| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 18 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.10% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1282 | | 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) | |
| 61.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1282 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "structure" | | 1 | "measured" | | 2 | "tinged" | | 3 | "gloom" | | 4 | "weight" | | 5 | "crystal" | | 6 | "shattered" | | 7 | "shimmered" | | 8 | "standard" | | 9 | "echoed" |
| |
| 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 | 92 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 92 | | filterMatches | | | hedgeMatches | (empty) | |
| 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 | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1281 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 75.09% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 1068 | | uniqueNames | 11 | | maxNameDensity | 1.5 | | worstName | "Harlow" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Harlow" | | discoveredNames | | Harlow | 16 | | Camden | 1 | | Herrera | 12 | | Met | 1 | | Saint | 1 | | Christopher | 1 | | London | 2 | | Underground | 1 | | Northern | 1 | | Line | 1 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Camden" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" |
| | places | | | globalScore | 0.751 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | 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 | 1281 | | 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 | 52 | | mean | 24.63 | | std | 13.74 | | cv | 0.558 | | sampleLengths | | 0 | 40 | | 1 | 2 | | 2 | 49 | | 3 | 2 | | 4 | 41 | | 5 | 25 | | 6 | 25 | | 7 | 46 | | 8 | 34 | | 9 | 34 | | 10 | 42 | | 11 | 25 | | 12 | 7 | | 13 | 21 | | 14 | 15 | | 15 | 22 | | 16 | 18 | | 17 | 56 | | 18 | 16 | | 19 | 12 | | 20 | 26 | | 21 | 41 | | 22 | 9 | | 23 | 44 | | 24 | 9 | | 25 | 25 | | 26 | 14 | | 27 | 8 | | 28 | 47 | | 29 | 21 | | 30 | 24 | | 31 | 26 | | 32 | 41 | | 33 | 10 | | 34 | 17 | | 35 | 31 | | 36 | 7 | | 37 | 19 | | 38 | 26 | | 39 | 23 | | 40 | 12 | | 41 | 18 | | 42 | 14 | | 43 | 25 | | 44 | 11 | | 45 | 20 | | 46 | 46 | | 47 | 9 | | 48 | 43 | | 49 | 46 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 92 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 184 | | matches | (empty) | |
| 87.91% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 104 | | ratio | 0.019 | | matches | | 0 | "The heavy padlock didn't click open; it dissolved into a swirl of grey ash." | | 1 | "Morris's lifeless face flashed in her mind—the bloodless skin, the shattered service weapon, the closed investigation file stamped *Unexplained*." |
| |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1081 | | adjectiveStacks | 2 | | stackExamples | | 0 | "clean, military-precise hurtle." | | 1 | "thick, violet-tinged gloom." |
| | adverbCount | 17 | | adverbRatio | 0.01572617946345976 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0018501387604070306 | |
| 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 | 12.32 | | std | 6.57 | | cv | 0.533 | | sampleLengths | | 0 | 6 | | 1 | 21 | | 2 | 13 | | 3 | 2 | | 4 | 12 | | 5 | 15 | | 6 | 22 | | 7 | 2 | | 8 | 4 | | 9 | 14 | | 10 | 23 | | 11 | 9 | | 12 | 16 | | 13 | 25 | | 14 | 8 | | 15 | 5 | | 16 | 16 | | 17 | 6 | | 18 | 11 | | 19 | 15 | | 20 | 19 | | 21 | 13 | | 22 | 21 | | 23 | 6 | | 24 | 13 | | 25 | 23 | | 26 | 10 | | 27 | 6 | | 28 | 9 | | 29 | 7 | | 30 | 3 | | 31 | 18 | | 32 | 15 | | 33 | 22 | | 34 | 18 | | 35 | 13 | | 36 | 43 | | 37 | 3 | | 38 | 13 | | 39 | 12 | | 40 | 12 | | 41 | 14 | | 42 | 7 | | 43 | 3 | | 44 | 14 | | 45 | 17 | | 46 | 9 | | 47 | 11 | | 48 | 28 | | 49 | 5 |
| |
| 62.18% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.41346153846153844 | | totalSentences | 104 | | uniqueOpeners | 43 | |
| 74.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 89 | | matches | | 0 | "Just slick cobblestones, overflowing gutters," | | 1 | "Instead, a jolt of static" |
| | ratio | 0.022 | |
| 98.65% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 89 | | matches | | 0 | "She vaulted a toppled wheelie" | | 1 | "She wiped water from her" | | 2 | "He vaulted a low iron" | | 3 | "She landed on the balls" | | 4 | "She cursed, releasing the button." | | 5 | "He threw a frantic look" | | 6 | "He tugged at the heavy" | | 7 | "She kept her baton angled" | | 8 | "He pressed his back against" | | 9 | "His fingers slipped from the" | | 10 | "He jammed it into a" | | 11 | "He extended a gloved palm." | | 12 | "She reached the threshold just" | | 13 | "She threw her weight against" | | 14 | "Her fingers tingled, numb to" | | 15 | "Her breath plumed in the" | | 16 | "She dropped her gaze to" | | 17 | "It must have fallen from" | | 18 | "She crouched and picked it" | | 19 | "Her radio crackled to life," |
| | ratio | 0.303 | |
| 44.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 89 | | matches | | 0 | "She vaulted a toppled wheelie" | | 1 | "Harlow lengthened her stride, her" | | 2 | "She wiped water from her" | | 3 | "Herrera didn't look back." | | 4 | "He vaulted a low iron" | | 5 | "The collar of his jacket" | | 6 | "Harlow took the railing in" | | 7 | "She landed on the balls" | | 8 | "Static hissed from the receiver," | | 9 | "She cursed, releasing the button." | | 10 | "A glance at the worn" | | 11 | "Herrera cut left into a" | | 12 | "Harlow rounded the corner two" | | 13 | "The alley ended at a" | | 14 | "Herrera slammed against the iron" | | 15 | "He threw a frantic look" | | 16 | "He tugged at the heavy" | | 17 | "Harlow slowed to a deliberate" | | 18 | "Rain dripped from her sharp" | | 19 | "She kept her baton angled" |
| | ratio | 0.831 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 92.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 4 | | matches | | 0 | "She vaulted a toppled wheelie bin, her boots splashing through an oil-slicked puddle that reflected the amber glow of Camden’s streetlights." | | 1 | "Herrera cut left into a narrow cul-de-sac that reeked of rotting cabbage and wet soot." | | 2 | "A heavy wool coat hid the doorman's frame, and a wide-brimmed hat shadowed his face, save for a pair of eyes that reflected the streetlamp like a cat's." | | 3 | "Across the tracks, an apothecary weighed violet powder on brass scales, surrounded by jars of preserved organs that twitched in their brine." |
| |
| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "the doorman rasped, his voice grinding like gravel under a tyre" |
| |
| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "the giant growled (growl)" |
| | dialogueSentences | 18 | | tagDensity | 0.056 | | leniency | 0.111 | | rawRatio | 1 | | effectiveRatio | 0.111 | |