| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "he said finally [finally]" |
| | dialogueSentences | 20 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.125 | | effectiveRatio | 0.1 | |
| 96.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1541 | | 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) | |
| 61.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1541 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "echoed" | | 1 | "familiar" | | 2 | "glint" | | 3 | "footsteps" | | 4 | "fractured" | | 5 | "unsettled" | | 6 | "etched" | | 7 | "glinting" | | 8 | "silence" | | 9 | "could feel" | | 10 | "weight" | | 11 | "depths" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 123 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 123 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 15 | | totalWords | 1525 | | ratio | 0.01 | | matches | | 0 | "Midnight. Camden. He'll be moving product." | | 1 | "Don't go without a guide. Don't go at all." |
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| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "For a long moment, he said nothing." |
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| 99.42% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1384 | | uniqueNames | 21 | | maxNameDensity | 1.01 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Tomás" | | discoveredNames | | Harlow | 1 | | Quinn | 14 | | Silas | 2 | | Kaine | 2 | | Raven | 1 | | Nest | 1 | | Tottenham | 1 | | Court | 1 | | Road | 1 | | Jubilee | 1 | | Sauer | 1 | | Maglite | 1 | | Morris | 4 | | Hungerford | 1 | | Bridge | 1 | | Veil | 1 | | Market | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 1 | | Tomás | 6 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Silas" | | 3 | "Kaine" | | 4 | "Sauer" | | 5 | "Morris" | | 6 | "Market" | | 7 | "Saint" | | 8 | "Christopher" | | 9 | "Herrera" | | 10 | "Tomás" |
| | places | | 0 | "Raven" | | 1 | "Tottenham" | | 2 | "Court" | | 3 | "Road" | | 4 | "Hungerford" | | 5 | "Bridge" |
| | globalScore | 0.994 | | windowScore | 1 | |
| 59.64% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 3 | | matches | | 0 | "appeared, emerging from a service entrance like a rat testing the air before committing to a garbage run" | | 1 | "looked like it had been there for years," | | 2 | "looked like dried flowers but moved when" |
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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 | 1525 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 30.5 | | std | 22.48 | | cv | 0.737 | | sampleLengths | | 0 | 62 | | 1 | 13 | | 2 | 63 | | 3 | 42 | | 4 | 77 | | 5 | 48 | | 6 | 6 | | 7 | 57 | | 8 | 20 | | 9 | 43 | | 10 | 44 | | 11 | 49 | | 12 | 3 | | 13 | 47 | | 14 | 8 | | 15 | 28 | | 16 | 52 | | 17 | 56 | | 18 | 21 | | 19 | 14 | | 20 | 6 | | 21 | 51 | | 22 | 3 | | 23 | 80 | | 24 | 25 | | 25 | 54 | | 26 | 2 | | 27 | 23 | | 28 | 73 | | 29 | 5 | | 30 | 30 | | 31 | 4 | | 32 | 28 | | 33 | 47 | | 34 | 17 | | 35 | 4 | | 36 | 34 | | 37 | 55 | | 38 | 9 | | 39 | 23 | | 40 | 13 | | 41 | 8 | | 42 | 4 | | 43 | 31 | | 44 | 42 | | 45 | 23 | | 46 | 10 | | 47 | 7 | | 48 | 4 | | 49 | 57 |
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| 96.71% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 123 | | matches | | 0 | "were rusted" | | 1 | "was chipped" | | 2 | "was carved" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 232 | | matches | | 0 | "were running" | | 1 | "was gaining" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 16 | | semicolonCount | 0 | | flaggedSentences | 14 | | totalSentences | 135 | | ratio | 0.104 | | matches | | 0 | "Detective Harlow Quinn moved through the downpour with the economy of motion that eighteen years on the force had drilled into her bones—breath steady, heels striking the wet pavement in a rhythm she could have kept up all night." | | 1 | "Tonight, she'd finally caught a break—a tip from a CI who owed her a favor, whispered between sips of cheap whiskey in a pub near Tottenham Court Road." | | 2 | "He'd spotted her almost immediately—good instincts, or guilty conscience—and now they were running." | | 3 | "Ten feet down, the light caught a glint of metal—a discarded syringe." | | 4 | "The air changed as she descended—grew cooler, damper, heavy with the smell of old concrete and something else." | | 5 | "The man's footprints were visible in the grime—fresh impressions, heading north along the tunnel." | | 6 | "The paint was chipped, revealing wood that felt wrong—too smooth, too warm, like living skin." | | 7 | "She'd heard rumors of these things—entry fees for places the city's official maps didn't mark." | | 8 | "It simply swung inward, revealing a staircase that descended into amber light—candlelight, gaslight, something older and warmer than electricity." | | 9 | "The air was thick with incense and smoke and the smell of things cooking—meat and spices and something sweet, cloying, wrong." | | 10 | "Ex-paramedic, license revoked, rumored to provide medical services to people the hospitals wouldn't—or couldn't—treat." | | 11 | "The patrons here didn't spare her a glance—they were too busy with their own business, heads bent over potions and artifacts and documents yellowed with age." | | 12 | "Around them, the market hummed with its own strange life—bargains struck, favors traded, secrets sold by the word." | | 13 | "She had a choice to make—push deeper into the dark, risk whatever had taken Morris, or retreat to the light where she understood the rules." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1402 | | adjectiveStacks | 1 | | stackExamples | | 0 | "old, painted black, set" |
| | adverbCount | 27 | | adverbRatio | 0.01925820256776034 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.004992867332382311 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 11.3 | | std | 8.9 | | cv | 0.788 | | sampleLengths | | 0 | 23 | | 1 | 39 | | 2 | 9 | | 3 | 2 | | 4 | 1 | | 5 | 1 | | 6 | 3 | | 7 | 26 | | 8 | 28 | | 9 | 1 | | 10 | 1 | | 11 | 4 | | 12 | 29 | | 13 | 13 | | 14 | 10 | | 15 | 21 | | 16 | 4 | | 17 | 9 | | 18 | 33 | | 19 | 17 | | 20 | 12 | | 21 | 19 | | 22 | 6 | | 23 | 18 | | 24 | 9 | | 25 | 12 | | 26 | 18 | | 27 | 6 | | 28 | 14 | | 29 | 8 | | 30 | 18 | | 31 | 17 | | 32 | 13 | | 33 | 17 | | 34 | 14 | | 35 | 10 | | 36 | 20 | | 37 | 19 | | 38 | 3 | | 39 | 20 | | 40 | 13 | | 41 | 6 | | 42 | 4 | | 43 | 4 | | 44 | 8 | | 45 | 7 | | 46 | 15 | | 47 | 6 | | 48 | 15 | | 49 | 4 |
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| 46.67% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.35555555555555557 | | totalSentences | 135 | | uniqueOpeners | 48 | |
| 62.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 107 | | matches | | 0 | "Dark curly hair." | | 1 | "Then he turned his back" |
| | ratio | 0.019 | |
| 77.94% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 107 | | matches | | 0 | "She'd tracked this particular thread" | | 1 | "He'll be moving product.*" | | 2 | "She'd staked out the alley" | | 3 | "He'd spotted her almost immediately—good" | | 4 | "She recognized the location." | | 5 | "She hit the button on" | | 6 | "She could hear his footsteps," | | 7 | "She followed, her shoes crunching" | | 8 | "She was alone in the" | | 9 | "It was old, painted black," | | 10 | "Her light revealed no handle," | | 11 | "They didn't continue past." | | 12 | "They didn't double back." | | 13 | "She pulled her hand back," | | 14 | "She picked it up." | | 15 | "It was carved from bone," | | 16 | "She'd heard rumors of these" | | 17 | "She thought of her partner," | | 18 | "They'd found his jacket three" | | 19 | "She hadn't touched it." |
| | ratio | 0.355 | |
| 48.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 107 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn moved through" | | 2 | "Quinn's jaw tightened." | | 3 | "She'd tracked this particular thread" | | 4 | "Tonight, she'd finally caught a" | | 5 | "He'll be moving product.*" | | 6 | "She'd staked out the alley" | | 7 | "He'd spotted her almost immediately—good" | | 8 | "Quinn's hand brushed her holster" | | 9 | "The man was gaining, his" | | 10 | "She recognized the location." | | 11 | "The old Jubilee line extension," | | 12 | "The council had sealed the" | | 13 | "The man's boots clanged on" | | 14 | "Quinn slowed at the top" | | 15 | "The SIG Sauer felt cool" | | 16 | "The stairs dropped into absolute" | | 17 | "She hit the button on" | | 18 | "The steps were rusted, the" | | 19 | "The man was down there" |
| | ratio | 0.822 | |
| 93.46% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 107 | | matches | | 0 | "Whoever he was, he'd walked" | | 1 | "Now she stood at the" |
| | ratio | 0.019 | |
| 56.65% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 58 | | technicalSentenceCount | 7 | | matches | | 0 | "She'd tracked this particular thread for three weeks, pulling on loose ends that kept leading back to Silas Kaine and his operation at The Raven's Nest." | | 1 | "The man was gaining, his longer legs eating up the distance toward a set of iron stairs that descended into darkness." | | 2 | "The tracks lay exposed, puddled with water that reflected her flashlight back at her in fractured patterns." | | 3 | "The paint was chipped, revealing wood that felt wrong—too smooth, too warm, like living skin." | | 4 | "It simply swung inward, revealing a staircase that descended into amber light—candlelight, gaslight, something older and warmer than electricity." | | 5 | "But there was a figure she did recognize, standing at a stall near the far end of the cavern, examining a row of glass jars filled with things that glowed." | | 6 | "Then he turned his back on her, and the market swallowed him into its labyrinthine depths, leaving Quinn standing alone in the amber glow of lights that burned …" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 2 | | matches | | 0 | "he said, his accent softening the word" | | 1 | "she said, her voice low" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |