| 72.34% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 3 | | adverbTags | | 0 | "she asked suddenly [suddenly]" | | 1 | "She gestured vaguely [vaguely]" | | 2 | "she said quietly [quietly]" |
| | dialogueSentences | 47 | | tagDensity | 0.426 | | leniency | 0.851 | | rawRatio | 0.15 | | effectiveRatio | 0.128 | |
| 91.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2284 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "slowly" | | 1 | "suddenly" | | 2 | "really" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 54.03% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2284 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "silence" | | 1 | "weight" | | 2 | "scanning" | | 3 | "measured" | | 4 | "flickered" | | 5 | "tracing" | | 6 | "warmth" | | 7 | "throbbed" | | 8 | "eyebrow" | | 9 | "potential" | | 10 | "comfortable" | | 11 | "calculating" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 131 | | matches | | |
| 77.43% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 6 | | narrationSentences | 131 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 156 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 65 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2276 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1596 | | uniqueNames | 25 | | maxNameDensity | 0.5 | | worstName | "Silas" | | maxWindowNameDensity | 1 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Tuesday | 1 | | October | 1 | | London | 2 | | Carter | 2 | | Brick | 1 | | Lane | 1 | | Evan | 3 | | Silas | 8 | | Golden | 1 | | Empress | 1 | | Blackwood | 1 | | Prague | 2 | | Cardiff | 1 | | Eva | 3 | | Uncle | 1 | | Si | 1 | | Lagavulin | 1 | | Pembrokeshire | 1 | | Spymaster | 1 | | Rory | 3 | | Bond | 1 | | Service | 1 | | Aurora | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Evan" | | 4 | "Silas" | | 5 | "Empress" | | 6 | "Blackwood" | | 7 | "Eva" | | 8 | "Uncle" | | 9 | "Si" | | 10 | "Rory" | | 11 | "Service" | | 12 | "Aurora" |
| | places | | 0 | "London" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Prague" | | 4 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 93.82% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 89 | | glossingSentenceCount | 2 | | matches | | 0 | "quite read" | | 1 | "looked like the girl he remembered—small" |
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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 | 2276 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 156 | | matches | | 0 | "learned that volume" | | 1 | "spoken that name" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 59 | | mean | 38.58 | | std | 30.08 | | cv | 0.78 | | sampleLengths | | 0 | 94 | | 1 | 118 | | 2 | 92 | | 3 | 22 | | 4 | 111 | | 5 | 16 | | 6 | 104 | | 7 | 3 | | 8 | 21 | | 9 | 13 | | 10 | 71 | | 11 | 17 | | 12 | 18 | | 13 | 12 | | 14 | 10 | | 15 | 62 | | 16 | 4 | | 17 | 17 | | 18 | 8 | | 19 | 49 | | 20 | 11 | | 21 | 27 | | 22 | 30 | | 23 | 3 | | 24 | 13 | | 25 | 27 | | 26 | 57 | | 27 | 9 | | 28 | 56 | | 29 | 59 | | 30 | 7 | | 31 | 95 | | 32 | 21 | | 33 | 7 | | 34 | 20 | | 35 | 37 | | 36 | 46 | | 37 | 5 | | 38 | 40 | | 39 | 77 | | 40 | 23 | | 41 | 59 | | 42 | 46 | | 43 | 54 | | 44 | 58 | | 45 | 26 | | 46 | 46 | | 47 | 67 | | 48 | 37 | | 49 | 48 |
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| 94.55% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 131 | | matches | | 0 | "was posted" | | 1 | "been planed" | | 2 | "been redacted" | | 3 | "being seen" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 275 | | matches | | 0 | "was recalculating" | | 1 | "was tracing" | | 2 | "was watching" |
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| 32.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 156 | | ratio | 0.038 | | matches | | 0 | "Her straight black hair had grown out again; it now brushed the collar of the battered leather jacket she’d bought in a charity shop off Brick Lane." | | 1 | "The small crescent scar on her left wrist caught the lamplight whenever she lifted her glass—pale against her skin, a souvenir from the summer she was nine and had tried to climb the neighbour’s wrought-iron fence after a football." | | 2 | "He expected to see one of the usual early crowd—perhaps the ex-diplomat who nursed a single whisky for three hours, or the young hacker who paid in cryptocurrency and never gave his real name." | | 3 | "The leather jacket was new to him, but the way she held herself—weight balanced, eyes scanning exits—was not." | | 4 | "The words rose in his throat—sharp, authoritative, the tone of the Spymaster who had once convinced presidents to change policy with nothing but a raised eyebrow." | | 5 | "For a moment she looked like the girl he remembered—small shoulders, fierce eyes, the kind of courage that didn’t need an audience." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1610 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 57 | | adverbRatio | 0.03540372670807453 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.009937888198757764 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 156 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 156 | | mean | 14.59 | | std | 11.46 | | cv | 0.786 | | sampleLengths | | 0 | 26 | | 1 | 19 | | 2 | 25 | | 3 | 24 | | 4 | 21 | | 5 | 27 | | 6 | 39 | | 7 | 4 | | 8 | 4 | | 9 | 23 | | 10 | 17 | | 11 | 28 | | 12 | 23 | | 13 | 24 | | 14 | 22 | | 15 | 15 | | 16 | 17 | | 17 | 25 | | 18 | 20 | | 19 | 34 | | 20 | 16 | | 21 | 6 | | 22 | 31 | | 23 | 1 | | 24 | 14 | | 25 | 19 | | 26 | 33 | | 27 | 3 | | 28 | 20 | | 29 | 1 | | 30 | 13 | | 31 | 12 | | 32 | 8 | | 33 | 14 | | 34 | 12 | | 35 | 25 | | 36 | 5 | | 37 | 7 | | 38 | 5 | | 39 | 14 | | 40 | 4 | | 41 | 12 | | 42 | 5 | | 43 | 5 | | 44 | 28 | | 45 | 15 | | 46 | 19 | | 47 | 4 | | 48 | 11 | | 49 | 6 |
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| 46.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3269230769230769 | | totalSentences | 156 | | uniqueOpeners | 51 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 120 | | matches | | 0 | "Only a handful of patrons" | | 1 | "Instead he saw a woman" | | 2 | "Still did, some nights." | | 3 | "Instead he said," |
| | ratio | 0.033 | |
| 53.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 50 | | totalSentences | 120 | | matches | | 0 | "It was a Tuesday in" | | 1 | "Her straight black hair had" | | 2 | "She wore no makeup." | | 3 | "She rarely did anymore." | | 4 | "She had come downstairs from" | | 5 | "She was halfway through her" | | 6 | "His left knee complained as" | | 7 | "He moved with the deliberate" | | 8 | "He expected to see one" | | 9 | "He was thirty-three again, standing" | | 10 | "She looked up." | | 11 | "Her bright blue eyes widened," | | 12 | "He limped behind the bar," | | 13 | "he said, voice low" | | 14 | "It didn’t reach her eyes." | | 15 | "He poured himself two fingers" | | 16 | "She turned the glass slowly," | | 17 | "He studied her." | | 18 | "She had always been cautious," | | 19 | "He recognised the posture." |
| | ratio | 0.417 | |
| 51.67% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 120 | | matches | | 0 | "The Raven’s Nest smelled of" | | 1 | "It was a Tuesday in" | | 2 | "Aurora Carter sat at the" | | 3 | "Her straight black hair had" | | 4 | "The small crescent scar on" | | 5 | "She wore no makeup." | | 6 | "She rarely did anymore." | | 7 | "The woman who had once" | | 8 | "She had come downstairs from" | | 9 | "The flat was cheap, Silas" | | 10 | "She was halfway through her" | | 11 | "Silas Blackwood had been in" | | 12 | "His left knee complained as" | | 13 | "He moved with the deliberate" | | 14 | "The silver signet ring on" | | 15 | "He expected to see one" | | 16 | "He was thirty-three again, standing" | | 17 | "The girl who had once" | | 18 | "The girl who had written" | | 19 | "The girl who had shown" |
| | ratio | 0.817 | |
| 41.67% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 120 | | matches | | 0 | "Now that caution had calcified" |
| | ratio | 0.008 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 59 | | technicalSentenceCount | 14 | | matches | | 0 | "The Raven’s Nest smelled of wet wool, spilled ale, and the faint cedar tang of the old maps that clung to the walls like forgotten treaties." | | 1 | "Only a handful of patrons hunched over their drinks, speaking in the low, careful tones of people who had learned that volume invited trouble." | | 2 | "The woman who had once spent forty minutes perfecting a smoky eye for Evan’s friends had learned that blending in kept her alive." | | 3 | "He expected to see one of the usual early crowd—perhaps the ex-diplomat who nursed a single whisky for three hours, or the young hacker who paid in cryptocurren…" | | 4 | "The girl who had once called him Uncle Si even though they weren’t blood." | | 5 | "The girl who had shown up on his doorstep in London five years ago with a split lip, a duffel bag, and the kind of silence that told him everything Evan had don…" | | 6 | "But the intelligence was still there, bright and restless, the same quick mind that had once dismantled his chessboards in six moves while Eva cheered." | | 7 | "Silas reached for a clean glass without asking, poured her another gin, added tonic with the precise wrist flick that had once steadied his aim in six countries…" | | 8 | "The bar had gone quieter, as though the other patrons could sense history settling over the stools like dust." | | 9 | "The words rose in his throat—sharp, authoritative, the tone of the Spymaster who had once convinced presidents to change policy with nothing but a raised eyebro…" | | 10 | "The girl who had fallen asleep on his sofa watching old Bond films." | | 11 | "The girl who had cried into his shoulder the day her mother died." | | 12 | "But the green neon flickered across her face, highlighting the new hardness at the edge of her jaw, the faint line between her brows that hadn’t been there at t…" | | 13 | "For a moment she looked like the girl he remembered—small shoulders, fierce eyes, the kind of courage that didn’t need an audience." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 12 | | fancyCount | 2 | | fancyTags | | 0 | "he admitted (admit)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 47 | | tagDensity | 0.255 | | leniency | 0.511 | | rawRatio | 0.167 | | effectiveRatio | 0.085 | |