| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 1 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1331 | | 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) | |
| 58.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1331 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "etched" | | 1 | "glinting" | | 2 | "echoing" | | 3 | "aftermath" | | 4 | "determined" | | 5 | "unravel" | | 6 | "shimmered" | | 7 | "pawn" | | 8 | "silence" |
| |
| 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 | 1 | | narrationSentences | 66 | | matches | | |
| 34.63% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 1 | | narrationSentences | 66 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 66 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1303 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.46% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 60 | | wordCount | 1300 | | uniqueNames | 22 | | maxNameDensity | 1.23 | | worstName | "Tomás" | | maxWindowNameDensity | 2 | | worstWindowName | "Tomás" | | discoveredNames | | London | 2 | | Soho | 1 | | Harlow | 1 | | Quinn | 11 | | Tomás | 16 | | Herrera | 1 | | Raven | 1 | | Nest | 1 | | Saint | 1 | | Christopher | 1 | | Scottish | 1 | | Highlands | 1 | | East | 1 | | Camden | 3 | | High | 1 | | Street | 1 | | Morris | 7 | | Tube | 2 | | Veil | 1 | | Market | 1 | | Seville | 1 | | You | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Raven" | | 5 | "Nest" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Morris" | | 9 | "Market" | | 10 | "You" |
| | places | | 0 | "London" | | 1 | "Soho" | | 2 | "Scottish" | | 3 | "Highlands" | | 4 | "East" | | 5 | "Camden" | | 6 | "High" | | 7 | "Street" | | 8 | "Seville" |
| | globalScore | 0.885 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | 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 | 1303 | | matches | (empty) | |
| 65.66% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 66 | | matches | | 0 | "drop that paper" | | 1 | "cross that line" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 59.23 | | std | 35.23 | | cv | 0.595 | | sampleLengths | | 0 | 88 | | 1 | 87 | | 2 | 89 | | 3 | 82 | | 4 | 30 | | 5 | 9 | | 6 | 78 | | 7 | 85 | | 8 | 97 | | 9 | 12 | | 10 | 14 | | 11 | 79 | | 12 | 93 | | 13 | 75 | | 14 | 8 | | 15 | 25 | | 16 | 22 | | 17 | 93 | | 18 | 19 | | 19 | 24 | | 20 | 111 | | 21 | 83 |
| |
| 89.31% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 66 | | matches | | 0 | "was tangled" | | 1 | "was determined" | | 2 | "been found" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 214 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 20 | | semicolonCount | 3 | | flaggedSentences | 17 | | totalSentences | 66 | | ratio | 0.258 | | matches | | 0 | "Her closely cropped salt-and-pepper hair stuck to her sharp jaw, and her worn leather watch glinted under a flickering storefront light—18 years of decorated service etched into every line of her military precision stance." | | 1 | "The bar’s walls, she knew from her stakeout notes, lined with old maps and black-and-white photographs—clues to the clique’s movements, maybe, but she hadn’t gotten close enough to check." | | 2 | "The stand’s owner yelled, but she didn’t glance back—her focus was solely on Tomás’s retreating figure." | | 3 | "He darted between two parked cars, his scar—thin, silvery, a memento from a knife attack—glinting when he yanked his coat sleeve up to grip a car’s side mirror and pull himself around a corner." | | 4 | "She’d tracked suspects through worse—blizzards in the Scottish Highlands, riot-torn estates in East London—but the rain added a layer of friction, making every step a battle against the elements." | | 5 | "Her partner’s face—DS Morris, cold and still three years prior—flashed in her mind." | | 6 | "Quinn followed, her hand drifting to the baton at her belt—she didn’t carry a gun on stakeouts, not when she needed to corner a suspect without drawing unwanted attention from the clique’s lookouts, who she’d spotted loitering in the area for days." | | 7 | "Tomás bounded down them, his boots echoing off the damp stone walls covered in faded symbols she didn’t recognize—markers for the Veil Market, she guessed." | | 8 | "She’d read confidential reports of the hidden supernatural black market: it sold enchanted goods, banned alchemical substances, and information; it moved every full moon; its current location was an abandoned Tube station beneath Camden; entry required a bone token." | | 9 | "She could smell something acrid—burned sage mixed with the metallic tang of alchemical reagents—drifting up from the darkness below." | | 10 | "Tomás fumbled in his coat pocket, pulling out a small, yellowed token—bone, Quinn realized, her eyes narrowing." | | 11 | "The door rumbled open, spilling faint purple light into the stairwell, and Quinn could hear the murmur of voices from beyond—whispers