| 33.33% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said softly [softly]" |
| | dialogueSentences | 11 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0.167 | | effectiveRatio | 0.167 | |
| 85.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1071 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "softly" | | 1 | "very" | | 2 | "really" |
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| 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) | |
| 62.65% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1071 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "silence" | | 1 | "pulsed" | | 2 | "flicker" | | 3 | "warmth" | | 4 | "absolutely" | | 5 | "perfect" |
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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 | 1 | | narrationSentences | 102 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 102 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 32 | | totalWords | 1071 | | ratio | 0.03 | | matches | | 0 | "When the evidence changes, the witness is the problem." | | 1 | "The witness is the problem." | | 2 | "\"Aurora.\"" | | 3 | "\"Aurora, love, you've come so far. Come and let me look at you.\"" | | 4 | "love." | | 5 | "\"Come along now,\"" |
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| 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 | 27 | | wordCount | 1021 | | uniqueNames | 14 | | maxNameDensity | 0.78 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 1 | | Grove | 1 | | Rory | 8 | | March | 1 | | Park | 2 | | Heathrow | 1 | | Meaning | 2 | | Evan | 1 | | Lie | 1 | | Like | 3 | | Carter | 1 | | Cardiff | 1 | | Richmond | 2 | | Yu-Fei | 2 |
| | persons | | 0 | "Rory" | | 1 | "Meaning" | | 2 | "Evan" | | 3 | "Like" | | 4 | "Carter" | | 5 | "Yu-Fei" |
| | places | | 0 | "March" | | 1 | "Park" | | 2 | "Heathrow" | | 3 | "Cardiff" | | 4 | "Richmond" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 1 | | matches | | 0 | "seemed gentle now seemed expectant, the way a room feels when everyone's stopped talking the moment you enter" |
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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 | 1071 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 108 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 24.91 | | std | 22.13 | | cv | 0.888 | | sampleLengths | | 0 | 8 | | 1 | 49 | | 2 | 4 | | 3 | 64 | | 4 | 9 | | 5 | 56 | | 6 | 6 | | 7 | 3 | | 8 | 64 | | 9 | 1 | | 10 | 16 | | 11 | 32 | | 12 | 3 | | 13 | 4 | | 14 | 10 | | 15 | 50 | | 16 | 42 | | 17 | 14 | | 18 | 3 | | 19 | 37 | | 20 | 6 | | 21 | 47 | | 22 | 4 | | 23 | 66 | | 24 | 6 | | 25 | 29 | | 26 | 15 | | 27 | 64 | | 28 | 11 | | 29 | 3 | | 30 | 56 | | 31 | 5 | | 32 | 1 | | 33 | 36 | | 34 | 11 | | 35 | 8 | | 36 | 13 | | 37 | 39 | | 38 | 62 | | 39 | 55 | | 40 | 27 | | 41 | 7 | | 42 | 25 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 102 | | matches | | |
| 85.71% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 175 | | matches | | 0 | "were starting" | | 1 | "was standing" | | 2 | "were screaming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 108 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 127 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 5 | | adverbRatio | 0.03937007874015748 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 9.92 | | std | 9.7 | | cv | 0.978 | | sampleLengths | | 0 | 8 | | 1 | 12 | | 2 | 18 | | 3 | 19 | | 4 | 3 | | 5 | 1 | | 6 | 7 | | 7 | 5 | | 8 | 17 | | 9 | 3 | | 10 | 15 | | 11 | 17 | | 12 | 9 | | 13 | 12 | | 14 | 12 | | 15 | 24 | | 16 | 8 | | 17 | 6 | | 18 | 2 | | 19 | 1 | | 20 | 9 | | 21 | 2 | | 22 | 7 | | 23 | 10 | | 24 | 25 | | 25 | 11 | | 26 | 1 | | 27 | 6 | | 28 | 1 | | 29 | 9 | | 30 | 6 | | 31 | 14 | | 32 | 12 | | 33 | 3 | | 34 | 4 | | 35 | 10 | | 36 | 2 | | 37 | 22 | | 38 | 18 | | 39 | 3 | | 40 | 5 | | 41 | 4 | | 42 | 14 | | 43 | 18 | | 44 | 6 | | 45 | 14 | | 46 | 3 | | 47 | 6 | | 48 | 22 | | 49 | 3 |
