| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 56 | | tagDensity | 0.089 | | leniency | 0.179 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 98.01% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2508 | | 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) | |
| 66.11% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2508 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "pulse" | | 1 | "flicked" | | 2 | "silence" | | 3 | "shimmered" | | 4 | "silk" | | 5 | "shattered" | | 6 | "pulsed" | | 7 | "flickered" | | 8 | "crystal" | | 9 | "warmth" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "blood ran cold" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 612 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 612 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 663 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 18 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 15 | | markdownWords | 58 | | totalWords | 2509 | | ratio | 0.023 | | matches | | 0 | "Laila..." | | 1 | "Give it... we are hungry..." | | 2 | "Blood opens the door..." | | 3 | "We wait... The stone calls... The gate opens..." | | 4 | "Good girl... Feed us..." | | 5 | "Sacrifice opens the vein..." | | 6 | "STOOOOP..." | | 7 | "She wakes them... She wakes them all..." | | 8 | "The seal is the key... You turned the lock..." | | 9 | "Stay... Bloom... Be still..." | | 10 | "He's awake, Rory. He's watching..." | | 11 | "Run..." | | 12 | "Ride..." | | 13 | "NOOOO..." | | 14 | "Follow... Or bleed..." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 95 | | wordCount | 2266 | | uniqueNames | 13 | | maxNameDensity | 3 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Rory" | | discoveredNames | | London | 4 | | Heartstone | 2 | | Park | 2 | | Rory | 68 | | Knife | 1 | | Evan | 1 | | Richmond | 2 | | Eva | 2 | | Thames | 1 | | Real | 3 | | Heavy | 3 | | Wet | 3 | | Teeth | 3 |
| | persons | | 0 | "Heartstone" | | 1 | "Rory" | | 2 | "Knife" | | 3 | "Evan" | | 4 | "Eva" | | 5 | "Teeth" |
| | places | | 0 | "London" | | 1 | "Park" | | 2 | "Richmond" | | 3 | "Thames" |
| | globalScore | 0 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 109 | | 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 | 2509 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 663 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 439 | | mean | 5.72 | | std | 5.15 | | cv | 0.901 | | sampleLengths | | 0 | 55 | | 1 | 19 | | 2 | 9 | | 3 | 11 | | 4 | 28 | | 5 | 11 | | 6 | 3 | | 7 | 18 | | 8 | 19 | | 9 | 15 | | 10 | 2 | | 11 | 5 | | 12 | 18 | | 13 | 2 | | 14 | 25 | | 15 | 14 | | 16 | 2 | | 17 | 19 | | 18 | 11 | | 19 | 10 | | 20 | 1 | | 21 | 9 | | 22 | 13 | | 23 | 17 | | 24 | 8 | | 25 | 8 | | 26 | 13 | | 27 | 8 | | 28 | 14 | | 29 | 32 | | 30 | 8 | | 31 | 10 | | 32 | 9 | | 33 | 8 | | 34 | 5 | | 35 | 18 | | 36 | 17 | | 37 | 14 | | 38 | 5 | | 39 | 23 | | 40 | 8 | | 41 | 4 | | 42 | 12 | | 43 | 3 | | 44 | 31 | | 45 | 16 | | 46 | 8 | | 47 | 19 | | 48 | 13 | | 49 | 13 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 612 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 484 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 663 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2267 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.01940891045434495 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.002646669607410675 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 663 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 663 | | mean | 3.78 | | std | 2.29 | | cv | 0.607 | | sampleLengths | | 0 | 9 | | 1 | 6 | | 2 | 18 | | 3 | 11 | | 4 | 5 | | 5 | 6 | | 6 | 8 | | 7 | 6 | | 8 | 3 | | 9 | 2 | | 10 | 9 | | 11 | 3 | | 12 | 8 | | 13 | 6 | | 14 | 11 | | 15 | 9 | | 16 | 2 | | 17 | 4 | | 18 | 4 | | 19 | 3 | | 20 | 3 | | 21 | 4 | | 22 | 11 | | 23 | 2 | | 24 | 1 | | 25 | 3 | | 26 | 2 | | 27 | 6 | | 28 | 8 | | 29 | 2 | | 30 | 10 | | 31 | 2 | | 32 | 1 | | 33 | 2 | | 34 | 3 | | 35 | 1 | | 36 | 1 | | 37 | 5 | | 38 | 11 | | 39 | 2 | | 40 | 2 | | 41 | 3 | | 42 | 9 | | 43 | 9 | | 44 | 1 | | 45 | 3 | | 46 | 3 | | 47 | 6 | | 48 | 5 | | 49 | 2 |
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| 60.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 37 | | diversityRatio | 0.39668174962292607 | | totalSentences | 663 | | uniqueOpeners | 263 | |
| 40.45% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 412 | | matches | | 0 | "Too many joints." | | 1 | "Just a smooth surface where" | | 2 | "Just the dripping of sap" | | 3 | "Then at the mouth." | | 4 | "Then at the monster taxi." |
| | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 87 | | totalSentences | 412 | | matches | | 0 | "She touched the silver chain" | | 1 | "Her voice cracked." | | 2 | "She checked her watch." | | 3 | "She flicked her wrist." | | 4 | "Her hand dropped to the" | | 5 | "She stepped toward the stones." | | 6 | "Her shadow stretched long and" | | 7 | "She looked down." | | 8 | "Her shadow rippled like water" | | 9 | "Her heel caught on a" | | 10 | "She stumbled but kept balance." | | 11 | "She could leave." | | 12 | "She could turn back." | | 13 | "It wanted the stone." | | 14 | "She stepped deeper." | | 15 | "She didn't cower." | | 16 | "It wore the shape of" | | 17 | "It glided forward." | | 18 | "She tapped the pendant" | | 19 | "we are hungry...*" |
| | ratio | 0.211 | |
| 55.87% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 333 | | totalSentences | 412 | | matches | | 0 | "Rory stepped over the root" | | 1 | "Bark bit into her boot" | | 2 | "The standing stones rose like" | | 3 | "Night swallowed the sky, but" | | 4 | "Bioluminescence clung to the ferns." | | 5 | "She touched the silver chain" | | 6 | "The Heartstone hummed against her" | | 7 | "A steady rhythm." | | 8 | "Her voice cracked." | | 9 | "The sound died instantly, absorbed" | | 10 | "The cold seeped through her" | | 11 | "Richmond Park should have smelled" | | 12 | "Here, the air tasted of" | | 13 | "She checked her watch." | | 14 | "The dial spun backward." | | 15 | "The hands melted." | | 16 | "She flicked her wrist." | | 17 | "The crescent scar on her" | | 18 | "A branch snapped." | | 19 | "The air hung heavy and" |
| | ratio | 0.808 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 412 | | matches | (empty) | | ratio | 0 | |
| 87.91% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 13 | | technicalSentenceCount | 1 | | matches | | 0 | "The standing stones rose like broken teeth against the London smog that failed to penetrate the tree line." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Rory shouted (shout)" | | 1 | "Rory spat (spit)" |
| | dialogueSentences | 56 | | tagDensity | 0.036 | | leniency | 0.071 | | rawRatio | 1 | | effectiveRatio | 0.071 | |