| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.147 | | leniency | 0.294 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1368 | | 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) | |
| 56.14% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1368 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "shattered" | | 1 | "familiar" | | 2 | "weight" | | 3 | "silence" | | 4 | "flicked" | | 5 | "measured" | | 6 | "whisper" | | 7 | "unspoken" |
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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 | 63 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1368 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 20 | | wordCount | 777 | | uniqueNames | 11 | | maxNameDensity | 0.9 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 1 | | Carter | 1 | | Golden | 1 | | Empress | 1 | | Prague | 2 | | Aurora | 3 | | Eva | 1 | | Cardiff | 1 | | Silas | 7 |
| | persons | | 0 | "Raven" | | 1 | "Carter" | | 2 | "Aurora" | | 3 | "Eva" | | 4 | "Silas" |
| | places | | 0 | "Soho" | | 1 | "Golden" | | 2 | "Prague" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | 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 | 1368 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 92 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 33.37 | | std | 21.82 | | cv | 0.654 | | sampleLengths | | 0 | 45 | | 1 | 4 | | 2 | 63 | | 3 | 62 | | 4 | 9 | | 5 | 54 | | 6 | 1 | | 7 | 13 | | 8 | 67 | | 9 | 10 | | 10 | 38 | | 11 | 32 | | 12 | 9 | | 13 | 59 | | 14 | 42 | | 15 | 4 | | 16 | 44 | | 17 | 7 | | 18 | 26 | | 19 | 36 | | 20 | 37 | | 21 | 40 | | 22 | 45 | | 23 | 6 | | 24 | 51 | | 25 | 57 | | 26 | 4 | | 27 | 45 | | 28 | 15 | | 29 | 34 | | 30 | 79 | | 31 | 35 | | 32 | 7 | | 33 | 5 | | 34 | 51 | | 35 | 23 | | 36 | 22 | | 37 | 73 | | 38 | 29 | | 39 | 26 | | 40 | 59 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 63 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 138 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 92 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 786 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 22 | | adverbRatio | 0.027989821882951654 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.001272264631043257 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 14.87 | | std | 10.59 | | cv | 0.712 | | sampleLengths | | 0 | 19 | | 1 | 26 | | 2 | 4 | | 3 | 12 | | 4 | 15 | | 5 | 5 | | 6 | 2 | | 7 | 6 | | 8 | 23 | | 9 | 13 | | 10 | 11 | | 11 | 25 | | 12 | 13 | | 13 | 9 | | 14 | 11 | | 15 | 9 | | 16 | 21 | | 17 | 13 | | 18 | 1 | | 19 | 4 | | 20 | 9 | | 21 | 8 | | 22 | 8 | | 23 | 9 | | 24 | 22 | | 25 | 20 | | 26 | 10 | | 27 | 24 | | 28 | 14 | | 29 | 20 | | 30 | 4 | | 31 | 8 | | 32 | 9 | | 33 | 2 | | 34 | 20 | | 35 | 15 | | 36 | 13 | | 37 | 6 | | 38 | 3 | | 39 | 12 | | 40 | 30 | | 41 | 4 | | 42 | 15 | | 43 | 29 | | 44 | 7 | | 45 | 26 | | 46 | 7 | | 47 | 6 | | 48 | 23 | | 49 | 37 |
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| 85.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5217391304347826 | | totalSentences | 92 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 60 | | matches | | 0 | "Bright blue eyes tracked the" | | 1 | "Just the one word." |
| | ratio | 0.033 | |
| 73.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 60 | | matches | | 0 | "They crashed into a table." | | 1 | "It bounced off the green" | | 2 | "She still wore her delivery" | | 3 | "He twisted the drunk's wrist" | | 4 | "He said it like a" | | 5 | "She remember those eyes younger," | | 6 | "He limped behind the bar," | | 7 | "She took the drink, crescent" | | 8 | "She knew what lived behind" | | 9 | "He nodded at the embroidered" | | 10 | "He tapped the bar twice" | | 11 | "She set the glass down" | | 12 | "He refilled her glass without" | | 13 | "He turned the signet ring" | | 14 | "She leaned forward, cool voice" | | 15 | "She scar on her wrist" | | 16 | "She wondered if his knee" | | 17 | "He studied her, quiet authority" | | 18 | "She felt the old pull," | | 19 | "He set both hands flat" |
| | ratio | 0.367 | |
| 35.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 51 | | totalSentences | 60 | | matches | | 0 | "The bottle shattered against the" | | 1 | "Silas vaulted the bar counter" | | 2 | "The drunk snarled something thick" | | 3 | "Silas sidestepped it, planted his" | | 4 | "They crashed into a table." | | 5 | "A pint glass rolled and" | | 6 | "Regulars pressed against the walls," | | 7 | "Aurora Carter kicked the door" | | 8 | "It bounced off the green" | | 9 | "She still wore her delivery" | | 10 | "He twisted the drunk's wrist" | | 11 | "Silas rose slow, brushing dust" | | 12 | "The limp showed itself proper" | | 13 | "He said it like a" | | 14 | "The drunk groaned and fumbled" | | 15 | "Silas let him go, eyes" | | 16 | "She remember those eyes younger," | | 17 | "He limped behind the bar," | | 18 | "She took the drink, crescent" | | 19 | "The whiskey burned clean." |
| | ratio | 0.85 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 60 | | matches | (empty) | | ratio | 0 | |
| 79.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 3 | | matches | | 0 | "The bottle shattered against the far wall, glass shards spraying across the old maps that lined The Raven's Nest." | | 1 | "Regulars pressed against the walls, pints still in hand, watching the show with the detachment of people who'd seen worse in Soho basements." | | 2 | "She scar on her wrist itched under the fabric, memory of the childhood fall that had nothing to do with fists and everything to do with running too fast from no…" |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 34 | | tagDensity | 0.029 | | leniency | 0.059 | | rawRatio | 0 | | effectiveRatio | 0 | |