| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 855 | | 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) | |
| 59.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 855 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pumping" | | 1 | "glinting" | | 2 | "sanctuary" | | 3 | "absolutely" | | 4 | "weight" | | 5 | "crystal" | | 6 | "otherworldly" |
| |
| 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 | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 63 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 847 | | ratio | 0 | | matches | (empty) | |
| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "Not phantoms, she corrected herself grimly." |
| |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 842 | | uniqueNames | 19 | | maxNameDensity | 0.83 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Tomás" | | discoveredNames | | November | 1 | | Tomás | 4 | | Herrera | 1 | | Eighteen | 1 | | Morris | 2 | | Internal | 1 | | Affairs | 1 | | Homicide | 1 | | Quinn | 7 | | Saint | 1 | | Christopher | 1 | | Balkan | 1 | | Raven | 1 | | Nest | 1 | | Tomáš | 3 | | Tube | 1 | | Veil | 1 | | Market | 1 | | Marshal | 1 |
| | persons | | 0 | "Tomás" | | 1 | "Herrera" | | 2 | "Morris" | | 3 | "Affairs" | | 4 | "Quinn" | | 5 | "Saint" | | 6 | "Christopher" | | 7 | "Balkan" | | 8 | "Raven" | | 9 | "Tomáš" | | 10 | "Marshal" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 52 | | glossingSentenceCount | 1 | | matches | | 0 | "And apparently, according to files" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 847 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 49.83% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 56.47 | | std | 18.32 | | cv | 0.324 | | sampleLengths | | 0 | 66 | | 1 | 84 | | 2 | 69 | | 3 | 62 | | 4 | 84 | | 5 | 52 | | 6 | 23 | | 7 | 79 | | 8 | 32 | | 9 | 62 | | 10 | 52 | | 11 | 39 | | 12 | 38 | | 13 | 64 | | 14 | 41 |
| |
| 99.69% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 63 | | matches | | |
| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 144 | | matches | | 0 | "was blinking" | | 1 | "was going" | | 2 | "was running" | | 3 | "wasn't looking" | | 4 | "wasn't running" |
| |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 63 | | ratio | 0.095 | | matches | | 0 | "She swore under her breath, watching the figure ahead of her—Tomás Herrera—slip into an alleyway, the dark curly hair and olive skin disappearing into shadows like a ghost." | | 1 | "Paramedic, lost his license after treating supernatural patients—whatever that meant in practical terms." | | 2 | "Up ahead, a green neon sign—The Raven's Nest—was blinking furiously in the downpour, casting a watery glow on the chipped paint of the doorway." | | 3 | "Below, the air changed—warm, humid, filled with a myriad of smells she couldn't identify but somehow recognised as belonging below the city." | | 4 | "The changes came in waves—elven dignitaries in crystal headdresses, bespelled leatherwork fitted to giants disguised as humans, people she couldn't even classify doing transactions with small bone engraved tokens that must be some form of entry fee or currency." | | 5 | "That spelt confidence—or a trap." |
| |
| 85.97% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 854 | | adjectiveStacks | 1 | | stackExamples | | 0 | "comical mushroom-topped creatures." |
| | adverbCount | 42 | | adverbRatio | 0.04918032786885246 | | lyAdverbCount | 17 | | lyAdverbRatio | 0.01990632318501171 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 63 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 63 | | mean | 13.44 | | std | 7.87 | | cv | 0.586 | | sampleLengths | | 0 | 25 | | 1 | 13 | | 2 | 28 | | 3 | 12 | | 4 | 14 | | 5 | 6 | | 6 | 18 | | 7 | 7 | | 8 | 27 | | 9 | 15 | | 10 | 26 | | 11 | 28 | | 12 | 7 | | 13 | 13 | | 14 | 16 | | 15 | 18 | | 16 | 4 | | 17 | 4 | | 18 | 17 | | 19 | 11 | | 20 | 24 | | 21 | 6 | | 22 | 13 | | 23 | 2 | | 24 | 9 | | 25 | 2 | | 26 | 13 | | 27 | 13 | | 28 | 19 | | 29 | 7 | | 30 | 10 | | 31 | 3 | | 32 | 10 | | 33 | 15 | | 34 | 15 | | 35 | 16 | | 36 | 16 | | 37 | 17 | | 38 | 11 | | 39 | 17 | | 40 | 12 | | 41 | 22 | | 42 | 3 | | 43 | 2 | | 44 | 12 | | 45 | 15 | | 46 | 14 | | 47 | 3 | | 48 | 14 | | 49 | 9 |
| |
| 95.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.6190476190476191 | | totalSentences | 63 | | uniqueOpeners | 39 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 60 | | matches | | 0 | "Strangely culled accounts and reports" |
| | ratio | 0.017 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 60 | | matches | | 0 | "She swore under her breath," | | 1 | "she muttered, wiping water from" | | 2 | "It had gotten her laughed" | | 3 | "She caught a glimpse of" | | 4 | "She had done her homework" | | 5 | "They called themselves nothing official," | | 6 | "She skidded to a stop" | | 7 | "Her eyes landed on an" | | 8 | "He had known where he" | | 9 | "She approached the grate, finding" | | 10 | "It lifted silently, revealing a" | | 11 | "Her imagination was running wild" | | 12 | "She had researched it too," | | 13 | "It wasn't just about criminal" | | 14 | "It was about another layer" | | 15 | "His eyes met hers and" | | 16 | "He knew she was there." |
| | ratio | 0.283 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 60 | | matches | | 0 | "The pour of rain was" | | 1 | "Quinn's lungs burned with the" | | 2 | "She swore under her breath," | | 3 | "she muttered, wiping water from" | | 4 | "It had gotten her laughed" | | 5 | "The alley opened into a" | | 6 | "Tomáš was fast, but Quinn" | | 7 | "She caught a glimpse of" | | 8 | "She had done her homework" | | 9 | "They called themselves nothing official," | | 10 | "The rain Balkan just kamisado" | | 11 | "The scent of burnt ozone" | | 12 | "That was one of their" | | 13 | "Silas's bar, with its hidden" | | 14 | "She skidded to a stop" | | 15 | "Her eyes landed on an" | | 16 | "The kind that led below" | | 17 | "People avoided trash-filled alleyways in" | | 18 | "He had known where he" | | 19 | "Quinn muttered, straightening her coat" |
| | ratio | 0.667 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 60 | | matches | | 0 | "If Tomáš wanted sanctuary, he" | | 1 | "Either way, Quinn squared her" |
| | ratio | 0.033 | |
| 17.86% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 7 | | matches | | 0 | "The pour of rain was relentless, a grey curtain that blurred the edges of the city into watercoloured shapes of frustration and near-blinding white light." | | 1 | "She swore under her breath, watching the figure ahead of her—Tomás Herrera—slip into an alleyway, the dark curly hair and olive skin disappearing into shadows l…" | | 2 | "They called themselves nothing official, just a network, a clique of people who operated beyond conventional law enforcement." | | 3 | "Silas's bar, with its hidden back room that provided no doubt covert meetings." | | 4 | "The changes came in waves—elven dignitaries in crystal headdresses, bespelled leatherwork fitted to giants disguised as humans, people she couldn't even classif…" | | 5 | "Tomás wasn't looking at her but seemed to be monitoring the entrance where she stood, his medallion catching the overhead light." | | 6 | "Either way, Quinn squared her shoulders, holstered her gun under her coat, and moved forward, Marshal who enlisted lawful means in the face of the lawless unkno…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Quinn muttered (mutter)" |
| | dialogueSentences | 2 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 1 | | effectiveRatio | 1 | |