| 73.02% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 30 | | adverbTagCount | 4 | | adverbTags | | 0 | "Aurora said quietly [quietly]" | | 1 | "The denial came too [too]" | | 2 | "The single word cracked like [like]" | | 3 | "he agreed softly [softly]" |
| | dialogueSentences | 63 | | tagDensity | 0.476 | | leniency | 0.952 | | rawRatio | 0.133 | | effectiveRatio | 0.127 | |
| 93.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1545 | | totalAiIsmAdverbs | 2 | | 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) | |
| 57.93% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1545 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "familiar" | | 1 | "flickered" | | 2 | "marble" | | 3 | "echo" | | 4 | "weight" | | 5 | "traced" | | 6 | "silence" | | 7 | "magnetic" | | 8 | "unspoken" | | 9 | "echoed" |
| |
| 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 | 108 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 108 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1545 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 974 | | uniqueNames | 11 | | maxNameDensity | 0.92 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Aurora | 8 | | Silas | 9 | | Old | 1 | | Soho | 1 | | Grateful | 1 | | East | 1 | | End | 1 | | Spymaster | 1 | | Eva | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Aurora" | | 3 | "Silas" | | 4 | "Spymaster" | | 5 | "Eva" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 81.51% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 2 | | matches | | 0 | "quite place" | | 1 | "felt like an apology for something neit" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1545 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 99.30% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 25.33 | | std | 12.6 | | cv | 0.498 | | sampleLengths | | 0 | 42 | | 1 | 32 | | 2 | 1 | | 3 | 47 | | 4 | 26 | | 5 | 31 | | 6 | 23 | | 7 | 51 | | 8 | 10 | | 9 | 31 | | 10 | 23 | | 11 | 3 | | 12 | 34 | | 13 | 4 | | 14 | 26 | | 15 | 17 | | 16 | 33 | | 17 | 22 | | 18 | 12 | | 19 | 23 | | 20 | 12 | | 21 | 34 | | 22 | 26 | | 23 | 35 | | 24 | 17 | | 25 | 15 | | 26 | 42 | | 27 | 18 | | 28 | 14 | | 29 | 23 | | 30 | 54 | | 31 | 27 | | 32 | 18 | | 33 | 33 | | 34 | 6 | | 35 | 39 | | 36 | 35 | | 37 | 30 | | 38 | 12 | | 39 | 23 | | 40 | 36 | | 41 | 25 | | 42 | 30 | | 43 | 24 | | 44 | 45 | | 45 | 30 | | 46 | 2 | | 47 | 8 | | 48 | 26 | | 49 | 38 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 108 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 171 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 141 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 975 | | adjectiveStacks | 1 | | stackExamples | | 0 | "outside painted strange patterns" |
| | adverbCount | 37 | | adverbRatio | 0.03794871794871795 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006153846153846154 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 10.96 | | std | 6.83 | | cv | 0.624 | | sampleLengths | | 0 | 26 | | 1 | 12 | | 2 | 4 | | 3 | 12 | | 4 | 4 | | 5 | 16 | | 6 | 1 | | 7 | 12 | | 8 | 16 | | 9 | 19 | | 10 | 15 | | 11 | 11 | | 12 | 8 | | 13 | 14 | | 14 | 9 | | 15 | 14 | | 16 | 2 | | 17 | 7 | | 18 | 10 | | 19 | 4 | | 20 | 14 | | 21 | 15 | | 22 | 8 | | 23 | 5 | | 24 | 5 | | 25 | 31 | | 26 | 6 | | 27 | 4 | | 28 | 13 | | 29 | 3 | | 30 | 9 | | 31 | 9 | | 32 | 12 | | 33 | 4 | | 34 | 4 | | 35 | 15 | | 36 | 11 | | 37 | 9 | | 38 | 1 | | 39 | 1 | | 40 | 6 | | 41 | 19 | | 42 | 14 | | 43 | 14 | | 44 | 8 | | 45 | 11 | | 46 | 1 | | 47 | 9 | | 48 | 14 | | 49 | 11 |
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| 77.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.48226950354609927 | | totalSentences | 141 | | uniqueOpeners | 68 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 100 | | matches | | 0 | "Then she saw him." | | 1 | "Too honest for the girl" | | 2 | "Once he'd been the man" |
| | ratio | 0.03 | |
| 88.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 33 | | totalSentences | 100 | | matches | | 0 | "His hazel eyes lifted." | | 1 | "She crossed the room anyway," | | 2 | "She slid onto a stool," | | 3 | "He set the glass down" | | 4 | "She regretted the words the" | | 5 | "His hands, she noticed, had" | | 6 | "He slid the drink across." | | 7 | "Their fingers didn't quite touch." | | 8 | "His voice carried the same" | | 9 | "She studied him over the" | | 10 | "He wiped the bar in" | | 11 | "She traced the rim of" | | 12 | "She nodded toward the ceiling" | | 13 | "He shrugged, but the movement" | | 14 | "Her laugh came out hollow" | | 15 | "They both waited until the" | | 16 | "His expression didn't change, but" | | 17 | "She met his gaze directly" | | 18 | "She felt it nick something" | | 19 | "He leaned forward, forearms resting" |
| | ratio | 0.33 | |
| 10.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 100 | | matches | | 0 | "Aurora shoved the heavy oak" | | 1 | "The familiar scent of spilled" | | 2 | "Silas stood behind the bar" | | 3 | "His hazel eyes lifted." | | 4 | "Recognition flickered across his face," | | 5 | "The name landed between them," | | 6 | "She crossed the room anyway," | | 7 | "The crescent scar on her" | | 8 | "She slid onto a stool," | | 9 | "He set the glass down" | | 10 | "The silver signet ring caught" | | 11 | "She regretted the words the" | | 12 | "Silas poured two fingers of" | | 13 | "The bottle looked expensive." | | 14 | "His hands, she noticed, had" | | 15 | "The slight limp became apparent" | | 16 | "Prague had taken more than" | | 17 | "He slid the drink across." | | 18 | "Their fingers didn't quite touch." | | 19 | "His voice carried the same" |
| | ratio | 0.9 | |
| 50.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 100 | | matches | | | ratio | 0.01 | |
| 98.21% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 2 | | matches | | 0 | "Silas stood behind the bar polishing a glass that didn't need polishing." | | 1 | "He approached the bar with the careful steps of a man who knew he was being watched." |
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| 58.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 30 | | uselessAdditionCount | 4 | | matches | | 0 | "She slid, elbows finding the familiar groove in the bar top" | | 1 | "He wiped, the cloth moving with military precision" | | 2 | "He shrugged, but the movement pulled at something in his shoulder" | | 3 | "He leaned, forearms resting on the bar" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "he agreed softly (agree)" |
| | dialogueSentences | 63 | | tagDensity | 0.048 | | leniency | 0.095 | | rawRatio | 0.333 | | effectiveRatio | 0.032 | |