| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.70% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1888 | | totalAiIsmAdverbs | 2 | | 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) | |
| 60.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1888 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "pulse" | | 1 | "silence" | | 2 | "echo" | | 3 | "trembled" | | 4 | "measured" | | 5 | "whisper" | | 6 | "could feel" | | 7 | "familiar" | | 8 | "lilt" | | 9 | "perfect" | | 10 | "vibrated" | | 11 | "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 | 237 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 237 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 249 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1886 | | ratio | 0 | | matches | (empty) | |
| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "There was a shine where its face should be—not eyes, Rory told herself, only the wet gleam of bark." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1823 | | uniqueNames | 10 | | maxNameDensity | 1.26 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Park | 2 | | London | 2 | | Golden | 1 | | Empress | 1 | | Heartstone | 6 | | October | 1 | | Rory | 23 | | Welsh | 1 | | Cardiff | 2 | | Richmond | 2 |
| | persons | | | places | | 0 | "Park" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Richmond" |
| | globalScore | 0.869 | | windowScore | 0.833 | |
| 79.58% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 142 | | glossingSentenceCount | 4 | | matches | | 0 | "seemed farther away than it should have been" | | 1 | "appeared, empty except for one word" | | 2 | "sounded like dry leaves dragged over stone" | | 3 | "appeared just wide enough" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.53 | | wordCount | 1886 | | matches | | 0 | "not moved, exactly, but changed their angles" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 249 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 129 | | mean | 14.62 | | std | 14.29 | | cv | 0.977 | | sampleLengths | | 0 | 8 | | 1 | 51 | | 2 | 17 | | 3 | 54 | | 4 | 9 | | 5 | 15 | | 6 | 49 | | 7 | 36 | | 8 | 4 | | 9 | 35 | | 10 | 4 | | 11 | 1 | | 12 | 13 | | 13 | 13 | | 14 | 5 | | 15 | 5 | | 16 | 44 | | 17 | 4 | | 18 | 8 | | 19 | 10 | | 20 | 42 | | 21 | 5 | | 22 | 9 | | 23 | 6 | | 24 | 13 | | 25 | 23 | | 26 | 7 | | 27 | 21 | | 28 | 4 | | 29 | 31 | | 30 | 40 | | 31 | 6 | | 32 | 9 | | 33 | 31 | | 34 | 7 | | 35 | 7 | | 36 | 1 | | 37 | 2 | | 38 | 1 | | 39 | 31 | | 40 | 6 | | 41 | 41 | | 42 | 6 | | 43 | 11 | | 44 | 2 | | 45 | 25 | | 46 | 1 | | 47 | 4 | | 48 | 33 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 237 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 294 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 249 | | ratio | 0.008 | | matches | | 0 | "The stones themselves had shifted, she thought—not moved, exactly, but changed their angles." | | 1 | "There was a shine where its face should be—not eyes, Rory told herself, only the wet gleam of bark." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 306 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Tall, weather-scoured slabs" |
| | adverbCount | 10 | | adverbRatio | 0.032679738562091505 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.00980392156862745 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 249 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 249 | | mean | 7.57 | | std | 4.84 | | cv | 0.639 | | sampleLengths | | 0 | 8 | | 1 | 17 | | 2 | 15 | | 3 | 10 | | 4 | 9 | | 5 | 8 | | 6 | 9 | | 7 | 17 | | 8 | 14 | | 9 | 7 | | 10 | 16 | | 11 | 9 | | 12 | 2 | | 13 | 1 | | 14 | 3 | | 15 | 9 | | 16 | 2 | | 17 | 8 | | 18 | 18 | | 19 | 7 | | 20 | 7 | | 21 | 7 | | 22 | 13 | | 23 | 6 | | 24 | 7 | | 25 | 10 | | 26 | 4 | | 27 | 6 | | 28 | 20 | | 29 | 4 | | 30 | 5 | | 31 | 4 | | 32 | 1 | | 33 | 7 | | 34 | 6 | | 35 | 13 | | 36 | 5 | | 37 | 5 | | 38 | 12 | | 39 | 2 | | 40 | 3 | | 41 | 10 | | 42 | 17 | | 43 | 4 | | 44 | 2 | | 45 | 2 | | 46 | 4 | | 47 | 5 | | 48 | 5 | | 49 | 6 |
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| 43.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 17 | | diversityRatio | 0.2217741935483871 | | totalSentences | 248 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 210 | | matches | | 0 | "Too measured for that." | | 1 | "Of course every sound had" | | 2 | "Then she lowered the phone." | | 3 | "Then all of them, their" | | 4 | "Then she remembered the distance" | | 5 | "Then the shine blinked." | | 6 | "Then she stumbled onto gravel." | | 7 | "Only trees stood beyond the" | | 8 | "Then, from somewhere among the" |
| | ratio | 0.043 | |
| 92.38% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 67 | | totalSentences | 210 | | matches | | 0 | "Their tops disappeared into the" | | 1 | "She looked down at the" | | 2 | "I can tell you who" | | 3 | "She touched it through the" | | 4 | "It had been that way" | | 5 | "She could still see the" | | 6 | "She had parked nearby." | | 7 | "She checked the time." | | 8 | "Her phone showed one bar" | | 9 | "she murmured, because the silence" | | 10 | "She stepped between two stones." | | 11 | "It was October." | | 12 | "She crouched and touched one," | | 13 | "She stood again, listening." | | 14 | "It had been shut away." | | 15 | "It was smaller than it" | | 16 | "She could see the opening" | | 17 | "She had been inside for" | | 18 | "Her voice went out cleanly," | | 19 | "She lifted her phone and" |
| | ratio | 0.319 | |
| 60.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 168 | | totalSentences | 210 | | matches | | 0 | "The standing stones were not" | | 1 | "Rory checked her phone again" | | 2 | "Richmond Park sprawled around her" | | 3 | "Here, the cold had swallowed" | | 4 | "The map showed her on" | | 5 | "The road under her boots" | | 6 | "Their tops disappeared into the" | | 7 | "The gaps between them looked" | | 8 | "She looked down at the" | | 9 | "I can tell you who" | | 10 | "The message had arrived an" | | 11 | "That was enough to make" | | 12 | "The Heartstone rested beneath her" | | 13 | "She touched it through the" | | 14 | "The crimson gem was thumbnail-sized," | | 15 | "It had been that way" | | 16 | "A pulse, barely there." | | 17 | "Rory glanced back toward the" | | 18 | "She could still see the" | | 19 | "She had parked nearby." |
| | ratio | 0.8 | |
| 23.81% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 210 | | matches | | 0 | "Whoever sent it knew about" |
| | ratio | 0.005 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 69 | | technicalSentenceCount | 2 | | matches | | 0 | "The words carried the same gentle Welsh lilt, the same little rise at the end of a sentence that meant her mother was smiling." | | 1 | "A childhood memory flashed across her mind: the crescent scar on her wrist, the broken glass, her mother pressing a cloth to the cut while she insisted she wasn…" |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, her voice too thin" |
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| 91.18% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 17 | | tagDensity | 0.294 | | leniency | 0.588 | | rawRatio | 0.2 | | effectiveRatio | 0.118 | |