| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 96.25% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1334 | | totalAiIsmAdverbs | 1 | | 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) | |
| 58.77% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1334 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "familiar" | | 1 | "restrained" | | 2 | "scanning" | | 3 | "methodical" | | 4 | "scanned" | | 5 | "stomach" | | 6 | "traced" | | 7 | "charm" | | 8 | "whisper" | | 9 | "warmth" | | 10 | "tracing" |
| |
| 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 | 1 | | narrationSentences | 83 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 83 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 136 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1334 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 848 | | uniqueNames | 10 | | maxNameDensity | 1.18 | | worstName | "Caleb" | | maxWindowNameDensity | 3 | | worstWindowName | "Caleb" | | discoveredNames | | Raven | 1 | | Nest | 1 | | November | 1 | | Chinatown | 1 | | Prague | 1 | | Rory | 9 | | Cardiff | 1 | | Law | 1 | | Caleb | 10 | | Silas | 5 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Caleb" | | 4 | "Silas" |
| | places | | 0 | "Chinatown" | | 1 | "Prague" | | 2 | "Cardiff" |
| | globalScore | 0.91 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed starker beneath the green neon" |
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| 50.07% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.499 | | wordCount | 1334 | | matches | | 0 | "not with anger but with the friction of old guilt" | | 1 | "neither she nor" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 136 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 86 | | mean | 15.51 | | std | 20.42 | | cv | 1.316 | | sampleLengths | | 0 | 111 | | 1 | 95 | | 2 | 36 | | 3 | 68 | | 4 | 5 | | 5 | 1 | | 6 | 11 | | 7 | 1 | | 8 | 75 | | 9 | 5 | | 10 | 9 | | 11 | 5 | | 12 | 4 | | 13 | 1 | | 14 | 21 | | 15 | 4 | | 16 | 6 | | 17 | 25 | | 18 | 2 | | 19 | 23 | | 20 | 7 | | 21 | 4 | | 22 | 7 | | 23 | 12 | | 24 | 15 | | 25 | 2 | | 26 | 10 | | 27 | 14 | | 28 | 22 | | 29 | 5 | | 30 | 9 | | 31 | 17 | | 32 | 5 | | 33 | 2 | | 34 | 21 | | 35 | 4 | | 36 | 21 | | 37 | 24 | | 38 | 16 | | 39 | 8 | | 40 | 4 | | 41 | 6 | | 42 | 7 | | 43 | 13 | | 44 | 16 | | 45 | 4 | | 46 | 2 | | 47 | 13 | | 48 | 20 | | 49 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 83 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 145 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 136 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 860 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 13 | | adverbRatio | 0.015116279069767442 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.002325581395348837 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 136 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 136 | | mean | 9.81 | | std | 7.31 | | cv | 0.745 | | sampleLengths | | 0 | 12 | | 1 | 13 | | 2 | 28 | | 3 | 14 | | 4 | 8 | | 5 | 12 | | 6 | 24 | | 7 | 12 | | 8 | 16 | | 9 | 13 | | 10 | 23 | | 11 | 31 | | 12 | 8 | | 13 | 15 | | 14 | 2 | | 15 | 11 | | 16 | 3 | | 17 | 11 | | 18 | 12 | | 19 | 11 | | 20 | 8 | | 21 | 23 | | 22 | 5 | | 23 | 1 | | 24 | 5 | | 25 | 6 | | 26 | 1 | | 27 | 4 | | 28 | 22 | | 29 | 7 | | 30 | 8 | | 31 | 20 | | 32 | 14 | | 33 | 5 | | 34 | 9 | | 35 | 5 | | 36 | 4 | | 37 | 1 | | 38 | 12 | | 39 | 9 | | 40 | 4 | | 41 | 6 | | 42 | 10 | | 43 | 8 | | 44 | 7 | | 45 | 2 | | 46 | 5 | | 47 | 15 | | 48 | 3 | | 49 | 7 |
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| 38.24% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.29411764705882354 | | totalSentences | 136 | | uniqueOpeners | 40 | |
| 41.67% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 80 | | matches | | 0 | "Even his scent had changed," |
| | ratio | 0.013 | |
| 70.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 80 | | matches | | 0 | "She had spent the evening" | | 1 | "She found her usual corner" | | 2 | "His grey-streaked auburn hair caught" | | 3 | "He moved with the restrained" | | 4 | "He placed a pint of" | | 5 | "Her thumb found the crescent-shaped" | | 6 | "He was tall, his posture" | | 7 | "His gaze locked onto her." | | 8 | "She set the pint down." | | 9 | "He crossed the floor." | | 10 | "His laugh was a single" | | 11 | "He unbuttoned his coat and" | | 12 | "He placed a fresh coaster" | | 13 | "He always listened." | | 14 | "She turned her glass in" | | 15 | "He turned to face her." | | 16 | "His eyes were the same" | | 17 | "He finished the whisky." | | 18 | "She met his eyes." | | 19 | "He refilled Caleb's glass from" |
| | ratio | 0.375 | |
| 3.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 80 | | matches | | 0 | "The green neon above The" | | 1 | "Rory pushed through the door," | | 2 | "She had spent the evening" | | 3 | "She found her usual corner" | | 4 | "Silas leant against the back" | | 5 | "His grey-streaked auburn hair caught" | | 6 | "The silver signet ring on" | | 7 | "He moved with the restrained" | | 8 | "He placed a pint of" | | 9 | "Rory wrapped her left hand" | | 10 | "Her thumb found the crescent-shaped" | | 11 | "The beer cut through the" | | 12 | "The door opened." | | 13 | "A draught carried in the" | | 14 | "A man stood beneath the" | | 15 | "He was tall, his posture" | | 16 | "Everything about him spoke of" | | 17 | "His gaze locked onto her." | | 18 | "She set the pint down." | | 19 | "Foam clung to her upper" |
| | ratio | 0.913 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |