| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "Eva said quietly [quietly]" |
| | dialogueSentences | 33 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.091 | | effectiveRatio | 0.061 | |
| 78.68% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 938 | | 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) | |
| 89.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 938 | | totalAiIsms | 2 | | found | | | highlights | | |
| 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 | 46 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 46 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 67 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 938 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 46.55% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 38 | | wordCount | 580 | | uniqueNames | 16 | | maxNameDensity | 2.07 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Old | 1 | | Compton | 1 | | Street | 1 | | Raven | 1 | | Nest | 1 | | Rory | 12 | | Thursday | 1 | | Silas | 3 | | Barry | 1 | | Island | 1 | | Cardiff | 1 | | Soho | 1 | | Eva | 10 | | Staropramen | 1 | | Golden | 1 | | Empress | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Rory" | | 3 | "Silas" | | 4 | "Eva" | | 5 | "Staropramen" |
| | places | | 0 | "Old" | | 1 | "Compton" | | 2 | "Street" | | 3 | "Barry" | | 4 | "Island" | | 5 | "Cardiff" | | 6 | "Soho" |
| | globalScore | 0.466 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 31 | | 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 | 938 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 67 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 28.42 | | std | 23.71 | | cv | 0.834 | | sampleLengths | | 0 | 55 | | 1 | 59 | | 2 | 24 | | 3 | 37 | | 4 | 3 | | 5 | 53 | | 6 | 11 | | 7 | 46 | | 8 | 1 | | 9 | 2 | | 10 | 49 | | 11 | 6 | | 12 | 15 | | 13 | 47 | | 14 | 11 | | 15 | 77 | | 16 | 6 | | 17 | 29 | | 18 | 10 | | 19 | 12 | | 20 | 64 | | 21 | 3 | | 22 | 45 | | 23 | 53 | | 24 | 74 | | 25 | 39 | | 26 | 6 | | 27 | 1 | | 28 | 5 | | 29 | 19 | | 30 | 55 | | 31 | 16 | | 32 | 5 |
| |
| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 46 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 95 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 582 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.03608247422680412 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.010309278350515464 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 67 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 67 | | mean | 14 | | std | 13.25 | | cv | 0.946 | | sampleLengths | | 0 | 29 | | 1 | 26 | | 2 | 6 | | 3 | 21 | | 4 | 4 | | 5 | 28 | | 6 | 12 | | 7 | 12 | | 8 | 10 | | 9 | 17 | | 10 | 10 | | 11 | 3 | | 12 | 25 | | 13 | 28 | | 14 | 11 | | 15 | 3 | | 16 | 24 | | 17 | 12 | | 18 | 7 | | 19 | 1 | | 20 | 2 | | 21 | 3 | | 22 | 25 | | 23 | 21 | | 24 | 6 | | 25 | 8 | | 26 | 7 | | 27 | 33 | | 28 | 14 | | 29 | 8 | | 30 | 3 | | 31 | 54 | | 32 | 23 | | 33 | 6 | | 34 | 14 | | 35 | 15 | | 36 | 3 | | 37 | 7 | | 38 | 10 | | 39 | 2 | | 40 | 11 | | 41 | 53 | | 42 | 3 | | 43 | 8 | | 44 | 2 | | 45 | 35 | | 46 | 3 | | 47 | 31 | | 48 | 19 | | 49 | 7 |
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| 58.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3880597014925373 | | totalSentences | 67 | | uniqueOpeners | 26 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 14 | | totalSentences | 42 | | matches | | 0 | "She shook water from her" | | 1 | "He nodded toward the back" | | 2 | "He didn't need to." | | 3 | "She knew the rhythm of" | | 4 | "she said, sliding onto a" | | 5 | "He favoured his left leg" | | 6 | "She reached for her phone" | | 7 | "It was low and certain," | | 8 | "Her hair had been cropped" | | 9 | "She had imagined this moment" | | 10 | "He drifted to the other" | | 11 | "She pressed her left wrist" | | 12 | "It involved a flat above" | | 13 | "It involved a version of" |
| | ratio | 0.333 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 40 | | totalSentences | 42 | | matches | | 0 | "The rain had turned the" | | 1 | "She shook water from her" | | 2 | "Silas glanced up from the" | | 3 | "He nodded toward the back" | | 4 | "He didn't need to." | | 5 | "She knew the rhythm of" | | 6 | "she said, sliding onto a" | | 7 | "Silas said, reaching for a" | | 8 | "He favoured his left leg" | | 9 | "She reached for her phone" | | 10 | "It was low and certain," | | 11 | "Rory turned slowly." | | 12 | "A woman in a camel" | | 13 | "Her hair had been cropped" | | 14 | "A thin gold band caught" | | 15 | "Rory didn't move." | | 16 | "She had imagined this moment" | | 17 | "Eva's smile was thin, controlled" | | 18 | "Silas set the pint down" | | 19 | "He drifted to the other" |
| | ratio | 0.952 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 42 | | matches | (empty) | | ratio | 0 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 2 | | matches | | 0 | "It was low and certain, the kind of voice that had once argued with her over the last bag of crisps on a school trip to Barry Island." | | 1 | "Silas set the pint down in front of Rory without a word, but his gaze moved between the two women with the careful attention of a man who had spent decades read…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 33 | | tagDensity | 0.212 | | leniency | 0.424 | | rawRatio | 0.143 | | effectiveRatio | 0.061 | |