| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 44 | | adverbTagCount | 1 | | adverbTags | | 0 | "she asked again [again]" |
| | dialogueSentences | 91 | | tagDensity | 0.484 | | leniency | 0.967 | | rawRatio | 0.023 | | effectiveRatio | 0.022 | |
| 93.88% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 4083 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "softly" | | 1 | "slowly" | | 2 | "carefully" |
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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) | |
| 42.44% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 4083 | | totalAiIsms | 47 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | word | "down her spine" | | count | 1 |
| | 18 | |
| | highlights | | 0 | "pulsed" | | 1 | "throbbed" | | 2 | "silence" | | 3 | "weight" | | 4 | "flickered" | | 5 | "warmth" | | 6 | "echoed" | | 7 | "echo" | | 8 | "shimmered" | | 9 | "could feel" | | 10 | "whisper" | | 11 | "loomed" | | 12 | "tension" | | 13 | "output" | | 14 | "ensure" | | 15 | "footsteps" | | 16 | "pulse" | | 17 | "down her spine" | | 18 | "vibrated" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 1 | | found | | 0 | | label | "knuckles turned white" | | count | 2 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 816 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 5 | | hedgeCount | 3 | | narrationSentences | 816 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 847 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 39 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 51 | | markdownWords | 93 | | totalWords | 4125 | | ratio | 0.023 | | matches | | 0 | "Analyze the Request:" | | 1 | "Task:" | | 2 | "Genre:" | | 3 | "Length:" | | 4 | "Setting:" | | 5 | "Character:" | | 6 | "Plot Point:" | | 7 | "Style Rules:" | | 8 | "Codex Usage:" | | 9 | "Deconstruct the Scene:" | | 10 | "Start:" | | 11 | "Conflict:" | | 12 | "Props:" | | 13 | "Goal:" | | 14 | "Horror Element:" | | 15 | "Ending:" | | 16 | "Correction:" | | 17 | "Dialogue Constraint:" | | 18 | "Word Count:" | | 19 | "Drafting - Section by Section:" | | 20 | "Entrance:" | | 21 | "Observation:" | | 22 | "The Item:" | | 23 | "The Wrongness:" | | 24 | "Tension:" | | 25 | "Dialogue:" | | 26 | "Climax of Scene:" | | 27 | "Stopping:" | | 28 | "Constraint Check:" | | 29 | "Word Count:" | | 30 | "Writing - Step-by-Step:" | | 31 | "Opening:" | | 32 | "Sensory:" | | 33 | "The Pendant:" | | 34 | "The Environment:" | | 35 | "The Presence:" | | 36 | "feeling" | | 37 | "Dialogue:" | | 38 | "Horror:" | | 39 | "Ending:" | | 40 | "Drafting thought:" | | 41 | "Let's write." | | 42 | "Reviewing the Glossary:" | | 43 | "Scene Start:" | | 44 | "Scene End:" | | 45 | "Wait, one more check:" | | 46 | "Plan:" | | 47 | "Refining \"No Uncertainty\":" | | 48 | "Refining \"No Cliches\":" | | 49 | "Let's write." | | 50 | "Wait, one last thing:" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 49 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 151 | | wordCount | 3806 | | uniqueNames | 52 | | maxNameDensity | 0.79 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Fae" | | discoveredNames | | London | 3 | | Richmond | 4 | | Park | 4 | | Carter | 3 | | Heartstone | 6 | | Pendant | 6 | | Grove | 8 | | Process | 1 | | Continue | 1 | | Horror | 3 | | Fae | 4 | | Aurora | 30 | | Rory | 2 | | Alone | 1 | | Past | 1 | | General | 1 | | English | 1 | | Active | 1 | | Show | 1 | | Mix | 1 | | Incorporate | 1 | | Internal | 1 | | Hel | 1 | | Sensory | 3 | | Do | 1 | | Since | 1 | | Section | 2 | | Crossing | 2 | | Footsteps | 2 | | Whispering | 2 | | Easy | 1 | | Remove | 1 | | Ensure | 1 | | Describe | 2 | | Stepping | 1 | | Smell | 1 | | Warmth | 3 | | Trees | 1 | | Start | 3 | | Note | 1 | | Bad | 4 | | Good | 4 | | Word | 3 | | Count | 3 | | Check | 3 | | Strategy | 1 | | Snow | 4 | | Heavy | 4 | | One | 3 | | Closer | 3 | | Dark | 3 | | Time | 3 |
| | persons | | 0 | "Carter" | | 1 | "Heartstone" | | 2 | "Pendant" | | 3 | "Aurora" | | 4 | "Rory" | | 5 | "English" | | 6 | "Remove" | | 7 | "Warmth" | | 8 | "Trees" | | 9 | "Snow" |
| | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Grove" | | 4 | "Fae" | | 5 | "Hel" | | 6 | "Ensure" | | 7 | "One" | | 8 | "Dark" | | 9 | "Time" |
| | globalScore | 1 | | windowScore | 1 | |
| 85.90% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 195 | | glossingSentenceCount | 5 | | matches | | 0 | "felt like it was opening" | | 1 | "looked like a hole in the world, a silhou" | | 2 | "Something like a violin string snapping" | | 3 | "felt like it was opening" | | 4 | "looked like a hole in the world, a silhou" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.242 | | wordCount | 4125 | | matches | | 0 | "Not a monster yet, but a *feeling*" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 847 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 409 | | mean | 10.09 | | std | 15.93 | | cv | 1.58 | | sampleLengths | | 0 | 50 | | 1 | 27 | | 2 | 17 | | 3 | 10 | | 4 | 34 | | 5 | 45 | | 6 | 3 | | 7 | 41 | | 8 | 36 | | 9 | 22 | | 10 | 16 | | 11 | 26 | | 12 | 7 | | 13 | 11 | | 14 | 27 | | 15 | 28 | | 16 | 15 | | 17 | 38 | | 18 | 6 | | 19 | 46 | | 20 | 12 | | 21 | 30 | | 22 | 12 | | 23 | 31 | | 24 | 27 | | 25 | 4 | | 26 | 23 | | 27 | 13 | | 28 | 28 | | 29 | 4 | | 30 | 27 | | 31 | 19 | | 32 | 5 | | 33 | 7 | | 34 | 20 | | 35 | 4 | | 36 | 23 | | 37 | 13 | | 38 | 8 | | 39 | 6 | | 40 | 12 | | 41 | 23 | | 42 | 11 | | 43 | 10 | | 44 | 6 | | 45 | 5 | | 46 | 6 | | 47 | 25 | | 48 | 36 | | 49 | 13 |
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| 97.09% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 19 | | totalSentences | 816 | | matches | | 0 | "were gone" | | 1 | "was gone" | | 2 | "was gone" | | 3 | "was gone" | | 4 | "was gone" | | 5 | "was covered" | | 6 | "is given" | | 7 | "being echoed" | | 8 | "was gone" | | 9 | "was gone" | | 10 | "was gone" | | 11 | "was gone" | | 12 | "was gone" | | 13 | "was gone" | | 14 | "was gone" | | 15 | "were gone" | | 16 | "was gone" | | 17 | "were gone" | | 18 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 805 | | matches | | 0 | "was opening" | | 1 | "was turning" | | 2 | "was standing" | | 3 | "was opening" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 847 | | ratio | 0.002 | | matches | | 0 | "**Drafting - Section by Section:**" | | 1 | "**Writing - Step-by-Step:**" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 3774 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 96 | | adverbRatio | 0.025437201907790145 | | lyAdverbCount | 19 | | lyAdverbRatio | 0.005034446210916799 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 847 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 847 | | mean | 4.87 | | std | 3.26 | | cv | 0.669 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 1 | | 3 | 10 | | 4 | 6 | | 5 | 4 | | 6 | 4 | | 7 | 2 | | 8 | 2 | | 9 | 6 | | 10 | 2 | | 11 | 7 | | 12 | 8 | | 13 | 2 | | 14 | 7 | | 15 | 7 | | 16 | 3 | | 17 | 4 | | 18 | 13 | | 19 | 5 | | 20 | 12 | | 21 | 7 | | 22 | 10 | | 23 | 16 | | 24 | 7 | | 25 | 5 | | 26 | 3 | | 27 | 5 | | 28 | 4 | | 29 | 9 | | 30 | 4 | | 31 | 5 | | 32 | 6 | | 33 | 8 | | 34 | 2 | | 35 | 8 | | 36 | 4 | | 37 | 5 | | 38 | 5 | | 39 | 12 | | 40 | 15 | | 41 | 7 | | 42 | 8 | | 43 | 4 | | 44 | 4 | | 45 | 3 | | 46 | 4 | | 47 | 2 | | 48 | 6 | | 49 | 2 |
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| 39.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 84 | | diversityRatio | 0.1524609843937575 | | totalSentences | 833 | | uniqueOpeners | 127 | |
| 69.44% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 14 | | totalSentences | 672 | | matches | | 0 | "Just the wet squelch of" | | 1 | "Somewhere to her left." | | 2 | "Just the rustle of petals." | | 3 | "Too many syllables." | | 4 | "Just a smooth surface." | | 5 | "Then the flowers." | | 6 | "Too bright for night." | | 7 | "Then the pendant heating up." | | 8 | "Then the sounds." | | 9 | "Just stop at the action." | | 10 | "Just the wet squelch of" | | 11 | "Somewhere to her left." | | 12 | "Then she heard a second" | | 13 | "Just a smooth surface." |
| | ratio | 0.021 | |
| 30.71% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 318 | | totalSentences | 672 | | matches | | 0 | "She checked her watch." | | 1 | "she whispered to the darkness" | | 2 | "She pulled her coat tighter." | | 3 | "She stood at the center" | | 4 | "She took a step forward." | | 5 | "Her boot sank into the" | | 6 | "She listened to the hum" | | 7 | "She looked at her hand." | | 8 | "She spoke loud enough to" | | 9 | "She knew she spoke to" | | 10 | "She kept speaking anyway." | | 11 | "She did not turn." | | 12 | "Her neck muscles locked tight." | | 13 | "She took another step." | | 14 | "It bent like a head" | | 15 | "She held it up to" | | 16 | "Her breath fogged in the" | | 17 | "She didn't drop it." | | 18 | "She gripped it until her" | | 19 | "She spun around." |
| | ratio | 0.473 | |
| 26.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 583 | | totalSentences | 672 | | matches | | 0 | "The oak stones stood tall," | | 1 | "Snow fell softly on the" | | 2 | "Aurora Carter stepped across the" | | 3 | "She checked her watch." | | 4 | "The second hand ticked." | | 5 | "The watch still read the" | | 6 | "Aurora touched the crimson stone" | | 7 | "The silver chain cut into" | | 8 | "she whispered to the darkness" | | 9 | "The Heartstone Pendant pulsed." | | 10 | "A faint inner glow deepened," | | 11 | "She pulled her coat tighter." | | 12 | "The collarbone scar on her" | | 13 | "The trees here leaned in" | | 14 | "The canopy wove a net" | | 15 | "She stood at the center" | | 16 | "She took a step forward." | | 17 | "The ground felt spongy." | | 18 | "Her boot sank into the" | | 19 | "The silence was absolute." |
| | ratio | 0.868 | |
| 22.32% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 672 | | matches | | 0 | "If she ignored it, maybe" | | 1 | "If she is alone, how" | | 2 | "If she ignored it, maybe" |
| | ratio | 0.004 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 1 | | matches | | 0 | "I must generate fresh, coherent text that meets the word count and style guidelines.)" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 44 | | uselessAdditionCount | 1 | | matches | | 0 | "Describe the cold, the pulse, the light" |
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| 29.12% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 37 | | fancyCount | 11 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "She spoke (speak)" | | 2 | "she muttered (mutter)" | | 3 | "she shouted (shout)" | | 4 | "she gasped (gasp)" | | 5 | "she whispered (whisper)" | | 6 | "Describe the cold (describe)" | | 7 | "she whispered (whisper)" | | 8 | "She spoke (speak)" | | 9 | "she muttered (mutter)" | | 10 | "she shouted (shout)" |
| | dialogueSentences | 91 | | tagDensity | 0.407 | | leniency | 0.813 | | rawRatio | 0.297 | | effectiveRatio | 0.242 | |