| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 49 | | tagDensity | 0.163 | | leniency | 0.327 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.64% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1146 | | 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) | |
| 52.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1146 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "weight" | | 2 | "flickered" | | 3 | "scanning" | | 4 | "predator" | | 5 | "silence" | | 6 | "echoed" | | 7 | "crystalline" | | 8 | "vibrated" |
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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 | 74 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 74 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 115 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1146 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 747 | | uniqueNames | 10 | | maxNameDensity | 2.54 | | worstName | "Julian" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Julian" | | discoveredNames | | Rory | 10 | | Cardiff | 1 | | University | 1 | | Vance | 1 | | Golden | 1 | | Empress | 1 | | Julian | 19 | | Silas | 6 | | Torts | 1 | | Adam | 1 |
| | persons | | 0 | "Rory" | | 1 | "University" | | 2 | "Vance" | | 3 | "Julian" | | 4 | "Silas" | | 5 | "Adam" |
| | places | | | globalScore | 0.228 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a sketch of himself, drawn wi" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1146 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 115 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 69 | | mean | 16.61 | | std | 13.79 | | cv | 0.83 | | sampleLengths | | 0 | 27 | | 1 | 5 | | 2 | 29 | | 3 | 9 | | 4 | 9 | | 5 | 72 | | 6 | 10 | | 7 | 2 | | 8 | 35 | | 9 | 2 | | 10 | 1 | | 11 | 9 | | 12 | 5 | | 13 | 36 | | 14 | 15 | | 15 | 26 | | 16 | 4 | | 17 | 13 | | 18 | 16 | | 19 | 42 | | 20 | 33 | | 21 | 4 | | 22 | 15 | | 23 | 13 | | 24 | 2 | | 25 | 9 | | 26 | 11 | | 27 | 3 | | 28 | 10 | | 29 | 23 | | 30 | 23 | | 31 | 31 | | 32 | 11 | | 33 | 8 | | 34 | 30 | | 35 | 12 | | 36 | 8 | | 37 | 8 | | 38 | 29 | | 39 | 10 | | 40 | 20 | | 41 | 43 | | 42 | 2 | | 43 | 36 | | 44 | 14 | | 45 | 18 | | 46 | 4 | | 47 | 7 | | 48 | 12 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 74 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 125 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 115 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 748 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 13 | | adverbRatio | 0.017379679144385027 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.008021390374331552 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 115 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 115 | | mean | 9.97 | | std | 5.9 | | cv | 0.592 | | sampleLengths | | 0 | 12 | | 1 | 15 | | 2 | 5 | | 3 | 17 | | 4 | 12 | | 5 | 9 | | 6 | 9 | | 7 | 14 | | 8 | 19 | | 9 | 4 | | 10 | 14 | | 11 | 21 | | 12 | 3 | | 13 | 7 | | 14 | 2 | | 15 | 4 | | 16 | 15 | | 17 | 16 | | 18 | 2 | | 19 | 1 | | 20 | 9 | | 21 | 5 | | 22 | 5 | | 23 | 3 | | 24 | 20 | | 25 | 8 | | 26 | 15 | | 27 | 8 | | 28 | 9 | | 29 | 9 | | 30 | 4 | | 31 | 13 | | 32 | 16 | | 33 | 9 | | 34 | 15 | | 35 | 18 | | 36 | 21 | | 37 | 12 | | 38 | 4 | | 39 | 2 | | 40 | 13 | | 41 | 13 | | 42 | 2 | | 43 | 9 | | 44 | 11 | | 45 | 3 | | 46 | 10 | | 47 | 7 | | 48 | 16 | | 49 | 23 |
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| 40.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3130434782608696 | | totalSentences | 115 | | uniqueOpeners | 36 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 71 | | matches | | 0 | "He tapped the silver signet" | | 1 | "He wore an expensive navy" | | 2 | "He paused in the doorway," | | 3 | "His face had thinned, the" | | 4 | "He didn't sit." | | 5 | "He stood with a rigid," | | 6 | "He smelled of expensive sandalwood" | | 7 | "She rubbed the crescent-shaped scar" | | 8 | "He didn't speak, but his" | | 9 | "He saw the way Julian's" | | 10 | "She leaned in, the scent" | | 11 | "He didn't squeeze hard, but" | | 12 | "His Adam's apple bobbed in" | | 13 | "It was a collapse." | | 14 | "He gestured to the dim" | | 15 | "It went dark." | | 16 | "He stepped back, his expression" | | 17 | "He reached under the bar," | | 18 | "She hit the hidden release," | | 19 | "He had gone pale, his" |
| | ratio | 0.296 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 71 | | matches | | 0 | "Aurora scrubbed a sticky ring" | | 1 | "The cloth clung to the" | | 2 | "Silas leaned against the far" | | 3 | "He tapped the silver signet" | | 4 | "The green neon sign outside" | | 5 | "The bell above the door" | | 6 | "A man stepped inside." | | 7 | "He wore an expensive navy" | | 8 | "He paused in the doorway," | | 9 | "Rory stopped scrubbing." | | 10 | "The cloth stayed pressed to" | | 11 | "The man stepped forward." | | 12 | "His face had thinned, the" | | 13 | "Julian Vance looked like a" | | 14 | "Julian walked to the bar." | | 15 | "He didn't sit." | | 16 | "He stood with a rigid," | | 17 | "He smelled of expensive sandalwood" | | 18 | "Rory looked down at her" | | 19 | "A small splash of soy" |
| | ratio | 0.972 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 71 | | matches | (empty) | | ratio | 0 | |
| 53.57% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 32 | | technicalSentenceCount | 4 | | matches | | 0 | "He wore an expensive navy wool suit that cost more than Rory's annual rent." | | 1 | "He paused in the doorway, his eyes scanning the dimly lit room, lingering on the old maps pinned to the walls." | | 2 | "For a second, the polished solicitor vanished, leaving behind a terrified boy who used to cheat on his Torts exams." | | 3 | "The sound of shattering glass followed, a violent, crystalline explosion that ripped through the quiet." |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "Julian whispered, his voice cracking" |
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| 88.78% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 3 | | fancyTags | | 0 | "Julian whispered (whisper)" | | 1 | "Rory yelled (yell)" | | 2 | "a voice roared (roar)" |
| | dialogueSentences | 49 | | tagDensity | 0.082 | | leniency | 0.163 | | rawRatio | 0.75 | | effectiveRatio | 0.122 | |