in a language she didn’t recognize, the clink of glass vials, the rustle of enchanted fabrics that shimmered even in the dim light." | | 12 | "She reached the bottom step, her baton now in her hand, and studied Tomás—his shoulders hunched, his medallion twisting in his fingers as he hesitated in the doorframe." | | 13 | "She thought of Morris, of the way his body had been found with no visible wounds, of the strange symbols carved into the warehouse walls where he’d died—symbols the forensics team couldn’t identify." | | 14 | "She could turn back—call for backup, wait for a warrant, play by the book." | | 15 | "The full moon was high, and the market would move soon—she’d lose her chance to uncover the truth if she hesitated." | | 16 | "She had to decide—turn back, or follow the suspect into the unfamiliar, dangerous underground market." |
| |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1328 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small, yellowed token—bone," | | 1 | "unfamiliar, dangerous underground market." |
| | adverbCount | 19 | | adverbRatio | 0.01430722891566265 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.006024096385542169 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 66 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 66 | | mean | 19.74 | | std | 11.39 | | cv | 0.577 | | sampleLengths | | 0 | 15 | | 1 | 21 | | 2 | 34 | | 3 | 18 | | 4 | 24 | | 5 | 29 | | 6 | 34 | | 7 | 26 | | 8 | 15 | | 9 | 16 | | 10 | 32 | | 11 | 34 | | 12 | 19 | | 13 | 29 | | 14 | 30 | | 15 | 9 | | 16 | 12 | | 17 | 27 | | 18 | 13 | | 19 | 13 | | 20 | 2 | | 21 | 2 | | 22 | 9 | | 23 | 43 | | 24 | 42 | | 25 | 21 | | 26 | 25 | | 27 | 39 | | 28 | 12 | | 29 | 12 | | 30 | 7 | | 31 | 7 | | 32 | 4 | | 33 | 21 | | 34 | 19 | | 35 | 11 | | 36 | 24 | | 37 | 17 | | 38 | 32 | | 39 | 44 | | 40 | 28 | | 41 | 25 | | 42 | 22 | | 43 | 8 | | 44 | 7 | | 45 | 18 | | 46 | 7 | | 47 | 15 | | 48 | 20 | | 49 | 33 |
| |
| 34.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.2878787878787879 | | totalSentences | 66 | | uniqueOpeners | 19 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 13.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 62 | | matches | | 0 | "Her closely cropped salt-and-pepper hair" | | 1 | "She locked eyes with Tomás" | | 2 | "Her boots slammed into the" | | 3 | "His short curly dark brown" | | 4 | "He darted between two parked" | | 5 | "She’d tracked suspects through worse—blizzards" | | 6 | "You drop that paper, I’ll" | | 7 | "He straightened, grabbed a metal" | | 8 | "Her partner’s face—DS Morris, cold" | | 9 | "They hit Camden’s labyrinth of" | | 10 | "She’d read confidential reports of" | | 11 | "Her worn leather watch’s date" | | 12 | "You don’t know what you’re" | | 13 | "She took a step down," | | 14 | "She could smell something acrid—burned" | | 15 | "She’d tracked suspects into dangerous" | | 16 | "He pressed it into an" | | 17 | "She reached the bottom step," | | 18 | "He’d lost his NHS license" | | 19 | "He was a pawn, but" |
| | ratio | 0.516 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 62 | | matches | | 0 | "Rain lashed London’s Soho sidewalks," | | 1 | "Detective Harlow Quinn planted her" | | 2 | "Her closely cropped salt-and-pepper hair" | | 3 | "She locked eyes with Tomás" | | 4 | "Tomás had slipped out of" | | 5 | "The bar’s walls, she knew" | | 6 | "The distinctive green neon sign" | | 7 | "Quinn pushed off the wall" | | 8 | "Her boots slammed into the" | | 9 | "The stand’s owner yelled, but" | | 10 | "His short curly dark brown" | | 11 | "He darted between two parked" | | 12 | "Quinn followed, her boots skidding" | | 13 | "She’d tracked suspects through worse—blizzards" | | 14 | "You drop that paper, I’ll" | | 15 | "Tomás’s hand flew to the" | | 16 | "He straightened, grabbed a metal" | | 17 | "The rain intensified, soaking Quinn’s" | | 18 | "Her partner’s face—DS Morris, cold" | | 19 | "The clique Tomás aided was" |
| | ratio | 0.952 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 50 | | technicalSentenceCount | 5 | | matches | | 0 | "Quinn followed, her hand drifting to the baton at her belt—she didn’t carry a gun on stakeouts, not when she needed to corner a suspect without drawing unwanted…" | | 1 | "Tomás fumbled in his coat pocket, pulling out a small, yellowed token—bone, Quinn realized, her eyes narrowing." | | 2 | "The door rumbled open, spilling faint purple light into the stairwell, and Quinn could hear the murmur of voices from beyond—whispers in a language she didn’t r…" | | 3 | "He was a pawn, but he was a pawn with information, information that could lead her to the truth about Morris’s death." | | 4 | "She thought of the military precision that had carried her through 18 years of decorated service, of the sharp jaw that had never flinched from a fight, of the …" |
| |
| 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 | |