| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 91.60% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 595 | | 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) | |
| 15.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 595 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "comforting" | | 1 | "eyebrow" | | 2 | "charged" | | 3 | "flickered" | | 4 | "measured" | | 5 | "stomach" | | 6 | "comfortable" | | 7 | "silence" | | 8 | "tension" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
|
| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 26 | | matches | (empty) | |
| 0.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 26 | | filterMatches | (empty) | | hedgeMatches | | |
| 82.55% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 33 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0.03 | | matches | | 0 | "<Rory's voice slid into the silence, smooth and detached>Even after all this time, the memory of him still managed to leave a bitter taste on my palate." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 594 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 31.97% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 28 | | wordCount | 466 | | uniqueNames | 9 | | maxNameDensity | 2.36 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 3 | | Nest | 3 | | Eiffel | 1 | | Tower | 1 | | Eva | 1 | | Soho | 1 | | Rory | 11 | | Silas | 5 | | Evan | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Eva" | | 3 | "Rory" | | 4 | "Silas" | | 5 | "Evan" |
| | places | | | globalScore | 0.32 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 23 | | 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 | 594 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 33 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 14 | | mean | 42.43 | | std | 22.05 | | cv | 0.52 | | sampleLengths | | 0 | 86 | | 1 | 79 | | 2 | 50 | | 3 | 34 | | 4 | 50 | | 5 | 75 | | 6 | 19 | | 7 | 44 | | 8 | 38 | | 9 | 23 | | 10 | 21 | | 11 | 27 | | 12 | 23 | | 13 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 26 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 74 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 182 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.02197802197802198 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.01098901098901099 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 33 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 33 | | mean | 18 | | std | 8.84 | | cv | 0.491 | | sampleLengths | | 0 | 35 | | 1 | 23 | | 2 | 28 | | 3 | 24 | | 4 | 18 | | 5 | 37 | | 6 | 16 | | 7 | 14 | | 8 | 20 | | 9 | 27 | | 10 | 7 | | 11 | 24 | | 12 | 26 | | 13 | 22 | | 14 | 23 | | 15 | 17 | | 16 | 13 | | 17 | 19 | | 18 | 28 | | 19 | 16 | | 20 | 25 | | 21 | 13 | | 22 | 7 | | 23 | 10 | | 24 | 6 | | 25 | 19 | | 26 | 2 | | 27 | 27 | | 28 | 5 | | 29 | 4 | | 30 | 14 | | 31 | 6 | | 32 | 19 |
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| 74.75% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.48484848484848486 | | totalSentences | 33 | | uniqueOpeners | 16 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 25 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 7 | | totalSentences | 25 | | matches | | 0 | "She settled her hands on" | | 1 | "It wasn't terribly late, the" | | 2 | "His eyes locked onto Rory," | | 3 | "His name, Evan, flashed through" | | 4 | "His voice controlled but glowing" | | 5 | "His scared reply chased nervous" | | 6 | "His nervous spoken reply reclaimed" |
| | ratio | 0.28 | |
| 40.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 21 | | totalSentences | 25 | | matches | | 0 | "Rory slid onto the stool" | | 1 | "The air was thick with" | | 2 | "She settled her hands on" | | 3 | "It wasn't terribly late, the" | | 4 | "Rory's gaze landed on a" | | 5 | "Silas, her friend and the" | | 6 | "Rory's drink arrived, and she" | | 7 | "The sound of the TV," | | 8 | "His eyes locked onto Rory," | | 9 | "His name, Evan, flashed through" | | 10 | "A soft growl emanated from" | | 11 | "The constrained pause hung heavy," | | 12 | "A tense smirk appeared on" | | 13 | "Silas yelled, ushering Rory a" | | 14 | "Darkness shrouded the place behind" | | 15 | "His voice controlled but glowing" | | 16 | "<Rory's voice slid into the" | | 17 | "A ripple dissolved nervous undertones." | | 18 | "Darkness issued quietly up." | | 19 | "His scared reply chased nervous" |
| | ratio | 0.84 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 25 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 20 | | technicalSentenceCount | 1 | | matches | | 0 | "The constrained pause hung heavy, only growing thicker as Silas cleared his throat, folding his hands into his lap, he met Evan's piercing stare unblinking." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |