| 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 | 1107 | | 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) | |
| 27.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1107 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "measured" | | 2 | "echoed" | | 3 | "oppressive" | | 4 | "gloom" | | 5 | "velvet" | | 6 | "footsteps" | | 7 | "shimmered" | | 8 | "pulse" | | 9 | "grave" | | 10 | "silence" | | 11 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 77 | | matches | (empty) | |
| 31.54% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 4 | | narrationSentences | 77 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 77 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1097 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 3 | | matches | | 0 | "Herrera, she said, her voice dropping into the low, steady register she used for interrogations." | | 1 | "something other than patients, has a lot to answer for, Quinn retorted, closing the gap by a single, deliberate pace." | | 2 | "Where you go, I go, she said, her voice as hard as the London stone." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 43 | | wordCount | 1097 | | uniqueNames | 16 | | maxNameDensity | 0.64 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Harlow" | | discoveredNames | | Soho | 1 | | London | 2 | | Harlow | 6 | | Quinn | 7 | | Herrera | 6 | | Raven | 2 | | Nest | 2 | | Tomás | 6 | | Tube | 1 | | Veil | 1 | | Market | 2 | | Saint | 1 | | Christopher | 1 | | Morris | 2 | | Detective | 2 | | Met | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Tomás" | | 5 | "Market" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 29.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 3 | | matches | | 0 | "bioluminescence that seemed to cling to the stalactites overhead" | | 1 | "looked like a reflection in a broken mirr" | | 2 | "felt like a toy sword against an oncomi" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1097 | | matches | (empty) | |
| 36.80% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 77 | | matches | | 0 | "understand that a" | | 1 | "understand that my" | | 2 | "cross that line" |
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| 77.36% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 24 | | mean | 45.71 | | std | 19.23 | | cv | 0.421 | | sampleLengths | | 0 | 92 | | 1 | 54 | | 2 | 59 | | 3 | 63 | | 4 | 59 | | 5 | 24 | | 6 | 59 | | 7 | 35 | | 8 | 19 | | 9 | 53 | | 10 | 57 | | 11 | 31 | | 12 | 43 | | 13 | 68 | | 14 | 20 | | 15 | 22 | | 16 | 67 | | 17 | 42 | | 18 | 63 | | 19 | 49 | | 20 | 24 | | 21 | 31 | | 22 | 15 | | 23 | 48 |
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| 87.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 77 | | matches | | 0 | "being hunted" | | 1 | "were draped" | | 2 | "was littered" | | 3 | "was trapped" | | 4 | "was consumed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 180 | | matches | | 0 | "was like stepping" | | 1 | "was standing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 2 | | flaggedSentences | 8 | | totalSentences | 77 | | ratio | 0.104 | | matches | | 0 | "The rain in Soho was not a gentle mist; it was a rhythmic, punishing deluge that turned the London streets into a network of slick, black mirrors." | | 1 | "She simply closed the distance, her keen brown eyes fixed on the way Tomás favored his left arm—a subconscious defense of that jagged white scar running beneath his sleeve." | | 2 | "She had heard rumors of it—the black market that migrated with the moon—but seeing it was like stepping into an abscess in the city’s foundation." | | 3 | "She heard a soft, rhythmic clinking ahead—the sound of a chain hitting a Saint Christopher medallion." | | 4 | "What you’re looking for—the things you think we’re doing—you don’t understand the mechanism behind it." | | 5 | "It wasn’t a shadow; it was a hungry absence." | | 6 | "The ambient noise of the Market—hushed whispers, the clinking of alchemical vials, the low chant of unseen merchants—fell deathly silent." | | 7 | "But then she looked at Herrera’s scar—the evidence of a life lived in the margins—and saw the reflection of her own obsessions staring back." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1111 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.021602160216021602 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.0063006300630063005 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 77 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 77 | | mean | 14.25 | | std | 7.51 | | cv | 0.527 | | sampleLengths | | 0 | 27 | | 1 | 23 | | 2 | 17 | | 3 | 25 | | 4 | 16 | | 5 | 4 | | 6 | 5 | | 7 | 29 | | 8 | 14 | | 9 | 3 | | 10 | 11 | | 11 | 31 | | 12 | 9 | | 13 | 15 | | 14 | 23 | | 15 | 16 | | 16 | 5 | | 17 | 24 | | 18 | 5 | | 19 | 25 | | 20 | 8 | | 21 | 16 | | 22 | 30 | | 23 | 11 | | 24 | 18 | | 25 | 15 | | 26 | 20 | | 27 | 15 | | 28 | 4 | | 29 | 18 | | 30 | 11 | | 31 | 9 | | 32 | 15 | | 33 | 13 | | 34 | 20 | | 35 | 14 | | 36 | 10 | | 37 | 6 | | 38 | 4 | | 39 | 3 | | 40 | 18 | | 41 | 13 | | 42 | 21 | | 43 | 9 | | 44 | 21 | | 45 | 19 | | 46 | 9 | | 47 | 19 | | 48 | 11 | | 49 | 5 |
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| 43.29% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.33766233766233766 | | totalSentences | 77 | | uniqueOpeners | 26 | |
| 43.86% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 76 | | matches | | 0 | "Then come and collect it," |
| | ratio | 0.013 | |
| 51.58% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 76 | | matches | | 0 | "He skirted the perimeter of" | | 1 | "She didn't call out." | | 2 | "She didn't announce her presence." | | 3 | "She simply closed the distance," | | 4 | "He banked hard into an" | | 5 | "She rounded the corner, her" | | 6 | "She pulled her torch, the" | | 7 | "She had heard rumors of" | | 8 | "Her footsteps were agonizingly loud" | | 9 | "She heard a soft, rhythmic" | | 10 | "He looked back, his warm" | | 11 | "He was trapped between a" | | 12 | "She planted her feet, projecting" | | 13 | "I can’t go to the" | | 14 | "I understand that a man" | | 15 | "I understand that my partner" | | 16 | "He was consumed." | | 17 | "It wasn’t a shadow; it" | | 18 | "You’re hiding behind a bogeyman," | | 19 | "I don’t believe in monsters." |
| | ratio | 0.421 | |
| 25.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 76 | | matches | | 0 | "The rain in Soho was" | | 1 | "Detective Harlow Quinn ignored the" | | 2 | "Tomás Herrera moved with the" | | 3 | "He skirted the perimeter of" | | 4 | "Harlow tracked him, her stride" | | 5 | "She didn't call out." | | 6 | "She didn't announce her presence." | | 7 | "She simply closed the distance," | | 8 | "He banked hard into an" | | 9 | "Harlow didn’t hesitate." | | 10 | "She rounded the corner, her" | | 11 | "The alley was a dead" | | 12 | "The air grew heavy and" | | 13 | "The smell of ozone and" | | 14 | "She pulled her torch, the" | | 15 | "This wasn’t any derelict station." | | 16 | "The walls were draped in" | | 17 | "This was the Veil Market." | | 18 | "She had heard rumors of" | | 19 | "Her footsteps were agonizingly loud" |
| | ratio | 0.868 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 76 | | matches | | 0 | "By the time she reached" | | 1 | "What you’re looking for—the things" | | 2 | "If you cross that line," |
| | ratio | 0.039 | |
| 50.26% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 7 | | matches | | 0 | "The rain in Soho was not a gentle mist; it was a rhythmic, punishing deluge that turned the London streets into a network of slick, black mirrors." | | 1 | "The alley was a dead end for the public, but Herrera took a sharp left, disappearing into the throat of an old maintenance stairwell that led deep into the city…" | | 2 | "The walls were draped in heavy, velvet tapestries that felt wrong in the damp air, and the floor was littered with unrecognizable, calcified refuse." | | 3 | "She had heard rumors of it—the black market that migrated with the moon—but seeing it was like stepping into an abscess in the city’s foundation." | | 4 | "Tomás was standing near a pillar draped in rotting lace, his chest heaving, his olive skin pale beneath the artificial, sickly bioluminescence that seemed to cl…" | | 5 | "She planted her feet, projecting the authority of a woman who had seen the worst of humanity and remained unbreaking." | | 6 | "I understand that a man who loses his medical license for practicing on…" |
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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 | |