| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.462 | | leniency | 0.923 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1015 | | 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) | |
| 85.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1015 | | totalAiIsms | 3 | | 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 | 98 | | matches | (empty) | |
| 99.13% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 98 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 104 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1015 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 22 | | wordCount | 914 | | uniqueNames | 14 | | maxNameDensity | 0.66 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Greek | 1 | | Charlotte | 1 | | Street | 1 | | Tube | 2 | | Blitz | 1 | | Morris | 2 | | Camden | 2 | | Veil | 1 | | Market | 1 | | Patient | 1 | | Quinn | 6 |
| | persons | | 0 | "Morris" | | 1 | "Market" | | 2 | "Patient" | | 3 | "Quinn" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Charlotte" | | 3 | "Street" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | 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 | 1015 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 104 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 24.76 | | std | 19.82 | | cv | 0.801 | | sampleLengths | | 0 | 19 | | 1 | 56 | | 2 | 2 | | 3 | 22 | | 4 | 46 | | 5 | 27 | | 6 | 58 | | 7 | 3 | | 8 | 10 | | 9 | 13 | | 10 | 62 | | 11 | 6 | | 12 | 45 | | 13 | 17 | | 14 | 20 | | 15 | 8 | | 16 | 33 | | 17 | 37 | | 18 | 30 | | 19 | 3 | | 20 | 45 | | 21 | 9 | | 22 | 83 | | 23 | 3 | | 24 | 34 | | 25 | 29 | | 26 | 1 | | 27 | 15 | | 28 | 16 | | 29 | 27 | | 30 | 19 | | 31 | 7 | | 32 | 64 | | 33 | 12 | | 34 | 24 | | 35 | 12 | | 36 | 17 | | 37 | 50 | | 38 | 16 | | 39 | 6 | | 40 | 9 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 98 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 160 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 104 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 143 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 1 | | adverbRatio | 0.006993006993006993 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 104 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 104 | | mean | 9.76 | | std | 7.91 | | cv | 0.811 | | sampleLengths | | 0 | 19 | | 1 | 13 | | 2 | 13 | | 3 | 30 | | 4 | 2 | | 5 | 3 | | 6 | 3 | | 7 | 16 | | 8 | 6 | | 9 | 19 | | 10 | 4 | | 11 | 1 | | 12 | 8 | | 13 | 8 | | 14 | 3 | | 15 | 9 | | 16 | 15 | | 17 | 7 | | 18 | 26 | | 19 | 6 | | 20 | 19 | | 21 | 3 | | 22 | 10 | | 23 | 5 | | 24 | 8 | | 25 | 5 | | 26 | 5 | | 27 | 25 | | 28 | 27 | | 29 | 6 | | 30 | 8 | | 31 | 11 | | 32 | 3 | | 33 | 23 | | 34 | 6 | | 35 | 11 | | 36 | 12 | | 37 | 5 | | 38 | 1 | | 39 | 1 | | 40 | 1 | | 41 | 5 | | 42 | 3 | | 43 | 3 | | 44 | 23 | | 45 | 3 | | 46 | 4 | | 47 | 23 | | 48 | 4 | | 49 | 10 |
| |
| 81.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5096153846153846 | | totalSentences | 104 | | uniqueOpeners | 53 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 86 | | matches | | 0 | "Just dropped, like the earth" | | 1 | "Then a hundred colours." | | 2 | "Then he was gone, swallowed" |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 86 | | matches | | 0 | "She caught flashes of his" | | 1 | "He hooked left into an" | | 2 | "She followed, lungs burning, her" | | 3 | "He was fast." | | 4 | "She'd been watching him for" | | 5 | "She'd seen it in the" | | 6 | "He glanced now." | | 7 | "she muttered, more to herself" | | 8 | "He cut right, then dropped." | | 9 | "She edged to the lip" | | 10 | "Her radio crackled against her" | | 11 | "She thumbed it down without" | | 12 | "She'd waited at the top." | | 13 | "She never saw him again." | | 14 | "She drew her torch, clicked" | | 15 | "She went down." | | 16 | "She'd heard the name twice" | | 17 | "He glanced back." | | 18 | "She thought of Morris." | | 19 | "she said, surprising herself" |
| | ratio | 0.244 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 60 | | totalSentences | 86 | | matches | | 0 | "The kid had thirty feet" | | 1 | "Quinn pushed harder, boots slapping" | | 2 | "The Soho crowds parted and" | | 3 | "She caught flashes of his" | | 4 | "A useless shout." | | 5 | "Nobody ever stopped." | | 6 | "He hooked left into an" | | 7 | "She followed, lungs burning, her" | | 8 | "The walls closed in." | | 9 | "Puddles slick with chip grease" | | 10 | "A cat shrieked and vanished" | | 11 | "He was fast." | | 12 | "She'd been watching him for" | | 13 | "The clique used him to" | | 14 | "Whatever sat in that satchel" | | 15 | "She'd seen it in the" | | 16 | "He glanced now." | | 17 | "she muttered, more to herself" | | 18 | "He cut right, then dropped." | | 19 | "Quinn skidded to a halt." |
| | ratio | 0.698 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 96.77% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 2 | | matches | | 0 | "The kind of forgotten staircase that led to a sealed Tube entrance, the sort the city had a hundred of, bricked over and rotting since the Blitz." | | 1 | "But under it, something sweet and rotten and electric, like ozone after lightning, like a butcher's shop that sold things with no names." |
| |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "she muttered, more to herself than him" |
| |
| 73.08% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 13 | | tagDensity | 0.308 | | leniency | 0.615 | | rawRatio | 0.25 | | effectiveRatio | 0.154 | |