| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.34% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 958 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "very" | | 2 | "slowly" |
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| 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) | |
| 68.68% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 958 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "tinged" | | 1 | "flickered" | | 2 | "resonated" | | 3 | "pulse" | | 4 | "navigate" | | 5 | "weight" |
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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 | 57 | | matches | (empty) | |
| 92.73% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 57 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 60 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 965 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 941 | | uniqueNames | 15 | | maxNameDensity | 0.64 | | worstName | "Harlow" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Harlow" | | discoveredNames | | Camden | 2 | | High | 1 | | Street | 2 | | Quinn | 1 | | Raven | 2 | | Nest | 2 | | Morris | 1 | | Inverness | 1 | | TfL | 1 | | Harlow | 6 | | Veil | 1 | | Market | 2 | | Saint | 1 | | Christopher | 1 | | Sevillian | 2 |
| | persons | | 0 | "Quinn" | | 1 | "Raven" | | 2 | "Morris" | | 3 | "Harlow" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Sevillian" |
| | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Inverness" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | 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 | 965 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 60 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 33.28 | | std | 23.4 | | cv | 0.703 | | sampleLengths | | 0 | 56 | | 1 | 45 | | 2 | 3 | | 3 | 66 | | 4 | 67 | | 5 | 35 | | 6 | 52 | | 7 | 12 | | 8 | 8 | | 9 | 64 | | 10 | 3 | | 11 | 69 | | 12 | 25 | | 13 | 19 | | 14 | 10 | | 15 | 51 | | 16 | 59 | | 17 | 7 | | 18 | 2 | | 19 | 20 | | 20 | 61 | | 21 | 24 | | 22 | 15 | | 23 | 33 | | 24 | 52 | | 25 | 67 | | 26 | 15 | | 27 | 11 | | 28 | 14 |
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| 80.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 57 | | matches | | 0 | "was deserted" | | 1 | "been redacted" | | 2 | "being spoken" | | 3 | "been taught" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 141 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 1 | | flaggedSentences | 10 | | totalSentences | 60 | | ratio | 0.167 | | matches | | 0 | "She'd been watching him for three nights — the courier who slipped packages into the Raven's Nest after closing, who left through the fire exit with his collar up and his hands empty." | | 1 | "Her leather watch dug into her wrist as she raised her arm to check the time — 11:47." | | 2 | "He was fast, and he knew the terrain; she heard him kick a milk crate out of his path and heard it clatter against a recycling bin." | | 3 | "The station sign above her read MORNTOWN — a name she'd never seen on any TfL map, the letters faded under decades of grime, a green-tinged glow leaking from somewhere below." | | 4 | "The tunnel opened into a cavern that the tracks had never touched — a vaulted brick chamber lined with tarpaulin stalls and bare bulbs strung on cables." | | 5 | "He looked past her, to the crowd, and something in his expression shifted — a slow widening of the eyes that made the hair on her arms lift." | | 6 | "The courier's grey hood flickered at the far end of the chamber, beside a staircase that spiralled down past a wall of old maps and black-and-white photographs — she recognised the Raven's Nest décor bleeding down here like roots." | | 7 | "Voices carried through the gap — low, urgent, a man with a Sevillian accent speaking fast, and another voice she didn't recognise counting slowly in a language that had no business being spoken in Camden." | | 8 | "She pressed her ear to the wood and heard the Sevillian say, \"—not here, not tonight, she's following and you know what she is.\"" | | 9 | "The heavy man with the ledger stood at the mouth of the passage, and behind him three others — one carrying a crate that rattled with glass, another with hands stained black to the wrist." