| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 173 | | tagDensity | 0.116 | | leniency | 0.231 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2321 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 89.23% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2321 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "weight" | | 1 | "perfect" | | 2 | "warmth" | | 3 | "flickered" | | 4 | "comfortable" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 2 |
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| | highlights | | 0 | "eyes narrowed" | | 1 | "eyes widened" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 160 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 160 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened to" | | 1 | "tried to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 314 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 69 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2321 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 41 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 85 | | wordCount | 1354 | | uniqueNames | 12 | | maxNameDensity | 2.07 | | worstName | "Aurora" | | maxWindowNameDensity | 5 | | worstWindowName | "Owen" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Silas | 18 | | Aurora | 28 | | Cardiff | 2 | | University | 1 | | Owen | 27 | | Hughes | 2 | | Europe | 1 | | London | 2 | | Mr | 1 | | City | 1 |
| | persons | | 0 | "Raven" | | 1 | "Silas" | | 2 | "Aurora" | | 3 | "Owen" | | 4 | "Hughes" | | 5 | "Mr" |
| | places | | 0 | "Cardiff" | | 1 | "Europe" | | 2 | "London" |
| | globalScore | 0.466 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 97 | | 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 | 2321 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 314 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 247 | | mean | 9.4 | | std | 12.13 | | cv | 1.29 | | sampleLengths | | 0 | 48 | | 1 | 52 | | 2 | 4 | | 3 | 13 | | 4 | 7 | | 5 | 4 | | 6 | 15 | | 7 | 6 | | 8 | 7 | | 9 | 10 | | 10 | 2 | | 11 | 13 | | 12 | 6 | | 13 | 5 | | 14 | 22 | | 15 | 10 | | 16 | 10 | | 17 | 20 | | 18 | 8 | | 19 | 69 | | 20 | 7 | | 21 | 71 | | 22 | 5 | | 23 | 5 | | 24 | 1 | | 25 | 13 | | 26 | 8 | | 27 | 21 | | 28 | 1 | | 29 | 12 | | 30 | 4 | | 31 | 3 | | 32 | 15 | | 33 | 6 | | 34 | 9 | | 35 | 14 | | 36 | 4 | | 37 | 4 | | 38 | 1 | | 39 | 6 | | 40 | 5 | | 41 | 3 | | 42 | 6 | | 43 | 7 | | 44 | 3 | | 45 | 6 | | 46 | 6 | | 47 | 31 | | 48 | 4 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 160 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 243 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 2 | | flaggedSentences | 1 | | totalSentences | 314 | | ratio | 0.003 | | matches | | 0 | "For a second, Aurora saw him as he had been at nineteen: a lean boy in a denim jacket, laughing over a broken bicycle chain on the pavement outside Cardiff University; a boy who had borrowed her notes and returned them with rude cartoons in the margins; a boy who had climbed through the library window because he had lost his student card and considered rules a personal insult." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1203 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.029925187032418952 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004156275976724855 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 314 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 314 | | mean | 7.39 | | std | 6.58 | | cv | 0.89 | | sampleLengths | | 0 | 19 | | 1 | 29 | | 2 | 21 | | 3 | 7 | | 4 | 12 | | 5 | 12 | | 6 | 4 | | 7 | 13 | | 8 | 7 | | 9 | 4 | | 10 | 5 | | 11 | 10 | | 12 | 6 | | 13 | 7 | | 14 | 10 | | 15 | 2 | | 16 | 13 | | 17 | 6 | | 18 | 5 | | 19 | 22 | | 20 | 10 | | 21 | 10 | | 22 | 8 | | 23 | 12 | | 24 | 8 | | 25 | 69 | | 26 | 7 | | 27 | 11 | | 28 | 14 | | 29 | 10 | | 30 | 15 | | 31 | 21 | | 32 | 5 | | 33 | 5 | | 34 | 1 | | 35 | 13 | | 36 | 4 | | 37 | 4 | | 38 | 9 | | 39 | 12 | | 40 | 1 | | 41 | 12 | | 42 | 4 | | 43 | 3 | | 44 | 9 | | 45 | 6 | | 46 | 6 | | 47 | 9 | | 48 | 14 | | 49 | 4 |
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| 43.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.2070063694267516 | | totalSentences | 314 | | uniqueOpeners | 65 | |
| 48.31% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 138 | | matches | | 0 | "Then a man stepped beneath" | | 1 | "Then the door swung shut" |
| | ratio | 0.014 | |
| 77.97% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 49 | | totalSentences | 138 | | matches | | 0 | "His silver signet ring caught" | | 1 | "His hazel eyes narrowed over" | | 2 | "He paused with one hand" | | 3 | "His hair, once a careless" | | 4 | "He stood straighter than Owen" | | 5 | "His eyes had not changed." | | 6 | "They found her and held." | | 7 | "He did not ask." | | 8 | "He took two steps towards" | | 9 | "It vanished before it formed" | | 10 | "His gaze stayed on Owen." | | 11 | "His laugh came out rougher" | | 12 | "He looked at the empty" | | 13 | "Her hands needed a job." | | 14 | "He pulled off his gloves" | | 15 | "His hands had grown larger," | | 16 | "He did not lift it." | | 17 | "It sat between them all" | | 18 | "He stayed within earshot." | | 19 | "He gave people room without" |
| | ratio | 0.355 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 129 | | totalSentences | 138 | | matches | | 0 | "Rain shivered down the green" | | 1 | "Aurora shouldered through the door" | | 2 | "The bar smelled of old" | | 3 | "A jazz record muttered from" | | 4 | "Silas stood behind the counter," | | 5 | "His silver signet ring caught" | | 6 | "Silas set the glass down." | | 7 | "His hazel eyes narrowed over" | | 8 | "Aurora dropped the cartons on" | | 9 | "Silas reached for the paper" | | 10 | "Aurora snorted, then turned towards" | | 11 | "A gust of cold air" | | 12 | "He paused with one hand" | | 13 | "The man wore a dark" | | 14 | "His hair, once a careless" | | 15 | "A pale line crossed the" | | 16 | "He stood straighter than Owen" | | 17 | "His eyes had not changed." | | 18 | "They found her and held." | | 19 | "The name landed in the" |
| | ratio | 0.935 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 138 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 1 | | matches | | 0 | "For a second, Aurora saw him as he had been at nineteen: a lean boy in a denim jacket, laughing over a broken bicycle chain on the pavement outside Cardiff Univ…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 173 | | tagDensity | 0.092 | | leniency | 0.185 | | rawRatio | 0 | | effectiveRatio | 0 | |