| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 96.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1519 | | 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) | |
| 37.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1519 | | totalAiIsms | 19 | | found | | 0 | | word | "practiced ease" | | count | 1 |
| | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | |
| | highlights | | 0 | "practiced ease" | | 1 | "footsteps" | | 2 | "echoing" | | 3 | "footfall" | | 4 | "traced" | | 5 | "glint" | | 6 | "silence" | | 7 | "whisper" | | 8 | "echoed" | | 9 | "flickered" | | 10 | "electric" | | 11 | "pulsed" | | 12 | "wavered" | | 13 | "glinting" |
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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 | 139 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 4 | | hedgeCount | 0 | | narrationSentences | 139 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1498 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1483 | | uniqueNames | 13 | | maxNameDensity | 0.74 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 11 | | Soho | 1 | | Raven | 1 | | Nest | 1 | | Silas | 1 | | Morris | 5 | | Tube | 1 | | Camden | 1 | | Road | 1 | | Station | 1 | | London | 2 | | Three | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Silas" | | 4 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Camden" | | 2 | "Road" | | 3 | "Station" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 94.44% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 90 | | glossingSentenceCount | 2 | | matches | | 0 | "quite close" | | 1 | "quite make out, in languages she didn't recognize" |
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| 66.49% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.335 | | wordCount | 1498 | | matches | | 0 | "not the usual tags and crude drawings, but symbols" | | 1 | "not the steady glow of electric bulbs, but something" |
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| 95.74% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 141 | | matches | | 0 | "given that Silas kept that door" | | 1 | "drawn that symbol" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 31.21 | | std | 18.53 | | cv | 0.594 | | sampleLengths | | 0 | 63 | | 1 | 44 | | 2 | 31 | | 3 | 18 | | 4 | 9 | | 5 | 67 | | 6 | 64 | | 7 | 51 | | 8 | 42 | | 9 | 50 | | 10 | 51 | | 11 | 16 | | 12 | 59 | | 13 | 10 | | 14 | 11 | | 15 | 32 | | 16 | 2 | | 17 | 60 | | 18 | 38 | | 19 | 46 | | 20 | 5 | | 21 | 42 | | 22 | 25 | | 23 | 43 | | 24 | 4 | | 25 | 48 | | 26 | 52 | | 27 | 24 | | 28 | 28 | | 29 | 39 | | 30 | 36 | | 31 | 43 | | 32 | 17 | | 33 | 43 | | 34 | 28 | | 35 | 11 | | 36 | 13 | | 37 | 6 | | 38 | 28 | | 39 | 41 | | 40 | 17 | | 41 | 45 | | 42 | 37 | | 43 | 5 | | 44 | 6 | | 45 | 20 | | 46 | 24 | | 47 | 4 |
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| 87.59% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 139 | | matches | | 0 | "was cordoned" | | 1 | "been pried" | | 2 | "was obscured" | | 3 | "been sealed" | | 4 | "been made" | | 5 | "was soaked" | | 6 | "been scrubbed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 248 | | matches | | 0 | "was running" | | 1 | "was disappearing" | | 2 | "wasn't turning" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 12 | | totalSentences | 141 | | ratio | 0.085 | | matches | | 0 | "The man she'd been following—a reedy figure in a dark coat who moved with the practiced ease of someone who knew how to disappear—had spotted her." | | 1 | "The man had been leaving the Raven's Nest through a side entrance when she'd caught sight of him—something that shouldn't have been possible, given that Silas kept that door alarmed." | | 2 | "A sign overhead—rusty and bullet-holed—proclaimed this as Camden Road Station, closed since the fifties." | | 3 | "And now this suspect—this lead—was disappearing into a part of London that every whisper on the force told her to avoid." | | 4 | "Her torch picked out graffiti on the walls—not the usual tags and crude drawings, but symbols that made her eyes itch if she looked at them too long." | | 5 | "Beyond it, light flickered—not the steady glow of electric bulbs, but something that pulsed and wavered like firelight." | | 6 | "The memory rose unbidden—his body in the morgue, the look on the coroner's face when she'd asked for cause of death." | | 7 | "She thought about the suspect—about the flash of something small in his hand." | | 8 | "Her heart beat steady and slow against her ribs—military training, keeping her calm when every instinct screamed at her to turn back." | | 9 | "The air tasted wrong—thick with scents she couldn't name, sweet and sour and something underneath that made her think of burning leaves." | | 10 | "The symbol, the location, the way the evidence had been scrubbed from his case file—it all pointed here, to this threshold between the London she knew and something else entirely." | | 11 | "Her torch beam cut through the darkness, illuminating the tracks ahead—rusted and warped, leading deeper into the earth." