| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 0 | | tagDensity | 1 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.91% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1486 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "slowly" | | 1 | "suddenly" | | 2 | "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) | |
| 29.34% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1486 | | totalAiIsms | 21 | | found | | | highlights | | 0 | "pulse" | | 1 | "silence" | | 2 | "echoed" | | 3 | "gloom" | | 4 | "scanning" | | 5 | "pulsed" | | 6 | "warmth" | | 7 | "weight" | | 8 | "shimmered" | | 9 | "calculated" | | 10 | "whisper" | | 11 | "crystallized" | | 12 | "trembled" | | 13 | "loomed" | | 14 | "throbbed" | | 15 | "footsteps" |
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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 | 185 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 185 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 185 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1486 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 25 | | wordCount | 1478 | | uniqueNames | 14 | | maxNameDensity | 0.61 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 3 | | Park | 2 | | Rory | 9 | | November | 1 | | Heartstone | 1 | | Follow | 1 | | Golden | 1 | | Empress | 1 | | Eva | 1 | | Evan | 1 | | Cardiff | 1 | | Silas | 1 | | Pen | 1 | | Ponds | 1 |
| | persons | | 0 | "Rory" | | 1 | "Empress" | | 2 | "Eva" | | 3 | "Evan" | | 4 | "Silas" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Cardiff" | | 3 | "Pen" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 102 | | glossingSentenceCount | 1 | | matches | | 0 | "sounded like her name, but stretched thin" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.673 | | wordCount | 1486 | | matches | | 0 | "not from wind, but from pressure" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 185 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 51.24 | | std | 27.42 | | cv | 0.535 | | sampleLengths | | 0 | 67 | | 1 | 74 | | 2 | 101 | | 3 | 32 | | 4 | 76 | | 5 | 63 | | 6 | 3 | | 7 | 56 | | 8 | 72 | | 9 | 8 | | 10 | 53 | | 11 | 100 | | 12 | 8 | | 13 | 73 | | 14 | 18 | | 15 | 3 | | 16 | 69 | | 17 | 85 | | 18 | 47 | | 19 | 42 | | 20 | 6 | | 21 | 63 | | 22 | 30 | | 23 | 55 | | 24 | 62 | | 25 | 64 | | 26 | 42 | | 27 | 57 | | 28 | 57 |
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| 97.68% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 185 | | matches | | 0 | "been locked" | | 1 | "been coaxed" | | 2 | "been muffled" | | 3 | "was held" |
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| 59.35% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 237 | | matches | | 0 | "were breathing" | | 1 | "was behaving" | | 2 | "was not guiding" | | 3 | "was warning" | | 4 | "was bending" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 185 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 259 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 5 | | adverbRatio | 0.019305019305019305 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.003861003861003861 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 185 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 185 | | mean | 8.03 | | std | 5.72 | | cv | 0.712 | | sampleLengths | | 0 | 21 | | 1 | 25 | | 2 | 4 | | 3 | 12 | | 4 | 5 | | 5 | 12 | | 6 | 22 | | 7 | 9 | | 8 | 18 | | 9 | 6 | | 10 | 7 | | 11 | 6 | | 12 | 15 | | 13 | 3 | | 14 | 3 | | 15 | 12 | | 16 | 11 | | 17 | 20 | | 18 | 28 | | 19 | 3 | | 20 | 4 | | 21 | 20 | | 22 | 8 | | 23 | 6 | | 24 | 19 | | 25 | 15 | | 26 | 1 | | 27 | 6 | | 28 | 18 | | 29 | 8 | | 30 | 3 | | 31 | 6 | | 32 | 5 | | 33 | 27 | | 34 | 6 | | 35 | 5 | | 36 | 3 | | 37 | 11 | | 38 | 2 | | 39 | 1 | | 40 | 7 | | 41 | 3 | | 42 | 2 | | 43 | 10 | | 44 | 5 | | 45 | 15 | | 46 | 5 | | 47 | 5 | | 48 | 4 | | 49 | 4 |
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| 39.64% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 25 | | diversityRatio | 0.31891891891891894 | | totalSentences | 185 | | uniqueOpeners | 59 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 7 | | totalSentences | 167 | | matches | | 0 | "Then she saw the stones." | | 1 | "Roughly the size of a" | | 2 | "Too close to the shape" | | 3 | "Maybe thirteen if the roots" | | 4 | "Nearly three hours." | | 5 | "Only then did she let" | | 6 | "Only then did she admit" |
| | ratio | 0.042 | |
| 71.50% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 62 | | totalSentences | 167 | | matches | | 0 | "She slipped through the gap," | | 1 | "It went still and heavy," | | 2 | "Their trunks had been coaxed" | | 3 | "They should not have been" | | 4 | "It was warm." | | 5 | "She hooked a finger under" | | 6 | "She had lingered anyway." | | 7 | "Her boots sank into soil" | | 8 | "She kept her hands out" | | 9 | "It was held." | | 10 | "Her bright blue eyes adjusted" | | 11 | "She took another step." | | 12 | "She rubbed her thumb over" | | 13 | "It did nothing now." | | 14 | "Her breath plumed white, though" | | 15 | "Her straight black hair clung" | | 16 | "She did not jerk." | | 17 | "She let her eyes track" | | 18 | "It slipped between two oaks" | | 19 | "She turned her head." |
| | ratio | 0.371 | |
| 58.80% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 134 | | totalSentences | 167 | | matches | | 0 | "The iron gate to Richmond" | | 1 | "She slipped through the gap," | | 2 | "The air changed first." | | 3 | "It went still and heavy," | | 4 | "Their trunks had been coaxed" | | 5 | "Wildflowers pushed through the moss" | | 6 | "They should not have been" | | 7 | "Nothing about this place obeyed" | | 8 | "Rory stepped over the root" | | 9 | "The silver chain at her" | | 10 | "It was warm." | | 11 | "A steady, radiating pulse that" | | 12 | "She hooked a finger under" | | 13 | "The unknown benefactor who had" | | 14 | "She had lingered anyway." | | 15 | "Deliveries for the Golden Empress" | | 16 | "Rory moved deeper into the" | | 17 | "Her boots sank into soil" | | 18 | "She kept her hands out" | | 19 | "That was what Eva called" |
| | ratio | 0.802 | |
| 29.94% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 167 | | matches | | 0 | "Now it hung directly overhead," |
| | ratio | 0.006 | |
| 89.95% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 4 | | matches | | 0 | "The unknown benefactor who had left it in her coat pocket three weeks ago had included a single line of instruction on a torn receipt: Follow the heat." | | 1 | "Her boots sank into soil that felt too soft, too yielding, as if the earth were breathing beneath her." | | 2 | "Her straight black hair clung to her damp neck, heavy with moisture that had no source." | | 3 | "Limbs that were too long, joints that bent backward, a silhouette that refused to hold a single shape." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |