| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1232 | | 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) | |
| 51.30% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1232 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "charged" | | 1 | "echo" | | 2 | "pulse" | | 3 | "measured" | | 4 | "could feel" | | 5 | "weight" | | 6 | "warmth" | | 7 | "familiar" | | 8 | "throbbed" |
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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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 137 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 142 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1230 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 88.07% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 1211 | | uniqueNames | 5 | | maxNameDensity | 1.24 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Carter | 1 | | Richmond | 1 | | Park | 1 | | Heartstone | 1 | | Rory | 15 |
| | persons | | 0 | "Carter" | | 1 | "Heartstone" | | 2 | "Rory" |
| | places | | | globalScore | 0.881 | | windowScore | 1 | |
| 99.49% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 99 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared beneath it" | | 1 | "felt like a coin held against a flame" |
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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 | 1230 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 142 | | matches | | 0 | "checking that her" | | 1 | "passed that bench" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 18.64 | | std | 14.5 | | cv | 0.778 | | sampleLengths | | 0 | 14 | | 1 | 49 | | 2 | 41 | | 3 | 25 | | 4 | 9 | | 5 | 12 | | 6 | 36 | | 7 | 56 | | 8 | 5 | | 9 | 35 | | 10 | 16 | | 11 | 34 | | 12 | 6 | | 13 | 7 | | 14 | 22 | | 15 | 9 | | 16 | 56 | | 17 | 19 | | 18 | 16 | | 19 | 20 | | 20 | 3 | | 21 | 9 | | 22 | 14 | | 23 | 25 | | 24 | 29 | | 25 | 41 | | 26 | 4 | | 27 | 19 | | 28 | 17 | | 29 | 12 | | 30 | 2 | | 31 | 2 | | 32 | 42 | | 33 | 8 | | 34 | 25 | | 35 | 6 | | 36 | 21 | | 37 | 26 | | 38 | 2 | | 39 | 6 | | 40 | 15 | | 41 | 2 | | 42 | 22 | | 43 | 30 | | 44 | 4 | | 45 | 41 | | 46 | 8 | | 47 | 51 | | 48 | 8 | | 49 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 137 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 185 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 142 | | ratio | 0.014 | | matches | | 0 | "The park’s night sounds continued behind her—a car on a distant road, wind stirring the high branches—but nothing answered from ahead." | | 1 | "White petals, yellow petals, blue petals; none of them folded against the cold." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1213 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 30 | | adverbRatio | 0.0247320692497939 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.00247320692497939 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 142 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 142 | | mean | 8.66 | | std | 5.14 | | cv | 0.593 | | sampleLengths | | 0 | 14 | | 1 | 19 | | 2 | 21 | | 3 | 9 | | 4 | 11 | | 5 | 9 | | 6 | 21 | | 7 | 7 | | 8 | 7 | | 9 | 11 | | 10 | 3 | | 11 | 6 | | 12 | 12 | | 13 | 2 | | 14 | 21 | | 15 | 13 | | 16 | 3 | | 17 | 19 | | 18 | 10 | | 19 | 11 | | 20 | 13 | | 21 | 5 | | 22 | 10 | | 23 | 11 | | 24 | 14 | | 25 | 4 | | 26 | 10 | | 27 | 2 | | 28 | 11 | | 29 | 17 | | 30 | 6 | | 31 | 2 | | 32 | 4 | | 33 | 7 | | 34 | 4 | | 35 | 18 | | 36 | 9 | | 37 | 3 | | 38 | 17 | | 39 | 19 | | 40 | 17 | | 41 | 4 | | 42 | 15 | | 43 | 12 | | 44 | 4 | | 45 | 8 | | 46 | 12 | | 47 | 3 | | 48 | 9 | | 49 | 6 |
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| 45.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.2323943661971831 | | totalSentences | 142 | | uniqueOpeners | 33 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 123 | | matches | | 0 | "Instead she saw more trees," | | 1 | "Then she took out her" | | 2 | "Then the thing on its" |
| | ratio | 0.024 | |
| 80.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 43 | | totalSentences | 123 | | matches | | 0 | "She had come to Richmond" | | 1 | "She pressed the pendant through" | | 2 | "Its silver chain shifted against" | | 3 | "Her voice came back from" | | 4 | "She drew the torch from" | | 5 | "Her boots sank into soft" | | 6 | "She raised her torch." | | 7 | "Its beam caught pale bark," | | 8 | "She pressed it with her" | | 9 | "She opened the compass." | | 10 | "They looked less like a" | | 11 | "She had read about standing" | | 12 | "She took a photograph." | | 13 | "They had not moved." | | 14 | "She took another picture, this" | | 15 | "She swung the torch that" | | 16 | "Its beam crossed flowers, earth," | | 17 | "She moved to the nearest" | | 18 | "She could feel the chain" | | 19 | "She brought the torch closer." |
| | ratio | 0.35 | |
| 37.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 123 | | matches | | 0 | "Aurora Carter left the marked" | | 1 | "She had come to Richmond" | | 2 | "The rest of the park" | | 3 | "The Heartstone had warmed at" | | 4 | "Rory had marked each spot" | | 5 | "The points had narrowed to" | | 6 | "She pressed the pendant through" | | 7 | "Its silver chain shifted against" | | 8 | "The crimson stone held a" | | 9 | "Her voice came back from" | | 10 | "The park’s night sounds continued" | | 11 | "She drew the torch from" | | 12 | "The ground dipped." | | 13 | "Her boots sank into soft" | | 14 | "Wildflowers crowded its edges, their" | | 15 | "Rory turned and looked back." | | 16 | "The two oaks stood behind" | | 17 | "She raised her torch." | | 18 | "Its beam caught pale bark," | | 19 | "A small crescent scar crossed" |
| | ratio | 0.846 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 123 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 56 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 6 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 1 | | effectiveRatio | 0.333 | |