| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1507 | | 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) | |
| 23.69% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1507 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "shattered" | | 1 | "streaming" | | 2 | "cascading" | | 3 | "chill" | | 4 | "familiar" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "wavering" | | 8 | "stomach" | | 9 | "velvet" | | 10 | "rhythmic" | | 11 | "vibrated" | | 12 | "silk" | | 13 | "could feel" | | 14 | "weight" | | 15 | "structure" | | 16 | "fragmented" | | 17 | "unravel" | | 18 | "tracing" | | 19 | "scanning" |
| |
| 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 | 158 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 158 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 158 | | 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 | 1507 | | ratio | 0 | | matches | (empty) | |
| 83.33% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 1 | | matches | | 0 | "No bone, no passage, he said." |
| |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1507 | | uniqueNames | 21 | | maxNameDensity | 0.93 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 3 | | High | 1 | | Street | 1 | | Metropolitan | 2 | | Police | 3 | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Herrera | 7 | | Seville | 1 | | London | 2 | | Underground | 1 | | Morris | 4 | | Quinn | 14 | | Veil | 1 | | Market | 2 | | Detective | 1 | | Saint | 1 | | Christopher | 1 | | Three | 4 | | Tonight | 3 |
| | persons | | 0 | "Police" | | 1 | "Raven" | | 2 | "Herrera" | | 3 | "Underground" | | 4 | "Morris" | | 5 | "Quinn" | | 6 | "Market" | | 7 | "Saint" | | 8 | "Christopher" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Soho" | | 4 | "Seville" | | 5 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 106 | | 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 | 1507 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 158 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 55.81 | | std | 36.44 | | cv | 0.653 | | sampleLengths | | 0 | 84 | | 1 | 129 | | 2 | 12 | | 3 | 111 | | 4 | 68 | | 5 | 22 | | 6 | 95 | | 7 | 19 | | 8 | 89 | | 9 | 92 | | 10 | 9 | | 11 | 67 | | 12 | 46 | | 13 | 16 | | 14 | 118 | | 15 | 69 | | 16 | 33 | | 17 | 11 | | 18 | 44 | | 19 | 29 | | 20 | 51 | | 21 | 38 | | 22 | 4 | | 23 | 92 | | 24 | 79 | | 25 | 66 | | 26 | 14 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 158 | | matches | | 0 | "were gone" | | 1 | "was scratched" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 265 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 158 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1516 | | adjectiveStacks | 1 | | stackExamples | | 0 | "pale, knuckle-sized object," |
| | adverbCount | 25 | | adverbRatio | 0.016490765171503958 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.006596306068601583 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 158 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 158 | | mean | 9.54 | | std | 6.83 | | cv | 0.716 | | sampleLengths | | 0 | 20 | | 1 | 10 | | 2 | 22 | | 3 | 16 | | 4 | 16 | | 5 | 15 | | 6 | 20 | | 7 | 7 | | 8 | 2 | | 9 | 8 | | 10 | 33 | | 11 | 28 | | 12 | 16 | | 13 | 1 | | 14 | 1 | | 15 | 10 | | 16 | 5 | | 17 | 12 | | 18 | 6 | | 19 | 29 | | 20 | 1 | | 21 | 2 | | 22 | 9 | | 23 | 27 | | 24 | 20 | | 25 | 11 | | 26 | 15 | | 27 | 10 | | 28 | 7 | | 29 | 6 | | 30 | 9 | | 31 | 5 | | 32 | 5 | | 33 | 9 | | 34 | 4 | | 35 | 9 | | 36 | 14 | | 37 | 6 | | 38 | 3 | | 39 | 13 | | 40 | 9 | | 41 | 6 | | 42 | 8 | | 43 | 20 | | 44 | 8 | | 45 | 8 | | 46 | 6 | | 47 | 7 | | 48 | 3 | | 49 | 3 |
| |
| 47.89% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.34810126582278483 | | totalSentences | 158 | | uniqueOpeners | 55 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 141 | | matches | (empty) | | ratio | 0 | |
| 83.83% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 141 | | matches | | 0 | "He moved with the desperate" | | 1 | "Her left wrist ached where" | | 2 | "She checked the time out" | | 3 | "She’d spent weeks mapping the" | | 4 | "she shouted, though the wind" | | 5 | "He cut left down a" | | 6 | "She caught a flash of" | | 7 | "He vaulted a rusted gate" | | 8 | "Her breath plumed in the" | | 9 | "Her thumb drifted to the" | | 10 | "She wiped it on her" | | 11 | "They’d called it a structural" | | 12 | "She’d smelled the copper-and-ash stink" | | 13 | "She still didn’t understand what" | | 14 | "She only knew it hadn’t" | | 15 | "He was tiring." | | 16 | "He didn’t knock." | | 17 | "He pulled something from his" | | 18 | "Her boots skidded on the" | | 19 | "She jammed her shoulder against" |
| | ratio | 0.34 | |
| 73.48% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 141 | | matches | | 0 | "Rain fell in hard, diagonal" | | 1 | "Quinn’s boots hit the pavement" | | 2 | "He moved with the desperate" | | 3 | "Quinn adjusted her grip on" | | 4 | "Her left wrist ached where" | | 5 | "She checked the time out" | | 6 | "She’d spent weeks mapping the" | | 7 | "Tonight, she’d finally caught one" | | 8 | "she shouted, though the wind" | | 9 | "The suspect didn’t break stride." | | 10 | "He cut left down a" | | 11 | "Quinn followed, shoulder brushing damp" | | 12 | "She caught a flash of" | | 13 | "The name clicked into place" | | 14 | "He vaulted a rusted gate" | | 15 | "Quinn hit the landing a" | | 16 | "The air grew thick, smelling" | | 17 | "Her breath plumed in the" | | 18 | "This wasn’t just a maintenance" | | 19 | "The tiles on the walls" |
| | ratio | 0.773 | |
| 70.92% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 141 | | matches | | 0 | "Now he was the clique’s" | | 1 | "If she let that door" |
| | ratio | 0.014 | |
| 27.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 10 | | matches | | 0 | "She’d spent weeks mapping the clique’s movements through that bar, noting how they vanished through a bookshelf in the back room that led nowhere on any archite…" | | 1 | "Tonight, she’d finally caught one of them carrying a duffel bag that clinked like glass vials." | | 2 | "Born in Seville, moved to London for the NHS, lost his medical license after administering unauthorized treatments to patients who didn’t show up on any hospita…" | | 3 | "Now he was the clique’s off-the-books surgeon, patching up criminals who bled colors that didn’t belong in a human body." | | 4 | "The file sat in her bottom drawer, a ghost that breathed down her neck every time she worked past midnight." | | 5 | "Above it, someone had spray-painted a symbol that made Quinn’s stomach tighten: a circle split by a jagged line." | | 6 | "She could feel the weight of her badge in her pocket, the rigid structure of the law that had kept her upright for nearly two decades." | | 7 | "A black market that traded in enchanted goods, banned alchemical substances, and information that could unravel a life." | | 8 | "Lanterns hung from rusted girders, casting amber pools over tables laden with dried roots, stoppered bottles, and weapons that looked too old to be legal." | | 9 | "She kept her hands loose at her sides, her gaze scanning, her mind cataloging exits, threats, angles." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |