| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 51 | | tagDensity | 0.275 | | leniency | 0.549 | | rawRatio | 0.071 | | effectiveRatio | 0.039 | |
| 96.95% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1639 | | 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) | |
| 75.59% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1639 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "tracing" | | 1 | "silence" | | 2 | "traced" | | 3 | "weight" | | 4 | "warmth" |
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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 | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 51 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1639 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 31.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 37 | | wordCount | 757 | | uniqueNames | 6 | | maxNameDensity | 2.38 | | worstName | "Silas" | | maxWindowNameDensity | 4 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 18 | | Rory | 15 | | Prague | 1 | | London | 1 |
| | persons | | | places | | | globalScore | 0.311 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 51 | | 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 | 1639 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 109 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 38.12 | | std | 20.18 | | cv | 0.529 | | sampleLengths | | 0 | 83 | | 1 | 39 | | 2 | 30 | | 3 | 51 | | 4 | 17 | | 5 | 54 | | 6 | 26 | | 7 | 26 | | 8 | 6 | | 9 | 30 | | 10 | 40 | | 11 | 82 | | 12 | 21 | | 13 | 59 | | 14 | 73 | | 15 | 38 | | 16 | 16 | | 17 | 71 | | 18 | 23 | | 19 | 63 | | 20 | 56 | | 21 | 47 | | 22 | 69 | | 23 | 24 | | 24 | 30 | | 25 | 53 | | 26 | 59 | | 27 | 40 | | 28 | 13 | | 29 | 42 | | 30 | 7 | | 31 | 25 | | 32 | 51 | | 33 | 24 | | 34 | 4 | | 35 | 41 | | 36 | 51 | | 37 | 18 | | 38 | 19 | | 39 | 29 | | 40 | 24 | | 41 | 32 | | 42 | 33 |
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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 | 138 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 109 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 760 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 27 | | adverbRatio | 0.035526315789473684 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010526315789473684 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 15.04 | | std | 10.42 | | cv | 0.693 | | sampleLengths | | 0 | 31 | | 1 | 31 | | 2 | 21 | | 3 | 23 | | 4 | 16 | | 5 | 7 | | 6 | 23 | | 7 | 14 | | 8 | 15 | | 9 | 22 | | 10 | 7 | | 11 | 10 | | 12 | 17 | | 13 | 14 | | 14 | 23 | | 15 | 10 | | 16 | 12 | | 17 | 4 | | 18 | 6 | | 19 | 11 | | 20 | 6 | | 21 | 3 | | 22 | 6 | | 23 | 8 | | 24 | 22 | | 25 | 7 | | 26 | 4 | | 27 | 29 | | 28 | 7 | | 29 | 22 | | 30 | 38 | | 31 | 15 | | 32 | 10 | | 33 | 11 | | 34 | 40 | | 35 | 19 | | 36 | 9 | | 37 | 6 | | 38 | 8 | | 39 | 50 | | 40 | 4 | | 41 | 34 | | 42 | 4 | | 43 | 12 | | 44 | 34 | | 45 | 13 | | 46 | 12 | | 47 | 12 | | 48 | 14 | | 49 | 9 |
| |
| 52.91% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3394495412844037 | | totalSentences | 109 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 65.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 24 | | totalSentences | 62 | | matches | | 0 | "She dropped her delivery receipts" | | 1 | "he said, voice low and" | | 2 | "She met his gaze without" | | 3 | "He limped around the bar," | | 4 | "He lowered himself onto the" | | 5 | "Her straight black hair fell" | | 6 | "He tapped the bar top" | | 7 | "They sat with that for" | | 8 | "His grey-streaked auburn hair fell" | | 9 | "She set the glass down" | | 10 | "She rubbed the scar on" | | 11 | "He flipped the sign to" | | 12 | "He met her eyes directly" | | 13 | "She looked past him at" | | 14 | "Her bright blue eyes stayed" | | 15 | "He turned his right hand" | | 16 | "She finished the whisky and" | | 17 | "He reached behind the counter" | | 18 | "He set it between them." | | 19 | "She kept her hands flat" |
| | ratio | 0.387 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 62 | | matches | | 0 | "Rory pushed through the heavy" | | 1 | "She dropped her delivery receipts" | | 2 | "The bar smelled of old" | | 3 | "Silas looked up from the" | | 4 | "he said, voice low and" | | 5 | "She met his gaze without" | | 6 | "Silas poured two fingers into" | | 7 | "The silver signet ring on" | | 8 | "Rory traced the rim of" | | 9 | "He limped around the bar," | | 10 | "He lowered himself onto the" | | 11 | "Her straight black hair fell" | | 12 | "Silas nodded once, the movement" | | 13 | "He tapped the bar top" | | 14 | "They sat with that for" | | 15 | "The jazz record on the" | | 16 | "Rory finally lifted the glass" | | 17 | "The burn steadied her." | | 18 | "Silas leaned his elbows on" | | 19 | "His grey-streaked auburn hair fell" |
| | ratio | 0.935 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 62 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 1 | | matches | | 0 | "One showed a younger Silas in a raincoat, a cigarette between his fingers, standing in front of a Prague street that looked colder than any London winter." |
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| 89.29% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, voice low and even" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 51 | | tagDensity | 0.216 | | leniency | 0.431 | | rawRatio | 0 | | effectiveRatio | 0 | |