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1504 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.02526595744680851 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.004654255319148936 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 10.62 | | std | 7.62 | | cv | 0.717 | | sampleLengths | | 0 | 16 | | 1 | 25 | | 2 | 4 | | 3 | 10 | | 4 | 8 | | 5 | 26 | | 6 | 4 | | 7 | 14 | | 8 | 10 | | 9 | 3 | | 10 | 18 | | 11 | 4 | | 12 | 14 | | 13 | 9 | | 14 | 15 | | 15 | 19 | | 16 | 3 | | 17 | 30 | | 18 | 15 | | 19 | 19 | | 20 | 8 | | 21 | 5 | | 22 | 17 | | 23 | 23 | | 24 | 18 | | 25 | 10 | | 26 | 4 | | 27 | 19 | | 28 | 3 | | 29 | 2 | | 30 | 14 | | 31 | 8 | | 32 | 9 | | 33 | 14 | | 34 | 4 | | 35 | 2 | | 36 | 13 | | 37 | 13 | | 38 | 4 | | 39 | 1 | | 40 | 27 | | 41 | 6 | | 42 | 5 | | 43 | 11 | | 44 | 3 | | 45 | 6 | | 46 | 9 | | 47 | 3 | | 48 | 17 | | 49 | 21 |
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| 63.12% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.425531914893617 | | totalSentences | 141 | | uniqueOpeners | 60 | |
| 81.97% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 122 | | matches | | 0 | "Of course he had." | | 1 | "Of course not." | | 2 | "Just the drip of water" |
| | ratio | 0.025 | |
| 92.13% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 39 | | totalSentences | 122 | | matches | | 0 | "She checked the worn leather" | | 1 | "He was running now." | | 2 | "She heard the splash of" | | 3 | "Her boots struck the cobblestones" | | 4 | "She didn't care." | | 5 | "She'd walked them a thousand" | | 6 | "She emerged onto a side" | | 7 | "His face was obscured by" | | 8 | "He ducked through the gap" | | 9 | "She knew the history." | | 10 | "She crouched near the gap" | | 11 | "She'd found the sketch in" | | 12 | "Her jaw tightened." | | 13 | "She pulled out her phone." | | 14 | "Her voice echoed down the" | | 15 | "Her torch picked out graffiti" | | 16 | "She kept her gaze fixed" | | 17 | "She moved forward, tracking the" | | 18 | "They led toward the tunnel" | | 19 | "She heard voices." |
| | ratio | 0.32 | |
| 99.34% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 88 | | totalSentences | 122 | | matches | | 0 | "Detective Harlow Quinn pressed her" | | 1 | "The man she'd been following—a" | | 2 | "She checked the worn leather" | | 3 | "Quarter past midnight." | | 4 | "The streets of Soho had" | | 5 | "He was running now." | | 6 | "She heard the splash of" | | 7 | "Quinn pushed off from the" | | 8 | "Her boots struck the cobblestones" | | 9 | "The salt-and-pepper crop of her" | | 10 | "She didn't care." | | 11 | "The man had been leaving" | | 12 | "The pursuit cut left down" | | 13 | "Quinn's torch beam caught the" | | 14 | "The suspect was fast, she'd" | | 15 | "She'd walked them a thousand" | | 16 | "She emerged onto a side" | | 17 | "The entrance was cordoned off" | | 18 | "Boards covered the stairs, but" | | 19 | "The suspect glanced back." |
| | ratio | 0.721 | |
| 40.98% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 122 | | matches | | 0 | "As if a healthy thirty-eight-year-old" |
| | ratio | 0.008 | |
| 46.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 67 | | technicalSentenceCount | 9 | | matches | | 0 | "The man she'd been following—a reedy figure in a dark coat who moved with the practiced ease of someone who knew how to disappear—had spotted her." | | 1 | "The man had been leaving the Raven's Nest through a side entrance when she'd caught sight of him—something that shouldn't have been possible, given that Silas k…" | | 2 | "Old advertisements peeled from the tiled walls, promoting products that hadn't existed in half a century." | | 3 | "They led toward the tunnel mouth, past a turnstile that had been bent outward with considerable force." | | 4 | "He'd gone in alone, against protocol, because he'd trusted his instincts more than he'd trusted the procedures that kept them safe." | | 5 | "She could almost see Morris standing beside her, that crooked smile he got when he was about to do something stupid." | | 6 | "He'd left her alone with nothing but questions and a sharp jaw that people said made her look severe and a military bearing that kept everyone at arm's length." | | 7 | "She'd heard rumours, whispers from informants who'd gone pale when she'd pressed for details." | | 8 | "Wait for uniformed officers who would arrive too late, find nothing, and file a report that would join the others in the growing stack of unresolved cases on he…" |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "he'd, but his hands had shaken as he'd signed the certificate" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 5 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 1 | | effectiveRatio | 0.4 | |