| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2143 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 44.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2143 | | totalAiIsms | 24 | | found | | | highlights | | 0 | "weight" | | 1 | "pulsed" | | 2 | "throbbed" | | 3 | "silence" | | 4 | "vibrated" | | 5 | "perfect" | | 6 | "whisper" | | 7 | "rhythmic" | | 8 | "measured" | | 9 | "traced" | | 10 | "echoed" | | 11 | "pulse" | | 12 | "footsteps" | | 13 | "warmth" | | 14 | "fractured" | | 15 | "familiar" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 556 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 556 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 556 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 15 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2143 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 92 | | wordCount | 2141 | | uniqueNames | 24 | | maxNameDensity | 1.12 | | worstName | "You" | | maxWindowNameDensity | 3 | | worstWindowName | "You" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Heartstone | 1 | | Empress | 1 | | English | 1 | | Eva | 2 | | Neon | 1 | | Right | 3 | | Closer | 3 | | You | 24 | | Cold | 3 | | Like | 3 | | Heat | 4 | | Petals | 3 | | Close | 3 | | Branches | 3 | | Arms | 4 | | Three | 3 | | Fingers | 7 | | Boots | 3 | | Pressed | 3 | | Watched | 7 | | Two | 3 | | Street | 3 |
| | persons | | 0 | "Eva" | | 1 | "You" | | 2 | "Heat" | | 3 | "Petals" | | 4 | "Branches" | | 5 | "Arms" | | 6 | "Fingers" | | 7 | "Boots" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Neon" | | 3 | "Right" | | 4 | "Three" |
| | globalScore | 0.94 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 107 | | 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 | 2143 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 556 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 105 | | mean | 20.41 | | std | 10.89 | | cv | 0.533 | | sampleLengths | | 0 | 48 | | 1 | 28 | | 2 | 18 | | 3 | 60 | | 4 | 25 | | 5 | 17 | | 6 | 24 | | 7 | 41 | | 8 | 9 | | 9 | 35 | | 10 | 10 | | 11 | 33 | | 12 | 21 | | 13 | 21 | | 14 | 29 | | 15 | 43 | | 16 | 4 | | 17 | 32 | | 18 | 14 | | 19 | 30 | | 20 | 5 | | 21 | 17 | | 22 | 12 | | 23 | 11 | | 24 | 12 | | 25 | 16 | | 26 | 24 | | 27 | 27 | | 28 | 36 | | 29 | 32 | | 30 | 16 | | 31 | 24 | | 32 | 5 | | 33 | 36 | | 34 | 15 | | 35 | 30 | | 36 | 16 | | 37 | 28 | | 38 | 21 | | 39 | 35 | | 40 | 18 | | 41 | 22 | | 42 | 47 | | 43 | 33 | | 44 | 21 | | 45 | 12 | | 46 | 41 | | 47 | 25 | | 48 | 22 | | 49 | 35 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 556 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 489 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 556 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1987 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 31 | | adverbRatio | 0.01560140915953699 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0010065425264217413 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 556 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 556 | | mean | 3.85 | | std | 2 | | cv | 0.518 | | sampleLengths | | 0 | 4 | | 1 | 7 | | 2 | 6 | | 3 | 7 | | 4 | 7 | | 5 | 4 | | 6 | 9 | | 7 | 4 | | 8 | 8 | | 9 | 6 | | 10 | 5 | | 11 | 5 | | 12 | 4 | | 13 | 1 | | 14 | 6 | | 15 | 11 | | 16 | 7 | | 17 | 3 | | 18 | 6 | | 19 | 6 | | 20 | 8 | | 21 | 4 | | 22 | 6 | | 23 | 4 | | 24 | 7 | | 25 | 3 | | 26 | 2 | | 27 | 4 | | 28 | 7 | | 29 | 2 | | 30 | 6 | | 31 | 3 | | 32 | 1 | | 33 | 1 | | 34 | 5 | | 35 | 2 | | 36 | 15 | | 37 | 2 | | 38 | 7 | | 39 | 4 | | 40 | 3 | | 41 | 8 | | 42 | 5 | | 43 | 3 | | 44 | 8 | | 45 | 6 | | 46 | 4 | | 47 | 5 | | 48 | 4 | | 49 | 6 |
| |
| 56.83% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 54 | | diversityRatio | 0.39928057553956836 | | totalSentences | 556 | | uniqueOpeners | 222 | |
| 64.88% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 411 | | matches | | 0 | "Just a delivery run gone" | | 1 | "Then it dragged ahead of" | | 2 | "Then gave way." | | 3 | "Just the curve of the" | | 4 | "Just the dark." | | 5 | "Too many joints." | | 6 | "Right in front of her" | | 7 | "Then a click." |
| | ratio | 0.019 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 114 | | totalSentences | 411 | | matches | | 0 | "Her boots sank into damp" | | 1 | "She followed the heat." | | 2 | "She adjusted the strap of" | | 3 | "She pressed two fingers to" | | 4 | "She stepped between the oak" | | 5 | "Her watch ticked backwards." | | 6 | "I did not walk past" | | 7 | "They pointed at the centre" | | 8 | "She jerked back." | | 9 | "She wiped it on her" | | 10 | "She opened her palm." | | 11 | "You brought me here." | | 12 | "It smelled of rain and" | | 13 | "They hadn't a moment before." | | 14 | "She ran a hand over" | | 15 | "It coated her fingertips." | | 16 | "She rubbed it against her" | | 17 | "I have had a shift" | | 18 | "My knees ache." | | 19 | "My patience sits at zero." |
| | ratio | 0.277 | |
| 98.69% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 297 | | totalSentences | 411 | | matches | | 0 | "Night swallowed Richmond Park." | | 1 | "Rory stepped over the rusted" | | 2 | "Her boots sank into damp" | | 3 | "The Heartstone pendant rested against" | | 4 | "A thumbnail-sized weight burned through" | | 5 | "She followed the heat." | | 6 | "The map on her phone" | | 7 | "The stones waited ahead." | | 8 | "The air tasted of copper" | | 9 | "Wildflowers pushed through the leaf" | | 10 | "The leaves shivered anyway." | | 11 | "She adjusted the strap of" | | 12 | "The pendant pulsed." | | 13 | "A slow rhythm matched her" | | 14 | "She pressed two fingers to" | | 15 | "The gem throbbed hotter." | | 16 | "She stepped between the oak" | | 17 | "The curves looked too much" | | 18 | "The clearing opened." | | 19 | "Her watch ticked backwards." |
| | ratio | 0.723 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 411 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 5 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |