| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 32 | | adverbTagCount | 1 | | adverbTags | | 0 | "legal jargon had once [once]" |
| | dialogueSentences | 86 | | tagDensity | 0.372 | | leniency | 0.744 | | rawRatio | 0.031 | | effectiveRatio | 0.023 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1990 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 59.80% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1990 | | totalAiIsms | 16 | | found | | | highlights | | 0 | "tracing" | | 1 | "reminder" | | 2 | "flicked" | | 3 | "calculated" | | 4 | "silence" | | 5 | "scanning" | | 6 | "scanned" | | 7 | "trembled" | | 8 | "navigate" | | 9 | "weight" | | 10 | "throbbed" | | 11 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "weight of words/silence" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 91 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 91 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 150 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 60 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1976 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 20 | | unquotedAttributions | 0 | | matches | (empty) | |
| 96.92% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 942 | | uniqueNames | 17 | | maxNameDensity | 1.06 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 3 | | Carter | 1 | | Bond | 1 | | Street | 1 | | London | 1 | | Berlin | 1 | | Wall | 1 | | Aurora | 10 | | Guinness | 1 | | Spymaster | 1 | | Silas | 4 | | Yu-Fei | 3 | | Congo | 1 | | Prague | 1 | | Wrexham | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Wall" | | 4 | "Aurora" | | 5 | "Spymaster" | | 6 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Bond" | | 2 | "Street" | | 3 | "London" | | 4 | "Berlin" | | 5 | "Congo" | | 6 | "Prague" | | 7 | "Wrexham" |
| | globalScore | 0.969 | | windowScore | 1 | |
| 68.03% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 2 | | matches | | 0 | "felt like a language" | | 1 | "as if reading minds" |
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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 | 1976 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 150 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 29.94 | | std | 22.68 | | cv | 0.758 | | sampleLengths | | 0 | 136 | | 1 | 70 | | 2 | 58 | | 3 | 80 | | 4 | 42 | | 5 | 34 | | 6 | 57 | | 7 | 57 | | 8 | 22 | | 9 | 29 | | 10 | 32 | | 11 | 35 | | 12 | 10 | | 13 | 13 | | 14 | 64 | | 15 | 31 | | 16 | 47 | | 17 | 20 | | 18 | 21 | | 19 | 1 | | 20 | 23 | | 21 | 47 | | 22 | 13 | | 23 | 38 | | 24 | 69 | | 25 | 15 | | 26 | 7 | | 27 | 18 | | 28 | 22 | | 29 | 16 | | 30 | 24 | | 31 | 25 | | 32 | 1 | | 33 | 18 | | 34 | 32 | | 35 | 36 | | 36 | 19 | | 37 | 29 | | 38 | 38 | | 39 | 14 | | 40 | 13 | | 41 | 16 | | 42 | 19 | | 43 | 17 | | 44 | 70 | | 45 | 21 | | 46 | 21 | | 47 | 11 | | 48 | 50 | | 49 | 37 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 91 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 163 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 150 | | ratio | 0.053 | | matches | | 0 | "The scar on her wrist—a paper-thin crescent moon—itched under the thin fabric of her shirt, a reminder of childhood kitchen experiments gone awry." | | 1 | "There was no mistaking that gait—even now, it felt like a language." | | 2 | "“Silas Blackwood. Should’ve known the only reason my deliveries don’t end up in the bin is that you’ve got a system to track them.” She gestured to the photographs on the wall—black-and-white images of Soho’s forgotten years, maps of Berlin after the Wall collapsed, a faded polaroid of the bar’s wooden foundation bearing the initials SI+BW, 1978." | | 3 | "“I’m not closing tonight.” Her glance flicked to the bar door—the way it led to his secret room, the bookshelf entrance she avoided." | | 4 | "The ring caught her eye—its surface unmarred, unlike her wrist." | | 5 | "The bartender set down a fresh glass for Aurora—whiskey, as if reading minds." | | 6 | "The photographs followed her as she passed—more ghosts in frames, a 1972 photo of Silas in the Congo." | | 7 | "She studied the map—inked lines over Prague, Soho, a faint red dot near Wrexham." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 918 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.027233115468409588 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006535947712418301 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 150 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 150 | | mean | 13.17 | | std | 9.56 | | cv | 0.725 | | sampleLengths | | 0 | 27 | | 1 | 19 | | 2 | 23 | | 3 | 23 | | 4 | 23 | | 5 | 9 | | 6 | 10 | | 7 | 2 | | 8 | 10 | | 9 | 11 | | 10 | 12 | | 11 | 37 | | 12 | 12 | | 13 | 24 | | 14 | 14 | | 15 | 8 | | 16 | 8 | | 17 | 57 | | 18 | 10 | | 19 | 5 | | 20 | 14 | | 21 | 19 | | 22 | 9 | | 23 | 23 | | 24 | 11 | | 25 | 11 | | 26 | 9 | | 27 | 35 | | 28 | 2 | | 29 | 2 | | 30 | 25 | | 31 | 11 | | 32 | 6 | | 33 | 13 | | 34 | 6 | | 35 | 16 | | 36 | 14 | | 37 | 15 | | 38 | 23 | | 39 | 9 | | 40 | 24 | | 41 | 11 | | 42 | 3 | | 43 | 7 | | 44 | 9 | | 45 | 4 | | 46 | 7 | | 47 | 5 | | 48 | 2 | | 49 | 36 |
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| 48.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.30666666666666664 | | totalSentences | 150 | | uniqueOpeners | 46 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Somewhere behind him, a jukebox" | | 1 | "Just a young operative with" |
| | ratio | 0.024 | |
| 10.24% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 82 | | matches | | 0 | "She’d just finished delivering a" | | 1 | "She flexed her hand, watching" | | 2 | "He’d stood the same way" | | 3 | "His auburn eyebrows lifted over" | | 4 | "She gestured to the photographs" | | 5 | "She preferred the shifting present." | | 6 | "His laugh held the rasp" | | 7 | "He tilted his head at" | | 8 | "Her glance flicked to the" | | 9 | "He paused, tapping the ring" | | 10 | "Her father’s legal jargon had" | | 11 | "She set her hand flat" | | 12 | "He nodded to the bartender" | | 13 | "He didn’t smile." | | 14 | "Her fingers curled into her" | | 15 | "He tapped the rim of" | | 16 | "She leaned forward but stayed" | | 17 | "She let the question hang," | | 18 | "His injury had been a" | | 19 | "He exhaled through his nose." |
| | ratio | 0.524 | |
| 8.78% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 74 | | totalSentences | 82 | | matches | | 0 | "The Raven’s Nest hummed with" | | 1 | "Aurora Carter leaned against the" | | 2 | "She’d just finished delivering a" | | 3 | "Yu-Fei had once insisted on" | | 4 | "The scar on her wrist—a" | | 5 | "She flexed her hand, watching" | | 6 | "The man knew her name," | | 7 | "A creak of the front" | | 8 | "The limp, slow shuffle of" | | 9 | "He’d stood the same way" | | 10 | "the older man said, his" | | 11 | "His auburn eyebrows lifted over" | | 12 | "The scarlet tassel of his" | | 13 | "Aurora’s smile was a knife" | | 14 | "She gestured to the photographs" | | 15 | "The details of his life" | | 16 | "She preferred the shifting present." | | 17 | "His laugh held the rasp" | | 18 | "He tilted his head at" | | 19 | "Her glance flicked to the" |
| | ratio | 0.902 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 15.31% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 5 | | matches | | 0 | "He’d stood the same way at her school’s talent show in 1999, one hand gripping a cane that didn’t match his tailored MI6 uniform, the other propping open the em…" | | 1 | "His laugh held the rasp of a man who’d smoked his way through continents." | | 2 | "Aurora’s eyes followed the path of the bartender, who moved with practiced indifference, wiping glasses like she could clean ghosts." | | 3 | "The secret room lay behind a bookshelf of first editions (real ones, according to Yu-Fei, who’d once asked)." | | 4 | "Outside, the neon flickered, green and uncertain, as if the city itself was waiting for her to choose." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 32 | | uselessAdditionCount | 4 | | matches | | 0 | "the older man said, his voice a worn leather saddle" | | 1 | "But her gaze lingered, the foam collapsing like a secret" | | 2 | "The words came out, but her knuckles whitened on the whiskey" | | 3 | "She raised, the amber liquid catching the neon" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "Silas continued (continue)" | | 1 | "he added (add)" |
| | dialogueSentences | 86 | | tagDensity | 0.058 | | leniency | 0.116 | | rawRatio | 0.4 | | effectiveRatio | 0.047 | |