43 | 25 | | 44 | 10 | | 45 | 24 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 84 | | matches | | |
| 92.47% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 124 | | matches | | 0 | "wasn't spreading" | | 1 | "was burning" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 110 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 345 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 10 | | adverbRatio | 0.028985507246376812 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.005797101449275362 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 9.43 | | std | 6.46 | | cv | 0.686 | | sampleLengths | | 0 | 17 | | 1 | 7 | | 2 | 22 | | 3 | 27 | | 4 | 14 | | 5 | 6 | | 6 | 3 | | 7 | 16 | | 8 | 8 | | 9 | 6 | | 10 | 1 | | 11 | 1 | | 12 | 7 | | 13 | 17 | | 14 | 17 | | 15 | 7 | | 16 | 12 | | 17 | 3 | | 18 | 5 | | 19 | 7 | | 20 | 5 | | 21 | 13 | | 22 | 8 | | 23 | 4 | | 24 | 2 | | 25 | 16 | | 26 | 11 | | 27 | 8 | | 28 | 5 | | 29 | 7 | | 30 | 6 | | 31 | 3 | | 32 | 2 | | 33 | 3 | | 34 | 9 | | 35 | 14 | | 36 | 25 | | 37 | 6 | | 38 | 9 | | 39 | 17 | | 40 | 13 | | 41 | 2 | | 42 | 15 | | 43 | 12 | | 44 | 8 | | 45 | 15 | | 46 | 1 | | 47 | 12 | | 48 | 4 | | 49 | 5 |
| |
| 80.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.5181818181818182 | | totalSentences | 110 | | uniqueOpeners | 57 | |
| 92.59% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 72 | | matches | | 0 | "Just the man, laid out" | | 1 | "Somewhere above, in the black," |
| | ratio | 0.028 | |
| 97.78% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 72 | | matches | | 0 | "He stood, knees popping" | | 1 | "His hat sat upright six" | | 2 | "She studied the angle of" | | 3 | "He led her along the" | | 4 | "Her torch found the service" | | 5 | "She'd felt it once before." | | 6 | "She pushed the memory down." | | 7 | "She crouched again, gentler now," | | 8 | "She'd been wrong to call" | | 9 | "It wasn't spreading outward the" | | 10 | "It had been poured, ringing" | | 11 | "She'd seen a circle like" | | 12 | "Her hand went to her" | | 13 | "She'd never told anyone she" | | 14 | "She'd taken it from Morris's" | | 15 | "It was the only thing" | | 16 | "She drew the compass into" | | 17 | "It pointed dead at the" | | 18 | "She palmed the compass away" | | 19 | "She fixed him with a" |
| | ratio | 0.306 | |
| 50.28% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 72 | | matches | | 0 | "The body lay at the" | | 1 | "Quinn ducked under the tape" | | 2 | "The old Tube station breathed" | | 3 | "A single forensic lamp threw" | | 4 | "Sergeant Pell crouched near the" | | 5 | "He stood, knees popping" | | 6 | "Quinn crouched beside the body" | | 7 | "Wool coat, good quality, no" | | 8 | "His hat sat upright six" | | 9 | "She studied the angle of" | | 10 | "Pell went on" | | 11 | "Pell laughed, then caught himself." | | 12 | "The man wore brogues, polished" | | 13 | "Quinn ran the lamp's beam" | | 14 | "A man who'd pitched headlong" | | 15 | "These shoes looked as though" | | 16 | "The dust on the platform" | | 17 | "Pell's own boots." | | 18 | "Pell shook his head" | | 19 | "He led her along the" |
| | ratio | 0.819 | |
| 69.44% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 72 | | matches | | 0 | "As if the blood marked" |
| | ratio | 0.014 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 1 | | matches | | 0 | "The cold pressed in, not the ordinary cold of underground, but something with weight to it, something that sat on the back of her neck like a hand." |
| |
| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "He stood, knees popping" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 43 | | tagDensity | 0.093 | | leniency | 0.186 | | rawRatio | 0.25 | | effectiveRatio | 0.047 | |