| 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 | 1293 | | 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) | |
| 69.06% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1293 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "warmth" | | 1 | "pulsed" | | 2 | "churned" | | 3 | "pulse" | | 4 | "weight" | | 5 | "echo" | | 6 | "silence" |
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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 | 159 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 159 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 169 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 27 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1293 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1241 | | uniqueNames | 13 | | maxNameDensity | 1.05 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "One" | | discoveredNames | | Richmond | 2 | | Park | 2 | | Heartstone | 2 | | Pendant | 1 | | Isolde | 1 | | Eva | 1 | | Rory | 13 | | Cardiff | 1 | | London | 1 | | One | 8 | | Pause | 4 | | One-one | 5 | | Eight | 3 |
| | persons | | 0 | "Pendant" | | 1 | "Eva" | | 2 | "Rory" | | 3 | "Pause" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Isolde" | | 3 | "Cardiff" | | 4 | "London" | | 5 | "One" |
| | globalScore | 0.976 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | 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 | 1293 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 169 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 20.52 | | std | 18.09 | | cv | 0.882 | | sampleLengths | | 0 | 18 | | 1 | 44 | | 2 | 35 | | 3 | 5 | | 4 | 42 | | 5 | 9 | | 6 | 7 | | 7 | 12 | | 8 | 48 | | 9 | 20 | | 10 | 54 | | 11 | 5 | | 12 | 37 | | 13 | 48 | | 14 | 25 | | 15 | 5 | | 16 | 7 | | 17 | 39 | | 18 | 36 | | 19 | 2 | | 20 | 22 | | 21 | 37 | | 22 | 5 | | 23 | 1 | | 24 | 42 | | 25 | 7 | | 26 | 17 | | 27 | 6 | | 28 | 4 | | 29 | 39 | | 30 | 3 | | 31 | 18 | | 32 | 61 | | 33 | 9 | | 34 | 9 | | 35 | 3 | | 36 | 31 | | 37 | 3 | | 38 | 48 | | 39 | 4 | | 40 | 47 | | 41 | 14 | | 42 | 8 | | 43 | 59 | | 44 | 2 | | 45 | 8 | | 46 | 2 | | 47 | 47 | | 48 | 8 | | 49 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 159 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 209 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 169 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1250 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 25 | | adverbRatio | 0.02 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 169 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 169 | | mean | 7.65 | | std | 5.66 | | cv | 0.74 | | sampleLengths | | 0 | 18 | | 1 | 8 | | 2 | 14 | | 3 | 2 | | 4 | 10 | | 5 | 3 | | 6 | 7 | | 7 | 10 | | 8 | 7 | | 9 | 7 | | 10 | 1 | | 11 | 1 | | 12 | 1 | | 13 | 1 | | 14 | 7 | | 15 | 5 | | 16 | 6 | | 17 | 2 | | 18 | 22 | | 19 | 2 | | 20 | 2 | | 21 | 8 | | 22 | 6 | | 23 | 1 | | 24 | 2 | | 25 | 7 | | 26 | 12 | | 27 | 10 | | 28 | 5 | | 29 | 13 | | 30 | 20 | | 31 | 6 | | 32 | 2 | | 33 | 3 | | 34 | 9 | | 35 | 7 | | 36 | 2 | | 37 | 2 | | 38 | 15 | | 39 | 6 | | 40 | 8 | | 41 | 14 | | 42 | 5 | | 43 | 7 | | 44 | 5 | | 45 | 5 | | 46 | 20 | | 47 | 20 | | 48 | 14 | | 49 | 6 |
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| 60.52% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.39880952380952384 | | totalSentences | 168 | | uniqueOpeners | 67 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 126 | | matches | | 0 | "Then wet earth." | | 1 | "Then iron, sharp at the" |
| | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 126 | | matches | | 0 | "She stood, brushed ice crystals" | | 1 | "Her voice flattened against the" | | 2 | "She pulled the note from" | | 3 | "Her boots found frozen mud," | | 4 | "She spoke to hear a" | | 5 | "She stood and walked with" | | 6 | "She had never seen this" | | 7 | "She hissed and dragged the" | | 8 | "Her phone screen lit her" | | 9 | "She locked the screen." | | 10 | "Her wristwatch ticked against the" | | 11 | "She counted from the stone" | | 12 | "She counted back." | | 13 | "Her own pulse hammered in" | | 14 | "She cupped the pendant and" | | 15 | "Her eyes built trees from" | | 16 | "She looked straight at it" | | 17 | "She looked toward the grass" | | 18 | "She shifted her weight." | | 19 | "Hers came short and fast." |
| | ratio | 0.246 | |
| 71.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 98 | | totalSentences | 126 | | matches | | 0 | "Rory swung a leg over" | | 1 | "She stood, brushed ice crystals" | | 2 | "A fox crossed under a" | | 3 | "The Heartstone Pendant knocked against" | | 4 | "Heat leaked through her jumper" | | 5 | "The rhythm refused to match" | | 6 | "Her voice flattened against the" | | 7 | "She pulled the note from" | | 8 | "Words scored deep enough to" | | 9 | "Rory folded the note along" | | 10 | "The torch beam cut a" | | 11 | "Oak trunks crowded the path." | | 12 | "Branches locked overhead and stripped" | | 13 | "Her boots found frozen mud," | | 14 | "A scent built as she" | | 15 | "Wildflowers pushed through frost along" | | 16 | "Petals open to a night" | | 17 | "Rory crouched and touched a" | | 18 | "Warmth met her fingertip, absurd" | | 19 | "The flower bent toward her" |
| | ratio | 0.778 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 126 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 1 | | matches | | 0 | "Rory swung a leg over the Richmond Park railings and dropped into grass that crunched under her boots." |
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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 | |