| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 81.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1092 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "deliberately" | | count | 1 |
| | 2 | | | 3 | |
| | highlights | | 0 | "slightly" | | 1 | "deliberately" | | 2 | "slowly" | | 3 | "suddenly" |
| |
| 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) | |
| 63.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1092 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "weight" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "flickered" | | 4 | "electric" | | 5 | "familiar" | | 6 | "could feel" |
| |
| 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 | 87 | | matches | (empty) | |
| 93.60% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 88 | | 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 | 1082 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 94.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 1074 | | uniqueNames | 14 | | maxNameDensity | 1.12 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Morris" | | discoveredNames | | Harlow | 12 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Tomás | 1 | | Herrera | 8 | | Saint | 1 | | Christopher | 1 | | Eighteen | 1 | | Morris | 6 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Tomás" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Morris" | | 6 | "Raven" |
| | places | | 0 | "Chalk" | | 1 | "Farm" | | 2 | "Road" | | 3 | "Soho" |
| | globalScore | 0.941 | | windowScore | 1 | |
| 81.51% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 2 | | matches | | 0 | "quite fit" | | 1 | "quite explain" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.924 | | wordCount | 1082 | | matches | | 0 | "not electric, but the warm yellow of flames" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 88 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 45.08 | | std | 27.36 | | cv | 0.607 | | sampleLengths | | 0 | 46 | | 1 | 30 | | 2 | 84 | | 3 | 6 | | 4 | 92 | | 5 | 73 | | 6 | 77 | | 7 | 24 | | 8 | 62 | | 9 | 54 | | 10 | 68 | | 11 | 9 | | 12 | 50 | | 13 | 55 | | 14 | 17 | | 15 | 100 | | 16 | 13 | | 17 | 38 | | 18 | 10 | | 19 | 60 | | 20 | 35 | | 21 | 14 | | 22 | 43 | | 23 | 22 |
| |
| 97.20% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 87 | | matches | | 0 | "been trained" | | 1 | "was mapped" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 188 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 88 | | ratio | 0.08 | | matches | | 0 | "This was the third time this month she'd spotted someone from that damned clique—the group she'd been investigating since finding their symbol at DS Morris's death scene three years ago." | | 1 | "The gap was wider than it looked—for a moment she was airborne, rain in her face, the street four stories below—then her boots hit concrete and she rolled forward, coming up running." | | 2 | "The stairs ended in a basement that smelled of mildew and something else—something sharp and mineral, like blood and copper and stone." | | 3 | "How could she explain that she'd been obsessing over this case for three years, that she dreamed of Morris's body in that warehouse, that she knew—knew—something impossible had killed him?" | | 4 | "Light flickered—not electric, but the warm yellow of flames." | | 5 | "Yet here it was: a platform stretching into shadows, lined with stalls and vendors and people—so many people, all of them wrong in ways she couldn't quite articulate." | | 6 | "He pulled something from his pocket—something pale that caught the light—and pressed it into the palm of a vendor at the entrance." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1087 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.019319227230910764 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.007359705611775529 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 88 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 88 | | mean | 12.3 | | std | 7.36 | | cv | 0.599 | | sampleLengths | | 0 | 26 | | 1 | 20 | | 2 | 11 | | 3 | 19 | | 4 | 3 | | 5 | 18 | | 6 | 17 | | 7 | 16 | | 8 | 30 | | 9 | 6 | | 10 | 11 | | 11 | 12 | | 12 | 17 | | 13 | 17 | | 14 | 13 | | 15 | 6 | | 16 | 8 | | 17 | 8 | | 18 | 27 | | 19 | 10 | | 20 | 18 | | 21 | 9 | | 22 | 9 | | 23 | 15 | | 24 | 9 | | 25 | 13 | | 26 | 8 | | 27 | 32 | | 28 | 19 | | 29 | 5 | | 30 | 16 | | 31 | 12 | | 32 | 14 | | 33 | 6 | | 34 | 3 | | 35 | 1 | | 36 | 1 | | 37 | 9 | | 38 | 22 | | 39 | 10 | | 40 | 22 | | 41 | 7 | | 42 | 5 | | 43 | 3 | | 44 | 8 | | 45 | 7 | | 46 | 8 | | 47 | 30 | | 48 | 2 | | 49 | 7 |
| |
| 54.55% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4090909090909091 | | totalSentences | 88 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 84 | | matches | | 0 | "Her voice cut through the" | | 1 | "He veered left into an" | | 2 | "Her brown eyes tracked every" | | 3 | "She'd been watching The Raven's" | | 4 | "He jumped across a gap" | | 5 | "She followed without hesitation, her" | | 6 | "She was close enough now" | | 7 | "He shook his head, water" | | 8 | "She pulled her torch from" | | 9 | "Her breathing echoed off concrete" | | 10 | "She should call for backup." | | 11 | "Her watch felt heavy on" | | 12 | "He pulled something from his" | | 13 | "She could retreat now, go" | | 14 | "Her partner's face flashed through" | | 15 | "She kept her shoulders square," |
| | ratio | 0.19 | |
| 67.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 84 | | matches | | 0 | "The rain hammered down on" | | 1 | "Her voice cut through the" | | 2 | "Herrera didn't stop." | | 3 | "He veered left into an" | | 4 | "Harlow pushed harder, her worn" | | 5 | "The military precision of her" | | 6 | "This was the third time" | | 7 | "The symbol she still didn't" | | 8 | "The alley narrowed, forcing her" | | 9 | "The smell of rotting food" | | 10 | "Harlow grabbed the ladder and" | | 11 | "Her brown eyes tracked every" | | 12 | "The scar on his left" | | 13 | "The way he favored his" | | 14 | "The medical kit bag bouncing" | | 15 | "She'd been watching The Raven's" | | 16 | "People who whispered in corners" | | 17 | "People like Herrera, the former" | | 18 | "The file hadn't specified what" | | 19 | "Harlow reached the rooftop as" |
| | ratio | 0.786 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 84 | | matches | (empty) | | ratio | 0 | |
| 83.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 4 | | matches | | 0 | "The rain hammered down on Harlow's shoulders as she sprinted across Chalk Farm Road, her boots splashing through puddles that reflected the amber glow of street…" | | 1 | "She'd been watching The Raven's Nest for weeks, that dingy bar in Soho with its green neon sign and its parade of people who didn't quite fit." | | 2 | "Goods displayed under gaslight: bottles filled with luminescent liquid, books bound in leather that looked disturbingly organic, weapons that hummed with energy…" | | 3 | "Or she could step forward into this underground market, this impossible place, and follow the thread that connected to Morris's death." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |