| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 95.93% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1227 | | 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) | |
| 51.10% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1227 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "glinting" | | 1 | "pulse" | | 2 | "clandestine" | | 3 | "scanned" | | 4 | "gloom" | | 5 | "efficient" | | 6 | "weight" | | 7 | "charged" | | 8 | "mosaic" | | 9 | "silk" | | 10 | "scanning" | | 11 | "shimmered" |
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| 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 | 72 | | matches | (empty) | |
| 63.49% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 2 | | narrationSentences | 72 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 72 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1209 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 61 | | wordCount | 1209 | | uniqueNames | 21 | | maxNameDensity | 0.99 | | worstName | "Harlow" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Dean | 1 | | Street | 2 | | Soho | 1 | | Harlow | 12 | | Quinn | 2 | | Raven | 3 | | Nest | 3 | | London | 2 | | Morris | 2 | | Tomás | 3 | | Herrera | 11 | | Saint | 2 | | Christopher | 2 | | Brewer | 1 | | Seville | 1 | | London-hardened | 1 | | Camden | 2 | | Tube | 2 | | Veil | 3 | | Market | 3 | | Detective | 2 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Morris" | | 4 | "Tomás" | | 5 | "Herrera" | | 6 | "Saint" | | 7 | "Christopher" |
| | places | | 0 | "Dean" | | 1 | "Street" | | 2 | "Soho" | | 3 | "London" | | 4 | "Brewer" | | 5 | "Seville" | | 6 | "London-hardened" | | 7 | "Camden" | | 8 | "Market" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.481 | | wordCount | 1209 | | matches | | 0 | "Not the front entrance with its welcoming haze of smoke and jazz, but the hidden shelf" | | 1 | "not running, not yet, but with the efficient stride of a former paramedic who knew how" | | 2 | "not yet, but with the efficient stride of a former paramedic who knew how" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 72 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 39 | | std | 32.58 | | cv | 0.835 | | sampleLengths | | 0 | 87 | | 1 | 57 | | 2 | 5 | | 3 | 89 | | 4 | 8 | | 5 | 73 | | 6 | 32 | | 7 | 2 | | 8 | 86 | | 9 | 13 | | 10 | 3 | | 11 | 80 | | 12 | 54 | | 13 | 6 | | 14 | 72 | | 15 | 4 | | 16 | 7 | | 17 | 67 | | 18 | 18 | | 19 | 2 | | 20 | 65 | | 21 | 3 | | 22 | 67 | | 23 | 8 | | 24 | 85 | | 25 | 74 | | 26 | 25 | | 27 | 8 | | 28 | 38 | | 29 | 6 | | 30 | 65 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 72 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 212 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 18 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 72 | | ratio | 0.167 | | matches | | 0 | "The sign buzzed like an angry insect, casting sickly emerald light across the old maps and black-and-white photographs she knew hung inside—photographs of a London that no longer existed, or perhaps never had." | | 1 | "Not the front entrance with its welcoming haze of smoke and jazz, but the hidden shelf—the one that swung open into the alley behind the bar." | | 2 | "The scar running along his left forearm—old damage, knife-wound white against the dark—was visible even in the gloom as he pulled his coat tight." | | 3 | "She had suspected the clique of criminal activity for months—stolen alchemical supplies, unauthorized treatments, the kind of off-the-books medicine that had cost Herrera his NHS license after he treated supernatural patients he refused to name." | | 4 | "Herrera was quick—Seville-born, London-hardened, a man who had survived knife attacks and license revocations—but she was relentless." | | 5 | "She had heard whispers—bone tokens required for entry, the location shifting every full moon, a black market beneath Camden that dealt in enchanted goods and banned alchemical substances and information that could kill." | | 6 | "He reached into his coat, produced something small and pale—a carved token, bone-yellow in the streetlight—and pressed it against the gate’s lock." | | 7 | "Down there was unfamiliar territory—potentially dangerous, certainly supernatural, the kind of place that had taken Morris and never explained why." | | 8 | "Harlow descended with her hand near her hip, counting steps—twenty, thirty, forty—until the air changed, growing warmer, denser, charged with a pressure that made her teeth ache." | | 9 | "Stalls displayed goods she could not name—vials of liquid that moved against gravity, books bound in something that was not leather, herbs that glowed with a faint, poisonous blue." | | 10 | "She watched him exchange a packet—small, wrapped in black silk—for a vial of crimson liquid." | | 11 | "She could arrest him now—draw her weapon, announce herself, drag him back to the surface and into a world of courts and confessions that might never explain the truth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1238 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.023424878836833602 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.008077544426494346 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 72 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 72 | | mean | 16.79 | | std | 11.7 | | cv | 0.697 | | sampleLengths | | 0 | 16 | | 1 | 38 | | 2 | 33 | | 3 | 22 | | 4 | 35 | | 5 | 5 | | 6 | 26 | | 7 | 23 | | 8 | 40 | | 9 | 8 | | 10 | 37 | | 11 | 24 | | 12 | 12 | | 13 | 27 | | 14 | 5 | | 15 | 2 | | 16 | 22 | | 17 | 11 | | 18 | 35 | | 19 | 13 | | 20 | 5 | | 21 | 4 | | 22 | 9 | | 23 | 3 | | 24 | 4 | | 25 | 22 | | 26 | 17 | | 27 | 37 | | 28 | 20 | | 29 | 34 | | 30 | 3 | | 31 | 3 | | 32 | 33 | | 33 | 5 | | 34 | 7 | | 35 | 5 | | 36 | 22 | | 37 | 4 | | 38 | 7 | | 39 | 23 | | 40 | 20 | | 41 | 4 | | 42 | 4 | | 43 | 16 | | 44 | 18 | | 45 | 2 | | 46 | 16 | | 47 | 27 | | 48 | 22 | | 49 | 3 |
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| 48.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3472222222222222 | | totalSentences | 72 | | uniqueOpeners | 25 | |
| 95.24% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 70 | | matches | | 0 | "Then the back door moved." | | 1 | "Then he ran." |
| | ratio | 0.029 | |
| 82.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 70 | | matches | | 0 | "She was forty-one, with a" | | 1 | "She knew the layout because" | | 2 | "She recognized him from the" | | 3 | "He moved fast, not running," | | 4 | "She had suspected the clique" | | 5 | "She would not lose him." | | 6 | "He glanced back once." | | 7 | "Their eyes met for a" | | 8 | "She had buried a partner" | | 9 | "They crossed into Camden, the" | | 10 | "She had heard whispers—bone tokens" | | 11 | "She had never seen it." | | 12 | "She had never wanted to" | | 13 | "He reached into his coat," | | 14 | "She had no token." | | 15 | "She had no backup." | | 16 | "She had only her service" | | 17 | "He moved through the crowd" | | 18 | "She watched him exchange a" | | 19 | "His warm brown eyes met" |
| | ratio | 0.343 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 56 | | totalSentences | 70 | | matches | | 0 | "Rain sheared down Dean Street" | | 1 | "Detective Harlow Quinn kept her" | | 2 | "The sign buzzed like an" | | 3 | "She was forty-one, with a" | | 4 | "Harlow had mapped The Raven’s" | | 5 | "She knew the layout because" | | 6 | "The man who slipped out" | | 7 | "She recognized him from the" | | 8 | "The scar running along his" | | 9 | "He moved fast, not running," | | 10 | "Harlow stepped into the rain." | | 11 | "Herrera turned onto Brewer Street," | | 12 | "Harlow kept fifteen paces back," | | 13 | "She had suspected the clique" | | 14 | "She would not lose him." | | 15 | "He glanced back once." | | 16 | "Their eyes met for a" | | 17 | "The chase turned savage." | | 18 | "Rain lashed Harlow’s face as" | | 19 | "Herrera was quick—Seville—born, London-hardened, a" |
| | ratio | 0.8 | |
| 71.43% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 70 | | matches | | 0 | "Now she had him leaving" |
| | ratio | 0.014 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 14 | | matches | | 0 | "She was forty-one, with a sharp jaw and brown eyes that missed nothing, her closely cropped salt-and-pepper hair already darkening with rain." | | 1 | "She recognized him from the file: twenty-nine, olive skin, short curly dark brown hair plastered now to his forehead, warm brown eyes that should have looked ki…" | | 2 | "She had suspected the clique of criminal activity for months—stolen alchemical supplies, unauthorized treatments, the kind of off-the-books medicine that had co…" | | 3 | "Herrera was quick—Seville-born, London-hardened, a man who had survived knife attacks and license revocations—but she was relentless." | | 4 | "Herrera turned down a service road Harlow did not recognize, then stopped at the mouth of an abandoned Tube station, its entrance choked with rusted gates and w…" | | 5 | "She had heard whispers—bone tokens required for entry, the location shifting every full moon, a black market beneath Camden that dealt in enchanted goods and ba…" | | 6 | "Harlow skidded to a stop at the threshold, rain dripping from her jaw, her heart hammering a precise, military rhythm against her ribs." | | 7 | "Down there was unfamiliar territory—potentially dangerous, certainly supernatural, the kind of place that had taken Morris and never explained why." | | 8 | "The stairs were slick with moss and something darker, something that smelled of copper and incense." | | 9 | "Harlow descended with her hand near her hip, counting steps—twenty, thirty, forty—until the air changed, growing warmer, denser, charged with a pressure that ma…" | | 10 | "Stalls displayed goods she could not name—vials of liquid that moved against gravity, books bound in something that was not leather, herbs that glowed with a fa…" | | 11 | "The crowd was a mosaic of the impossible: figures in long coats with faces obscured by bone masks, others with eyes that reflected no light." | | 12 | "She had come for answers about the clique, about the crimes that connected The Raven’s Nest to this underground rot, about the supernatural origins of her partn…" | | 13 | "Below, in the abandoned Tube station that moved with the moon, Detective Harlow Quinn chose pursuit over safety." |
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| 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 | |