| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 969 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 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) | |
| 84.52% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 969 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "echo" | | 1 | "velvet" | | 2 | "sense of" |
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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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 79 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 969 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 16 | | wordCount | 954 | | uniqueNames | 9 | | maxNameDensity | 0.42 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 4 | | Richmond | 1 | | Park | 1 | | October | 2 | | Aurora | 1 | | London | 1 | | Cardiff | 1 | | Closer | 1 | | Rory | 4 |
| | persons | | 0 | "Eva" | | 1 | "Aurora" | | 2 | "Closer" | | 3 | "Rory" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 45 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a mouth" | | 1 | "felt like exactly what it wanted" | | 2 | "sounded like it had missed her" |
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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 | 969 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 79 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 28.5 | | std | 23.5 | | cv | 0.825 | | sampleLengths | | 0 | 57 | | 1 | 14 | | 2 | 7 | | 3 | 61 | | 4 | 68 | | 5 | 15 | | 6 | 1 | | 7 | 70 | | 8 | 23 | | 9 | 5 | | 10 | 32 | | 11 | 19 | | 12 | 15 | | 13 | 4 | | 14 | 67 | | 15 | 21 | | 16 | 2 | | 17 | 55 | | 18 | 6 | | 19 | 38 | | 20 | 41 | | 21 | 9 | | 22 | 54 | | 23 | 10 | | 24 | 49 | | 25 | 20 | | 26 | 1 | | 27 | 2 | | 28 | 8 | | 29 | 33 | | 30 | 63 | | 31 | 15 | | 32 | 68 | | 33 | 16 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 76 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 171 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 79 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 957 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 36 | | adverbRatio | 0.03761755485893417 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01044932079414838 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 79 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 79 | | mean | 12.27 | | std | 11.17 | | cv | 0.911 | | sampleLengths | | 0 | 14 | | 1 | 19 | | 2 | 24 | | 3 | 4 | | 4 | 2 | | 5 | 8 | | 6 | 6 | | 7 | 1 | | 8 | 33 | | 9 | 4 | | 10 | 3 | | 11 | 21 | | 12 | 6 | | 13 | 31 | | 14 | 31 | | 15 | 15 | | 16 | 1 | | 17 | 11 | | 18 | 6 | | 19 | 29 | | 20 | 5 | | 21 | 3 | | 22 | 16 | | 23 | 5 | | 24 | 18 | | 25 | 5 | | 26 | 4 | | 27 | 21 | | 28 | 7 | | 29 | 1 | | 30 | 18 | | 31 | 15 | | 32 | 4 | | 33 | 26 | | 34 | 19 | | 35 | 5 | | 36 | 8 | | 37 | 9 | | 38 | 9 | | 39 | 3 | | 40 | 9 | | 41 | 2 | | 42 | 35 | | 43 | 9 | | 44 | 5 | | 45 | 6 | | 46 | 6 | | 47 | 2 | | 48 | 2 | | 49 | 34 |
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| 67.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.45569620253164556 | | totalSentences | 79 | | uniqueOpeners | 36 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 66 | | matches | | 0 | "Simply absent, like someone had" | | 1 | "Just the tree line, the" | | 2 | "Just a small persistent heat," | | 3 | "Somewhere ahead, past a stand" |
| | ratio | 0.061 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 66 | | matches | | 0 | "She'd had four bars at" | | 1 | "she said to no one" | | 2 | "She held onto that the" | | 3 | "Her voice landed strange, swallowed" | | 4 | "She turned in a slow" | | 5 | "She'd give it ten minutes." | | 6 | "She counted three heartbeats before" | | 7 | "she said, and hated how" | | 8 | "She noticed it the way" | | 9 | "She backed toward the standing" | | 10 | "She spun, searching for the" | | 11 | "She walked, fast, angling away" | | 12 | "It sounded fond." | | 13 | "It sounded like it had" | | 14 | "She needed the stones, needed" |
| | ratio | 0.227 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 45 | | totalSentences | 66 | | matches | | 0 | "The standing stones didn't look" | | 1 | "Rory checked her phone." | | 2 | "She'd had four bars at" | | 3 | "she said to no one" | | 4 | "The pendant sat cold against" | | 5 | "She held onto that the" | | 6 | "The wildflowers shouldn't have been" | | 7 | "Eva had said the grove" | | 8 | "Eva hadn't mentioned that it" | | 9 | "Her voice landed strange, swallowed" | | 10 | "She turned in a slow" | | 11 | "The oaks marking the boundary" | | 12 | "She'd give it ten minutes." | | 13 | "A twig snapped behind her." | | 14 | "Rory didn't turn immediately." | | 15 | "Years of walking home alone" | | 16 | "She counted three heartbeats before" | | 17 | "she said, and hated how" | | 18 | "The flowers moved wrong." | | 19 | "She noticed it the way" |
| | ratio | 0.682 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 66 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 30 | | technicalSentenceCount | 7 | | matches | | 0 | "The foxglove nearest her boot bent sideways, slow, deliberate, as though something crouched low were pushing through the stems." | | 1 | "The boundary had rearranged itself, or she had, because now the oaks stood in a different configuration entirely, closer together, more of them than she remembe…" | | 2 | "A long, slow drag of air, in and out, coming from a spot between two of the oaks where the shadow pooled thicker than it should, thick as spilled ink, thick as …" | | 3 | "The flowers bent toward her path now, all of them, a slow-motion ripple that followed her steps like something tracking scent." | | 4 | "Behind her, low and almost gentle, a voice that wasn't a voice pressed itself into the space behind her ears." | | 5 | "The pendant burned properly now, a bright localized heat that made her gasp and yank her jumper away from her skin." | | 6 | "Somewhere ahead, past a stand of oaks that hadn't been there a moment ago, the darkness between the trunks began to thin, to open, to breathe out something that…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 6 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.333 | | effectiveRatio | 0.333 | |