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 746 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.01742627345844504 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002680965147453083 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 60 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 60 | | mean | 16.08 | | std | 10.58 | | cv | 0.658 | | sampleLengths | | 0 | 20 | | 1 | 36 | | 2 | 33 | | 3 | 6 | | 4 | 6 | | 5 | 3 | | 6 | 26 | | 7 | 2 | | 8 | 18 | | 9 | 20 | | 10 | 8 | | 11 | 27 | | 12 | 7 | | 13 | 25 | | 14 | 16 | | 15 | 19 | | 16 | 4 | | 17 | 31 | | 18 | 17 | | 19 | 4 | | 20 | 8 | | 21 | 8 | | 22 | 27 | | 23 | 13 | | 24 | 24 | | 25 | 3 | | 26 | 27 | | 27 | 22 | | 28 | 20 | | 29 | 3 | | 30 | 22 | | 31 | 12 | | 32 | 7 | | 33 | 10 | | 34 | 4 | | 35 | 28 | | 36 | 19 | | 37 | 39 | | 38 | 20 | | 39 | 4 | | 40 | 3 | | 41 | 2 | | 42 | 20 | | 43 | 4 | | 44 | 11 | | 45 | 11 | | 46 | 35 | | 47 | 24 | | 48 | 15 | | 49 | 10 |
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| 48.33% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.35 | | totalSentences | 60 | | uniqueOpeners | 21 | |
| 59.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 56 | | matches | | | ratio | 0.018 | |
| 84.29% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 19 | | totalSentences | 56 | | matches | | 0 | "She'd been watching him for" | | 1 | "Her leather watch dug into" | | 2 | "He was fast, and he" | | 3 | "She cleared the crate in" | | 4 | "He burst out onto Inverness" | | 5 | "She keyed her radio." | | 6 | "She took the stairs three" | | 7 | "She'd heard the name in" | | 8 | "he said, flat as a" | | 9 | "He looked past her, to" | | 10 | "She unholstered her sidearm and" | | 11 | "He glanced back at her," | | 12 | "He went through a doorway" | | 13 | "Her fingers found the seam" | | 14 | "She pressed her ear to" | | 15 | "She straightened, her pulse loud" | | 16 | "She looked at the shelf" | | 17 | "She looked at the passage" | | 18 | "Her radio crackled once, a" |
| | ratio | 0.339 | |
| 22.50% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 56 | | matches | | 0 | "The rain came down in" | | 1 | "Harlow Quinn hit the corner" | | 2 | "She'd been watching him for" | | 3 | "Tonight the package had stayed" | | 4 | "Tonight he'd looked straight at" | | 5 | "The hood turned, and she" | | 6 | "Her leather watch dug into" | | 7 | "The full moon hung behind" | | 8 | "The alley stank of bins" | | 9 | "He was fast, and he" | | 10 | "She cleared the crate in" | | 11 | "He burst out onto Inverness" | | 12 | "Harlow gripped the handrail." | | 13 | "The station sign above her" | | 14 | "The ticket hall yawned dark," | | 15 | "She keyed her radio." | | 16 | "Nothing but static, a wet" | | 17 | "She took the stairs three" | | 18 | "The platform was deserted save" | | 19 | "The woman's eyes tracked Harlow's" |
| | ratio | 0.875 | |
| 89.29% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 56 | | matches | | 0 | "By the time she reached" |
| | ratio | 0.018 | |
| 3.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 7 | | matches | | 0 | "Market stalls jostled for space: bottles of luminous liquid, racks of yellowed teeth, stacks of paper that rearranged themselves as she watched." | | 1 | "He looked past her, to the crowd, and something in his expression shifted — a slow widening of the eyes that made the hair on her arms lift." | | 2 | "The courier's grey hood flickered at the far end of the chamber, beside a staircase that spiralled down past a wall of old maps and black-and-white photographs …" | | 3 | "He went through a doorway and a bookshelf swung shut behind him with a click that resonated through the brick." | | 4 | "Voices carried through the gap — low, urgent, a man with a Sevillian accent speaking fast, and another voice she didn't recognise counting slowly in a language …" | | 5 | "The heavy man with the ledger stood at the mouth of the passage, and behind him three others — one carrying a crate that rattled with glass, another with hands …" | | 6 | "She looked at the shelf seam, at the thin line of light leaking through the books, at the staircase below that spiralled into rooms where people spoke her dead …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.333 | | effectiveRatio | 0.333 | |