| 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 | 1380 | | 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) | |
| 71.01% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1380 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "pulse" | | 1 | "silence" | | 2 | "footsteps" | | 3 | "weight" | | 4 | "dance" |
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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 | 158 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 158 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 166 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1380 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 1337 | | uniqueNames | 6 | | maxNameDensity | 0.82 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 2 | | Heartstone | 1 | | Park | 1 | | Silas | 1 | | London | 1 | | Rory | 11 |
| | persons | | 0 | "Heartstone" | | 1 | "Silas" | | 2 | "Rory" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed farther apart now than they had from outside" |
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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 | 1380 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 166 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 24.21 | | std | 19.44 | | cv | 0.803 | | sampleLengths | | 0 | 68 | | 1 | 49 | | 2 | 61 | | 3 | 3 | | 4 | 26 | | 5 | 1 | | 6 | 10 | | 7 | 43 | | 8 | 1 | | 9 | 40 | | 10 | 6 | | 11 | 31 | | 12 | 22 | | 13 | 40 | | 14 | 4 | | 15 | 4 | | 16 | 13 | | 17 | 61 | | 18 | 27 | | 19 | 10 | | 20 | 57 | | 21 | 9 | | 22 | 11 | | 23 | 20 | | 24 | 34 | | 25 | 38 | | 26 | 8 | | 27 | 11 | | 28 | 3 | | 29 | 11 | | 30 | 1 | | 31 | 38 | | 32 | 2 | | 33 | 29 | | 34 | 27 | | 35 | 11 | | 36 | 5 | | 37 | 57 | | 38 | 64 | | 39 | 6 | | 40 | 21 | | 41 | 33 | | 42 | 5 | | 43 | 12 | | 44 | 27 | | 45 | 48 | | 46 | 41 | | 47 | 41 | | 48 | 3 | | 49 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 158 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 212 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 166 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1343 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 42 | | adverbRatio | 0.03127326880119136 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0007446016381236039 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 166 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 166 | | mean | 8.31 | | std | 5.67 | | cv | 0.682 | | sampleLengths | | 0 | 14 | | 1 | 16 | | 2 | 23 | | 3 | 4 | | 4 | 4 | | 5 | 7 | | 6 | 7 | | 7 | 2 | | 8 | 3 | | 9 | 17 | | 10 | 20 | | 11 | 10 | | 12 | 14 | | 13 | 17 | | 14 | 5 | | 15 | 15 | | 16 | 3 | | 17 | 4 | | 18 | 5 | | 19 | 6 | | 20 | 11 | | 21 | 1 | | 22 | 4 | | 23 | 6 | | 24 | 4 | | 25 | 9 | | 26 | 11 | | 27 | 19 | | 28 | 1 | | 29 | 4 | | 30 | 15 | | 31 | 4 | | 32 | 17 | | 33 | 6 | | 34 | 7 | | 35 | 19 | | 36 | 2 | | 37 | 1 | | 38 | 2 | | 39 | 8 | | 40 | 4 | | 41 | 2 | | 42 | 1 | | 43 | 7 | | 44 | 12 | | 45 | 8 | | 46 | 20 | | 47 | 4 | | 48 | 4 | | 49 | 2 |
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| 41.57% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 14 | | diversityRatio | 0.25903614457831325 | | totalSentences | 166 | | uniqueOpeners | 43 | |
| 96.62% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 138 | | matches | | 0 | "Then another laugh, same pitch," | | 1 | "Then, from somewhere near the" | | 2 | "Too long in the jaw." | | 3 | "Too many fingers." |
| | ratio | 0.029 | |
| 60.58% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 138 | | matches | | 0 | "She kept to the treeline," | | 1 | "They had no business blooming." | | 2 | "Her own breath sounded too" | | 3 | "It hit the flowers and" | | 4 | "She took another step." | | 5 | "She turned to check the" | | 6 | "She pulled her phone." | | 7 | "She could have sworn it" | | 8 | "She pocketed the phone and" | | 9 | "She turned her head and" | | 10 | "She looked forward again and" | | 11 | "She had grown up on" | | 12 | "She turned a slow circle," | | 13 | "She had counted five from" | | 14 | "They had been open when" | | 15 | "Their heads now pointed inward," | | 16 | "She crouched and touched one." | | 17 | "She walked to the nearest" | | 18 | "She did not." | | 19 | "Her crescent scar caught that" |
| | ratio | 0.399 | |
| 10.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 124 | | totalSentences | 138 | | matches | | 0 | "The last bus left her" | | 1 | "Rory climbed the fence anyway," | | 2 | "The Heartstone sat against her" | | 3 | "Isolde knew the stones." | | 4 | "Isolde knew the grove." | | 5 | "That was the whole of" | | 6 | "Richmond Park stretched black in" | | 7 | "The lamps along the main" | | 8 | "She kept to the treeline," | | 9 | "The standing stones rose out" | | 10 | "Wildflowers carpeted the ground between" | | 11 | "They had no business blooming." | | 12 | "The air inside the ring" | | 13 | "Rory stepped through." | | 14 | "The park noise died." | | 15 | "Her own breath sounded too" | | 16 | "The name went nowhere." | | 17 | "It hit the flowers and" | | 18 | "She took another step." | | 19 | "The grass under her boots" |
| | ratio | 0.899 | |
| 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 | 56 | | technicalSentenceCount | 2 | | matches | | 0 | "Their heads now pointed inward, toward her, as if the stems had joints." | | 1 | "Carvings ran under her fingers, grooves worn shallow, shapes that might have been faces if she let her mind go there." |
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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 | |