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| 74.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.48148148148148145 | | totalSentences | 108 | | uniqueOpeners | 52 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 79 | | matches | | 0 | "Somewhere behind her, a twig" | | 1 | "Instead there was nothing, a" | | 2 | "Instead she looked at the" | | 3 | "Then, at the very edge" | | 4 | "Of course it did." |
| | ratio | 0.063 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 21 | | totalSentences | 79 | | matches | | 0 | "She picked her way deeper," | | 1 | "Her own voice came back" | | 2 | "She set it on a" | | 3 | "She turned to go." | | 4 | "It led away from the" | | 5 | "She was certain." | | 6 | "She'd circled this clearing twice." | | 7 | "Her father had a phrase" | | 8 | "She didn't move." | | 9 | "she said softly" | | 10 | "She was not alone." | | 11 | "Her heart slammed against her" | | 12 | "She saw almost nothing." | | 13 | "She took a step backwards" | | 14 | "It was the worst thing" | | 15 | "It came again, closer, from" | | 16 | "Her name, her full name," | | 17 | "It came from the new" | | 18 | "She'd left it on the" | | 19 | "her mother's voice cooed, and" |
| | ratio | 0.266 | |
| 99.24% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 79 | | matches | | 0 | "The standing stones weren't where" | | 1 | "Rory turned a slow circle," | | 2 | "The pendant lay cool against" | | 3 | "That, at least, made sense." | | 4 | "Yu-Fei had been clear: bring" | | 5 | "A simple errand." | | 6 | "A favour, the old woman" | | 7 | "The obvious questions were starting" | | 8 | "She picked her way deeper," | | 9 | "Bluebells, foxgloves, things she had" | | 10 | "The glow painted her hands" | | 11 | "Richmond Park at night should" | | 12 | "A plane stitching its way" | | 13 | "The hum of a city" | | 14 | "The quiet had crept up" | | 15 | "Her own voice came back" | | 16 | "Rory knelt and unclasped the" | | 17 | "The pendant pulsed once in" | | 18 | "She set it on a" | | 19 | "She turned to go." |
| | ratio | 0.722 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 79 | | matches | | 0 | "Now they crowded together, trunks" | | 1 | "Even in March, even under" |
| | ratio | 0.025 | |
| 7.72% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 7 | | matches | | 0 | "Bluebells, foxgloves, things she had no names for, all of them faintly luminous, as though they'd swallowed daylight and forgotten to let it go." | | 1 | "A clear gap between two oaks, the grass beyond it darker than the rest, beaten flat as though many feet had passed." | | 2 | "The glow that had seemed gentle now seemed expectant, the way a room feels when everyone's stopped talking the moment you enter." | | 3 | "It was the worst thing she'd heard in her life, that laugh, bright and delighted and absolutely empty, a recording of joy played by something that had only ever…" | | 4 | "It came again, closer, from a different direction, as though the child had crossed twenty feet of clearing between one breath and the next." | | 5 | "Lined on both sides by pale, patient shapes that had been there the whole time, waiting with the terrible courtesy of things that knew their guest could not lea…" | | 6 | "It seared her palm, blazing crimson, and behind her the oaks groaned and shuddered and began, with a sound like tearing roots, to pull apart." |
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| 41.67% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 1 | | matches | | 0 | "her mother's voice cooed, and a hand emerged from the dark at the path's mouth, long-fingered, white as a peeled root, palm up, beckoning" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 3 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "Rory whispered (whisper)" | | 2 | "her mother's voice cooed (coo)" |
| | dialogueSentences | 11 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0.6 | | effectiveRatio | 0.545 | |