| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.214 | | leniency | 0.429 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1285 | | 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) | |
| 72.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1285 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "echo" | | 1 | "furrowed" | | 2 | "weight" | | 3 | "pulse" | | 4 | "footsteps" | | 5 | "warmth" |
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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 | 133 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 133 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 144 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 4 | | totalWords | 1285 | | ratio | 0.003 | | matches | | 0 | "Midnight. Come alone." | | 1 | "love" |
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| 75.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 1 | | matches | | 0 | "Standing stones, Isolde called them, though they were wood, grey and furrowed and older than the city." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 1217 | | uniqueNames | 13 | | maxNameDensity | 0.9 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Sheen | 1 | | Gate | 1 | | Rory | 11 | | Golden | 1 | | Empress | 1 | | Isolde | 3 | | Heartstone | 2 | | Evan | 1 | | London | 1 | | Cardiff | 1 | | Swansea | 1 | | Nine | 3 | | Oak | 3 |
| | persons | | 0 | "Gate" | | 1 | "Rory" | | 2 | "Isolde" | | 3 | "Heartstone" | | 4 | "Evan" |
| | places | | 0 | "Sheen" | | 1 | "London" | | 2 | "Cardiff" | | 3 | "Oak" |
| | globalScore | 1 | | windowScore | 1 | |
| 74.24% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 2 | | matches | | 0 | "sounded like it was smiling" | | 1 | "sounded like her mother reading a word off" |
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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 | 1285 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 144 | | matches | | 0 | "check that she" | | 1 | "knew that trick" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 24.25 | | std | 23.34 | | cv | 0.963 | | sampleLengths | | 0 | 4 | | 1 | 72 | | 2 | 20 | | 3 | 3 | | 4 | 18 | | 5 | 75 | | 6 | 78 | | 7 | 3 | | 8 | 47 | | 9 | 1 | | 10 | 38 | | 11 | 11 | | 12 | 6 | | 13 | 61 | | 14 | 16 | | 15 | 2 | | 16 | 27 | | 17 | 7 | | 18 | 38 | | 19 | 11 | | 20 | 55 | | 21 | 2 | | 22 | 35 | | 23 | 36 | | 24 | 10 | | 25 | 23 | | 26 | 83 | | 27 | 8 | | 28 | 32 | | 29 | 2 | | 30 | 45 | | 31 | 19 | | 32 | 8 | | 33 | 6 | | 34 | 49 | | 35 | 13 | | 36 | 10 | | 37 | 30 | | 38 | 3 | | 39 | 62 | | 40 | 1 | | 41 | 31 | | 42 | 3 | | 43 | 40 | | 44 | 3 | | 45 | 1 | | 46 | 39 | | 47 | 1 | | 48 | 60 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 133 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 178 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 144 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1220 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.027049180327868853 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.001639344262295082 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 144 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 144 | | mean | 8.92 | | std | 8.58 | | cv | 0.961 | | sampleLengths | | 0 | 4 | | 1 | 10 | | 2 | 30 | | 3 | 7 | | 4 | 25 | | 5 | 5 | | 6 | 13 | | 7 | 2 | | 8 | 3 | | 9 | 4 | | 10 | 4 | | 11 | 10 | | 12 | 20 | | 13 | 1 | | 14 | 35 | | 15 | 19 | | 16 | 10 | | 17 | 17 | | 18 | 12 | | 19 | 39 | | 20 | 3 | | 21 | 2 | | 22 | 15 | | 23 | 20 | | 24 | 10 | | 25 | 1 | | 26 | 10 | | 27 | 2 | | 28 | 19 | | 29 | 1 | | 30 | 6 | | 31 | 4 | | 32 | 1 | | 33 | 6 | | 34 | 1 | | 35 | 3 | | 36 | 2 | | 37 | 22 | | 38 | 8 | | 39 | 13 | | 40 | 18 | | 41 | 3 | | 42 | 1 | | 43 | 7 | | 44 | 5 | | 45 | 2 | | 46 | 4 | | 47 | 14 | | 48 | 6 | | 49 | 3 |
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| 50.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 21 | | diversityRatio | 0.39436619718309857 | | totalSentences | 142 | | uniqueOpeners | 56 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 95 | | matches | | 0 | "Just a stone on a" | | 1 | "Soft, behind her and to" | | 2 | "Then the other." | | 3 | "Then, from the far side" |
| | ratio | 0.042 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 95 | | matches | | 0 | "She thumbed her torch on." | | 1 | "Her voice went nowhere." | | 2 | "It dropped at her feet" | | 3 | "She stepped through." | | 4 | "She checked her phone." | | 5 | "She was early." | | 6 | "She picked a spot near" | | 7 | "She clicked the torch off" | | 8 | "Her eyes adjusted." | | 9 | "She waited for the next" | | 10 | "It didn't come." | | 11 | "She shifted her heel against" | | 12 | "She did it once more," | | 13 | "Her own footstep, returned to" | | 14 | "She stood up." | | 15 | "She didn't decide to." | | 16 | "Her legs made the choice" | | 17 | "She stared at it." | | 18 | "She had sat on that" | | 19 | "She tapped the screen and" |
| | ratio | 0.4 | |
| 75.79% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 95 | | matches | | 0 | "The deer had gone." | | 1 | "Rory noticed that first, before" | | 2 | "She thumbed her torch on." | | 3 | "The beam found bracken, a" | | 4 | "Her voice went nowhere." | | 5 | "It dropped at her feet" | | 6 | "Isolde's message sat folded in" | | 7 | "The oaks rose out of" | | 8 | "Rory had walked between them" | | 9 | "She stepped through." | | 10 | "The air carried a flat," | | 11 | "The wildflowers still grew, bluebells" | | 12 | "The torchlight slid across them" | | 13 | "The name died the same" | | 14 | "She checked her phone." | | 15 | "She was early." | | 16 | "She picked a spot near" | | 17 | "She clicked the torch off" | | 18 | "Her eyes adjusted." | | 19 | "The pale smudge of cloud" |
| | ratio | 0.768 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 95 | | matches | | 0 | "Now, a quarter mile on," | | 1 | "Now she wanted to take" |
| | ratio | 0.021 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 51 | | technicalSentenceCount | 2 | | matches | | 0 | "Isolde's message sat folded in her jacket pocket, three words in green ink on paper that smelled of crushed nettles." | | 1 | "A gap in the foxgloves where the stems parted, as if something had pushed through, though the stems stood straight and unbroken." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |