| 46.15% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 3 | | adverbTags | | 0 | "Julian’s voice cracked slightly [slightly]" | | 1 | "Rory answered quietly [quietly]" | | 2 | "He gestured vaguely [vaguely]" |
| | dialogueSentences | 39 | | tagDensity | 0.256 | | leniency | 0.513 | | rawRatio | 0.3 | | effectiveRatio | 0.154 | |
| 86.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1466 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | |
| 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) | |
| 55.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1466 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "crystal" | | 1 | "gleaming" | | 2 | "gloom" | | 3 | "scanning" | | 4 | "silence" | | 5 | "measured" | | 6 | "resonance" | | 7 | "chill" | | 8 | "weight" | | 9 | "lilt" | | 10 | "traced" | | 11 | "pristine" |
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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 | 72 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 72 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 101 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 8 | | totalWords | 1466 | | ratio | 0.005 | | matches | | 0 | "Julian Powell, Barrister-at-Law, 4 King's Bench Walk, Temple." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 51 | | wordCount | 1125 | | uniqueNames | 24 | | maxNameDensity | 1.24 | | worstName | "Julian" | | maxWindowNameDensity | 3 | | worstWindowName | "Julian" | | discoveredNames | | Soho | 2 | | Raven | 1 | | Nest | 1 | | Blackwood | 1 | | Golden | 1 | | Empress | 1 | | Charing | 1 | | Cross | 1 | | Road | 1 | | Italian | 1 | | Cathays | 1 | | Park | 1 | | Powell | 2 | | Julian | 14 | | Silas | 5 | | London | 1 | | South | 1 | | Wales | 1 | | Rory | 9 | | Northern | 1 | | Barrister-at-Law | 1 | | King | 1 | | Bench | 1 | | Walk | 1 |
| | persons | | 0 | "Blackwood" | | 1 | "Powell" | | 2 | "Julian" | | 3 | "Silas" | | 4 | "Rory" | | 5 | "King" | | 6 | "Bench" |
| | places | | 0 | "Soho" | | 1 | "Raven" | | 2 | "Charing" | | 3 | "Cross" | | 4 | "Road" | | 5 | "Cathays" | | 6 | "Park" | | 7 | "London" | | 8 | "South" | | 9 | "Wales" |
| | globalScore | 0.878 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.682 | | wordCount | 1466 | | matches | | 0 | "not flinch, but her spine locked against the leather backrest" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 101 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 23.27 | | std | 18.96 | | cv | 0.815 | | sampleLengths | | 0 | 41 | | 1 | 49 | | 2 | 65 | | 3 | 26 | | 4 | 65 | | 5 | 7 | | 6 | 8 | | 7 | 1 | | 8 | 36 | | 9 | 40 | | 10 | 1 | | 11 | 44 | | 12 | 14 | | 13 | 6 | | 14 | 10 | | 15 | 26 | | 16 | 8 | | 17 | 37 | | 18 | 27 | | 19 | 12 | | 20 | 42 | | 21 | 20 | | 22 | 5 | | 23 | 10 | | 24 | 18 | | 25 | 12 | | 26 | 14 | | 27 | 16 | | 28 | 1 | | 29 | 22 | | 30 | 29 | | 31 | 6 | | 32 | 81 | | 33 | 33 | | 34 | 9 | | 35 | 56 | | 36 | 11 | | 37 | 9 | | 38 | 5 | | 39 | 48 | | 40 | 52 | | 41 | 6 | | 42 | 3 | | 43 | 31 | | 44 | 22 | | 45 | 39 | | 46 | 3 | | 47 | 3 | | 48 | 3 | | 49 | 49 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 72 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 173 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 101 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1134 | | adjectiveStacks | 1 | | stackExamples | | 0 | "heavy, cream-colored business" |
| | adverbCount | 22 | | adverbRatio | 0.019400352733686066 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007936507936507936 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 101 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 101 | | mean | 14.51 | | std | 9.41 | | cv | 0.648 | | sampleLengths | | 0 | 24 | | 1 | 17 | | 2 | 9 | | 3 | 28 | | 4 | 12 | | 5 | 17 | | 6 | 22 | | 7 | 26 | | 8 | 11 | | 9 | 15 | | 10 | 15 | | 11 | 28 | | 12 | 22 | | 13 | 7 | | 14 | 8 | | 15 | 1 | | 16 | 12 | | 17 | 24 | | 18 | 6 | | 19 | 34 | | 20 | 1 | | 21 | 29 | | 22 | 15 | | 23 | 14 | | 24 | 6 | | 25 | 10 | | 26 | 26 | | 27 | 8 | | 28 | 18 | | 29 | 19 | | 30 | 9 | | 31 | 18 | | 32 | 10 | | 33 | 2 | | 34 | 3 | | 35 | 39 | | 36 | 20 | | 37 | 5 | | 38 | 10 | | 39 | 18 | | 40 | 12 | | 41 | 14 | | 42 | 16 | | 43 | 1 | | 44 | 10 | | 45 | 12 | | 46 | 16 | | 47 | 13 | | 48 | 6 | | 49 | 13 |
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| 47.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.32673267326732675 | | totalSentences | 101 | | uniqueOpeners | 33 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 63.48% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 27 | | totalSentences | 69 | | matches | | 0 | "His left knee caught with" | | 1 | "Her knuckles bore the fresh" | | 2 | "She rubbed her thumb over" | | 3 | "He wore a tailored charcoal" | | 4 | "He raised his head, blinking" | | 5 | "His gaze snagged on the" | | 6 | "He moved toward the bar," | | 7 | "He stopped two stools away," | | 8 | "He laid his leather folio" | | 9 | "He set a fresh coaster" | | 10 | "He reached for a bottle" | | 11 | "he pressed, his voice dropping" | | 12 | "He searched her face for" | | 13 | "It carried no heat, only" | | 14 | "He gestured vaguely at her" | | 15 | "He reached into his overcoat" | | 16 | "He slid it across the" | | 17 | "It stopped an inch from" | | 18 | "he noted, his tone flattening," | | 19 | "It smelled of expensive stationery" |
| | ratio | 0.391 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 69 | | matches | | 0 | "Silas Blackwood limped along the" | | 1 | "His left knee caught with" | | 2 | "The silver signet ring on" | | 3 | "Rory sat on the end" | | 4 | "Her knuckles bore the fresh" | | 5 | "She rubbed her thumb over" | | 6 | "The street door swung inward" | | 7 | "A gust of wet air" | | 8 | "A man stepped onto the" | | 9 | "He wore a tailored charcoal" | | 10 | "He raised his head, blinking" | | 11 | "His gaze snagged on the" | | 12 | "The umbrella slipped two inches" | | 13 | "Rory did not flinch, but" | | 14 | "That voice belonged to drafty" | | 15 | "Julian Powell stood in the" | | 16 | "The soft-edged boy who used" | | 17 | "He moved toward the bar," | | 18 | "He stopped two stools away," | | 19 | "Rory picked up her glass," |
| | ratio | 0.957 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 99.13% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 3 | | matches | | 0 | "He raised his head, blinking against the amber gloom of the pub, scanning the yellowed nautical maps pinned to the mahogany paneling." | | 1 | "The soft-edged boy who used to spill ink across his torts notes had vanished beneath sharp jawlines, a salon fade, and the hard, sculpted polish of a junior bar…" | | 2 | "He searched her face for the girl who used to draft mock trial arguments on greasy napkins at three in the morning, the girl who could dismantle an opponent’s s…" |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 2 | | matches | | 0 | "he pressed, his voice dropping an octave, losing its crisp courtroom resonance" | | 1 | "he noted, his tone flattening, retreating behind the safety of professional courtesy" |
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| 47.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "Julian murmured (murmur)" | | 1 | "he pressed (press)" | | 2 | "Rory stated (state)" | | 3 | "he noted (note)" |
| | dialogueSentences | 39 | | tagDensity | 0.128 | | leniency | 0.256 | | rawRatio | 0.8 | | effectiveRatio | 0.205 | |