| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 41 | | tagDensity | 0.488 | | leniency | 0.976 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.11% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1452 | | 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) | |
| 65.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1452 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "silence" | | 1 | "gloom" | | 2 | "pulse" | | 3 | "scanned" | | 4 | "etched" | | 5 | "standard" | | 6 | "familiar" | | 7 | "warmth" | | 8 | "could feel" | | 9 | "implication" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 131 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1450 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 85.01% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 40 | | wordCount | 1154 | | uniqueNames | 11 | | maxNameDensity | 1.3 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 15 | | Tube | 1 | | Camden | 2 | | Detective | 2 | | Constable | 1 | | Reynolds | 11 | | Metropolitan | 1 | | Police | 1 | | Morris | 4 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Constable" | | 3 | "Reynolds" | | 4 | "Morris" | | 5 | "Market" |
| | places | (empty) | | globalScore | 0.85 | | windowScore | 1 | |
| 85.06% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 77 | | glossingSentenceCount | 2 | | matches | | 0 | "looked like they belonged to a different" | | 1 | "felt like it was pointing at her" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.69 | | wordCount | 1450 | | matches | | 0 | "Not the ambient warmth of the station, but a living heat, like skin" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 131 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 32.95 | | std | 22.81 | | cv | 0.692 | | sampleLengths | | 0 | 76 | | 1 | 44 | | 2 | 11 | | 3 | 53 | | 4 | 23 | | 5 | 40 | | 6 | 27 | | 7 | 49 | | 8 | 3 | | 9 | 16 | | 10 | 50 | | 11 | 64 | | 12 | 10 | | 13 | 9 | | 14 | 62 | | 15 | 41 | | 16 | 22 | | 17 | 21 | | 18 | 73 | | 19 | 13 | | 20 | 13 | | 21 | 34 | | 22 | 59 | | 23 | 10 | | 24 | 3 | | 25 | 31 | | 26 | 10 | | 27 | 44 | | 28 | 41 | | 29 | 82 | | 30 | 9 | | 31 | 29 | | 32 | 8 | | 33 | 13 | | 34 | 57 | | 35 | 65 | | 36 | 16 | | 37 | 9 | | 38 | 21 | | 39 | 15 | | 40 | 35 | | 41 | 14 | | 42 | 80 | | 43 | 45 |
| |
| 92.50% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 110 | | matches | | 0 | "was littered" | | 1 | "was etched" | | 2 | "been ruled" | | 3 | "were supposed" |
| |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 7 | | totalVerbs | 191 | | matches | | 0 | "wasn't pointing" | | 1 | "was spinning" | | 2 | "was pointing" | | 3 | "was pointing" | | 4 | "was still pointing" | | 5 | "wasn't just solving" | | 6 | "was closing" |
| |
| 77.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 3 | | totalSentences | 131 | | ratio | 0.023 | | matches | | 0 | "It wasn't the quiet of an empty space; it was the held breath of something waiting." | | 1 | "The platform was littered with debris—old tickets, rusted metal, but something else caught her eye." | | 2 | "It was spinning slowly, erratically, before locking onto a specific direction—straight down into the tunnel wall." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1159 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 34 | | adverbRatio | 0.029335634167385678 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008628127696289905 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 131 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 131 | | mean | 11.07 | | std | 6.4 | | cv | 0.578 | | sampleLengths | | 0 | 21 | | 1 | 18 | | 2 | 21 | | 3 | 16 | | 4 | 20 | | 5 | 24 | | 6 | 11 | | 7 | 17 | | 8 | 20 | | 9 | 16 | | 10 | 7 | | 11 | 16 | | 12 | 18 | | 13 | 11 | | 14 | 4 | | 15 | 2 | | 16 | 5 | | 17 | 11 | | 18 | 16 | | 19 | 9 | | 20 | 14 | | 21 | 7 | | 22 | 11 | | 23 | 7 | | 24 | 1 | | 25 | 3 | | 26 | 6 | | 27 | 10 | | 28 | 11 | | 29 | 4 | | 30 | 15 | | 31 | 13 | | 32 | 7 | | 33 | 8 | | 34 | 16 | | 35 | 4 | | 36 | 15 | | 37 | 5 | | 38 | 16 | | 39 | 10 | | 40 | 6 | | 41 | 3 | | 42 | 10 | | 43 | 23 | | 44 | 17 | | 45 | 7 | | 46 | 5 | | 47 | 7 | | 48 | 34 | | 49 | 12 |
| |
| 46.82% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.33587786259541985 | | totalSentences | 131 | | uniqueOpeners | 44 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 33.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 105 | | matches | | 0 | "It wasn't the quiet of" | | 1 | "She adjusted the collar of" | | 2 | "He looked too young for" | | 3 | "She didn't wait for an" | | 4 | "He lay on his back," | | 5 | "She pulled on latex gloves," | | 6 | "She leaned close to the" | | 7 | "She checked the pulse, then" | | 8 | "She scanned the area." | | 9 | "It glinted dully under the" | | 10 | "She picked it up with" | | 11 | "It was a compass, small" | | 12 | "She turned it over." | | 13 | "It was spinning slowly, erratically," | | 14 | "She felt that familiar prickle" | | 15 | "He patted the pockets, shaking" | | 16 | "It was pointing directly at" | | 17 | "She walked toward it, her" | | 18 | "She ran her hand along" | | 19 | "It was warm." |
| | ratio | 0.467 | |
| 21.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 92 | | totalSentences | 105 | | matches | | 0 | "The air down here tasted" | | 1 | "Detective Harlow Quinn stepped over" | | 2 | "The abandoned Tube station beneath" | | 3 | "It wasn't the quiet of" | | 4 | "She adjusted the collar of" | | 5 | "a voice called from the" | | 6 | "Detective Constable Reynolds stepped into" | | 7 | "He looked too young for" | | 8 | "Quinn asked, her voice low" | | 9 | "She didn't wait for an" | | 10 | "The victim was a man," | | 11 | "He lay on his back," | | 12 | "Reynolds said, lowering his voice" | | 13 | "Quinn knelt, her knees popping" | | 14 | "She pulled on latex gloves," | | 15 | "She leaned close to the" | | 16 | "The skin was pale, almost" | | 17 | "She checked the pulse, then" | | 18 | "Quinn stood, her sharp jaw" | | 19 | "She scanned the area." |
| | ratio | 0.876 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 105 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 5 | | matches | | 0 | "The air down here tasted of wet concrete and old electricity, a metallic tang that coated the back of the throat." | | 1 | "The victim was a man, mid-forties, dressed in clothes that looked like they belonged to a different decade." | | 2 | "The face was etched with protective sigils, geometric patterns that didn't match any standard cartography." | | 3 | "She could feel a hum vibrating through the soles of her boots, a low frequency that rattled her teeth." | | 4 | "Reynolds was still there, standing guard over a crime scene that wasn't a crime scene at all." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 5 | | matches | | 0 | "Quinn asked, her voice low" | | 1 | "Quinn said, her tone flat" | | 2 | "she countered, turning to face him" | | 3 | "Reynolds argued, his voice rising" | | 4 | "she said, her voice steady despite the adrenaline flooding her veins" |
| |
| 76.83% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 3 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "Reynolds argued (argue)" | | 2 | "Quinn interrupted (interrupt)" |
| | dialogueSentences | 41 | | tagDensity | 0.39 | | leniency | 0.78 | | rawRatio | 0.188 | | effectiveRatio | 0.146 | |