| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 63.02% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1217 | | totalAiIsmAdverbs | 9 | | found | | | highlights | | 0 | "suddenly" | | 1 | "slowly" | | 2 | "very" | | 3 | "softly" |
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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) | |
| 75.35% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1217 | | totalAiIsms | 6 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "perfect" | | 3 | "lurch" | | 4 | "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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 116 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 118 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 37 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1217 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 1209 | | uniqueNames | 17 | | maxNameDensity | 0.83 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Eva" | | discoveredNames | | Wrong | 2 | | Hour | 1 | | Rory | 10 | | Petersham | 1 | | Road | 1 | | Eva | 6 | | Park | 1 | | Heartstone | 1 | | Tuesday | 1 | | October | 2 | | Partridges | 1 | | Richmond | 2 | | Hill | 1 | | English | 1 | | London | 3 | | Sunday | 1 | | Evan | 1 |
| | persons | | 0 | "Wrong" | | 1 | "Rory" | | 2 | "Eva" | | 3 | "Evan" |
| | places | | 0 | "Hour" | | 1 | "Petersham" | | 2 | "Road" | | 3 | "Park" | | 4 | "October" | | 5 | "Partridges" | | 6 | "Richmond" | | 7 | "Hill" | | 8 | "London" |
| | globalScore | 1 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | 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 | 1217 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 118 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 32.89 | | std | 28.62 | | cv | 0.87 | | sampleLengths | | 0 | 3 | | 1 | 41 | | 2 | 14 | | 3 | 7 | | 4 | 69 | | 5 | 80 | | 6 | 43 | | 7 | 7 | | 8 | 87 | | 9 | 78 | | 10 | 10 | | 11 | 2 | | 12 | 84 | | 13 | 20 | | 14 | 49 | | 15 | 15 | | 16 | 52 | | 17 | 32 | | 18 | 11 | | 19 | 76 | | 20 | 14 | | 21 | 21 | | 22 | 30 | | 23 | 1 | | 24 | 17 | | 25 | 9 | | 26 | 76 | | 27 | 3 | | 28 | 17 | | 29 | 8 | | 30 | 60 | | 31 | 1 | | 32 | 72 | | 33 | 59 | | 34 | 39 | | 35 | 5 | | 36 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 116 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 187 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 118 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1211 | | adjectiveStacks | 1 | | stackExamples | | 0 | "silver-white, leafless, its" |
| | adverbCount | 44 | | adverbRatio | 0.03633360858794385 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007431874483897605 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 118 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 118 | | mean | 10.31 | | std | 9.85 | | cv | 0.955 | | sampleLengths | | 0 | 19 | | 1 | 25 | | 2 | 4 | | 3 | 10 | | 4 | 7 | | 5 | 27 | | 6 | 20 | | 7 | 22 | | 8 | 3 | | 9 | 29 | | 10 | 28 | | 11 | 5 | | 12 | 4 | | 13 | 6 | | 14 | 3 | | 15 | 2 | | 16 | 6 | | 17 | 37 | | 18 | 7 | | 19 | 3 | | 20 | 13 | | 21 | 12 | | 22 | 25 | | 23 | 22 | | 24 | 1 | | 25 | 11 | | 26 | 1 | | 27 | 2 | | 28 | 3 | | 29 | 3 | | 30 | 35 | | 31 | 22 | | 32 | 1 | | 33 | 2 | | 34 | 9 | | 35 | 6 | | 36 | 3 | | 37 | 1 | | 38 | 2 | | 39 | 12 | | 40 | 33 | | 41 | 21 | | 42 | 18 | | 43 | 1 | | 44 | 2 | | 45 | 17 | | 46 | 3 | | 47 | 9 | | 48 | 8 | | 49 | 12 |
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| 68.36% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.4915254237288136 | | totalSentences | 118 | | uniqueOpeners | 58 | |
| 37.45% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 89 | | matches | | 0 | "Just the oaks, just the" |
| | ratio | 0.011 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 89 | | matches | | 0 | "It had gone warm the" | | 1 | "She should turn back." | | 2 | "They mark the boundary." | | 3 | "You find them, you go" | | 4 | "Her voice came out flat," | | 5 | "She took another step, and" | | 6 | "She did not pick it" | | 7 | "She stepped over it, and" | | 8 | "She had not thought about" | | 9 | "She thought about her now," | | 10 | "Her mother's kitchen on a" | | 11 | "She moved toward the gap" | | 12 | "She stopped walking." | | 13 | "She had promised herself she" | | 14 | "She had run from Evan," | | 15 | "She lifted the pendant higher." |
| | ratio | 0.18 | |
| 94.83% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 89 | | matches | | 0 | "The Wrong Hour Rory's fingers" | | 1 | "It had gone warm the" | | 2 | "She should turn back." | | 3 | "The sensible thing, the smart" | | 4 | "The sensible thing had not" | | 5 | "Richmond Park spread out around" | | 6 | "London's glow hung on the" | | 7 | "These grew in a ring," | | 8 | "They mark the boundary." | | 9 | "You find them, you go" | | 10 | "Eva had known about the" | | 11 | "Eva had known a great" | | 12 | "Rory stepped between the first" | | 13 | "The air changed." | | 14 | "That was the first wrong" | | 15 | "This was a shift in" | | 16 | "The grass beneath her boots" | | 17 | "Wildflowers bloomed in a tight," | | 18 | "The smell hit her next," | | 19 | "Something almost animal beneath it," |
| | ratio | 0.73 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 45.45% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 6 | | matches | | 0 | "These grew in a ring, eight of them, their trunks grey and heavy with age, their roots buckling the earth into low ridges that felt deliberate under her boots." | | 1 | "This was a shift in the fundamental texture of the world, a softening, as if she had stepped from a solid floor onto a sponge." | | 2 | "Wildflowers bloomed in a tight, impossible ring around the first oak, their petals faintly luminous, a dozen different species that should not have been able to…" | | 3 | "The smell hit her next, thick and sweet, a perfume that had no business being in a London park at this hour." | | 4 | "She thought about her now, standing in a circle of ancient oaks at an hour that did not feel like any hour she had ever lived through, and the homesickness was …" | | 5 | "Running, she understood now with a calm that felt borrowed from someone braver than herself, would only make her easier to chase through the long grass." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "Rory whispered (whisper)" |
| | dialogueSentences | 4 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |