| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.17% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1764 | | 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) | |
| 77.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1764 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "pulsed" | | 1 | "pulse" | | 2 | "warmth" | | 3 | "trembled" | | 4 | "stomach" |
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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 | 196 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 196 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 199 | | 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 | 0 | | markdownWords | 0 | | totalWords | 1764 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 93.05% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 42 | | wordCount | 1756 | | uniqueNames | 16 | | maxNameDensity | 1.14 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | Heartstone | 1 | | Rory | 20 | | Richmond | 1 | | Park | 1 | | London | 1 | | Fae | 1 | | Grove | 1 | | Silas | 3 | | Golden | 2 | | Empress | 2 | | Hel | 1 | | Eva | 2 | | Barking | 1 | | Yu-Fei | 3 | | Welsh | 1 | | English | 1 |
| | persons | | 0 | "Rory" | | 1 | "Silas" | | 2 | "Eva" | | 3 | "Yu-Fei" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "London" | | 3 | "Fae" | | 4 | "Grove" | | 5 | "Golden" | | 6 | "English" |
| | globalScore | 0.931 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 123 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.567 | | wordCount | 1764 | | matches | | 0 | "not like skin waking up, but like something taking root" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 199 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 67 | | mean | 26.33 | | std | 21.86 | | cv | 0.83 | | sampleLengths | | 0 | 79 | | 1 | 15 | | 2 | 84 | | 3 | 69 | | 4 | 10 | | 5 | 20 | | 6 | 8 | | 7 | 51 | | 8 | 14 | | 9 | 68 | | 10 | 38 | | 11 | 6 | | 12 | 36 | | 13 | 3 | | 14 | 27 | | 15 | 8 | | 16 | 6 | | 17 | 56 | | 18 | 27 | | 19 | 2 | | 20 | 6 | | 21 | 36 | | 22 | 12 | | 23 | 31 | | 24 | 3 | | 25 | 33 | | 26 | 2 | | 27 | 36 | | 28 | 35 | | 29 | 17 | | 30 | 2 | | 31 | 43 | | 32 | 4 | | 33 | 62 | | 34 | 9 | | 35 | 31 | | 36 | 6 | | 37 | 36 | | 38 | 27 | | 39 | 6 | | 40 | 46 | | 41 | 3 | | 42 | 66 | | 43 | 1 | | 44 | 35 | | 45 | 5 | | 46 | 3 | | 47 | 34 | | 48 | 5 | | 49 | 12 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 196 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 281 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 199 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1759 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 55 | | adverbRatio | 0.03126776577600909 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0022740193291642978 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 199 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 199 | | mean | 8.86 | | std | 6.52 | | cv | 0.735 | | sampleLengths | | 0 | 7 | | 1 | 16 | | 2 | 11 | | 3 | 5 | | 4 | 23 | | 5 | 17 | | 6 | 5 | | 7 | 10 | | 8 | 23 | | 9 | 23 | | 10 | 24 | | 11 | 8 | | 12 | 6 | | 13 | 10 | | 14 | 13 | | 15 | 15 | | 16 | 12 | | 17 | 10 | | 18 | 9 | | 19 | 10 | | 20 | 10 | | 21 | 10 | | 22 | 8 | | 23 | 4 | | 24 | 9 | | 25 | 6 | | 26 | 14 | | 27 | 10 | | 28 | 8 | | 29 | 4 | | 30 | 5 | | 31 | 5 | | 32 | 20 | | 33 | 18 | | 34 | 11 | | 35 | 19 | | 36 | 8 | | 37 | 23 | | 38 | 7 | | 39 | 6 | | 40 | 2 | | 41 | 3 | | 42 | 2 | | 43 | 6 | | 44 | 23 | | 45 | 3 | | 46 | 10 | | 47 | 2 | | 48 | 15 | | 49 | 8 |
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| 34.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 31 | | diversityRatio | 0.22110552763819097 | | totalSentences | 199 | | uniqueOpeners | 44 | |
| 55.56% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 180 | | matches | | 0 | "Then it had grown hot" | | 1 | "Then she walked to the" | | 2 | "Then she heard a spoon" |
| | ratio | 0.017 | |
| 88.89% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 59 | | totalSentences | 180 | | matches | | 0 | "She stopped with one foot" | | 1 | "It should have been cold." | | 2 | "She had carried it through" | | 3 | "She had come because the" | | 4 | "She had thought of a" | | 5 | "He did not lift his" | | 6 | "She checked her phone." | | 7 | "She had left the restaurant" | | 8 | "She stepped forward again." | | 9 | "It seemed to like obedience." | | 10 | "They stood in a rough" | | 11 | "She pulled a marker from" | | 12 | "It came from the altar" | | 13 | "She did not turn toward" | | 14 | "Her hand tightened on her" | | 15 | "She let the beam sweep" | | 16 | "Her bright blue eyes watered." | | 17 | "She took another step." | | 18 | "It wore an apron." | | 19 | "Its head hung just too" |
| | ratio | 0.328 | |
| 21.11% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 158 | | totalSentences | 180 | | matches | | 0 | "The Heartstone pendant pulsed against" | | 1 | "She stopped with one foot" | | 2 | "The crimson gem fit like" | | 3 | "It should have been cold." | | 4 | "She had carried it through" | | 5 | "Rory drew back her foot." | | 6 | "The grass bent slowly and" | | 7 | "Wildflowers covered the ground, white" | | 8 | "Each blossom turned a little" | | 9 | "The motion made her teeth" | | 10 | "She had come because the" | | 11 | "She had thought of a" | | 12 | "Yu-Fei caught her holding her" | | 13 | "He did not lift his" | | 14 | "Objects made of old grief" | | 15 | "Rory touched the slip of" | | 16 | "The handwriting on it belonged" | | 17 | "She checked her phone." | | 18 | "The clock had sat at" | | 19 | "The battery percentage had not" |
| | ratio | 0.878 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 180 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 73 | | technicalSentenceCount | 4 | | matches | | 0 | "Still it gave heat, a small patient pulse, as if the grove were waking under her hand." | | 1 | "The darkness inside had edges, black iron edges, and behind them lay a lightless space that smelled of snow on stone." | | 2 | "Rory heard Eva’s laugh first, the sharp one, then Yu-Fei saying two tables one order don’t be precious, then Silas calling her name from the bar upstairs, all l…" | | 3 | "She thought of Yu-Fei’s wok, Silas’s bar, the flat above the music, the unknown hand that had given her the pendant, the name on the slip with no address, no nu…" |
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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 | | | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |