| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 12 | | adverbTagCount | 1 | | adverbTags | | 0 | "she realised aloud [aloud]" |
| | dialogueSentences | 19 | | tagDensity | 0.632 | | leniency | 1 | | rawRatio | 0.083 | | effectiveRatio | 0.083 | |
| 85.63% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1044 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 37.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1044 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "loomed" | | 1 | "pulsed" | | 2 | "warmth" | | 3 | "flickered" | | 4 | "perfect" | | 5 | "silence" | | 6 | "could feel" | | 7 | "predator" | | 8 | "stomach" | | 9 | "symphony" | | 10 | "searing" | | 11 | "shattered" |
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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 | 137 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 137 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened to" | | 1 | "begins to" |
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| 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 | | maxSentenceWordsSeen | 20 | | ratio | 0 | | matches | (empty) | |
| 72.59% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 18 | | markdownWords | 66 | | totalWords | 1036 | | ratio | 0.064 | | matches | | 0 | "Tonight. Midnight. The Grove will show you what happened to Marcus." | | 1 | "HE ASKED TOO MANY QUESTIONS" | | 2 | "YOU" | | 3 | "NO GODS HERE" | | 4 | "ONLY QUESTIONS" | | 5 | "HE ASKED ABOUT THE HEARTSTONE" | | 6 | "ABOUT WHO GAVE IT TO YOU" | | 7 | "ABOUT WHY YOU" | | 8 | "LIES" | | 9 | "FOR NOW" | | 10 | "BUT YOU CAME HERE" | | 11 | "YOU CROSSED THE BOUNDARY" | | 12 | "TIME MOVES DIFFERENTLY HERE" | | 13 | "TOO LATE" | | 14 | "YOU'VE BEEN HERE BEFORE" | | 15 | "YOU JUST DON'T REMEMBER" | | 16 | "FINALLY" | | 17 | "SHE BEGINS TO UNDERSTAND" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 76.24% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 949 | | uniqueNames | 15 | | maxNameDensity | 1.48 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Richmond | 1 | | Park | 1 | | October | 1 | | Heartstone | 1 | | Eva | 1 | | Midnight | 1 | | Grove | 1 | | Years | 1 | | Brendan | 1 | | Carter | 2 | | London | 1 | | Aurora | 14 | | New | 2 | | One | 1 | | Cardiff | 1 |
| | persons | | 0 | "Eva" | | 1 | "Grove" | | 2 | "Brendan" | | 3 | "Carter" | | 4 | "Aurora" | | 5 | "One" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "October" | | 3 | "London" | | 4 | "Cardiff" |
| | globalScore | 0.762 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 1 | | matches | | 0 | "something like amusement" |
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| 6.95% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.931 | | wordCount | 1036 | | matches | | 0 | "Not human laughter, but the sound windchimes might make if they could feel malice" | | 1 | "Not mud, but something organic, yielding" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 144 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 56 | | mean | 18.5 | | std | 13.82 | | cv | 0.747 | | sampleLengths | | 0 | 39 | | 1 | 23 | | 2 | 47 | | 3 | 5 | | 4 | 28 | | 5 | 27 | | 6 | 7 | | 7 | 29 | | 8 | 13 | | 9 | 36 | | 10 | 17 | | 11 | 33 | | 12 | 33 | | 13 | 7 | | 14 | 41 | | 15 | 38 | | 16 | 17 | | 17 | 5 | | 18 | 4 | | 19 | 3 | | 20 | 34 | | 21 | 12 | | 22 | 35 | | 23 | 8 | | 24 | 42 | | 25 | 4 | | 26 | 10 | | 27 | 36 | | 28 | 27 | | 29 | 5 | | 30 | 10 | | 31 | 5 | | 32 | 6 | | 33 | 3 | | 34 | 30 | | 35 | 16 | | 36 | 1 | | 37 | 34 | | 38 | 31 | | 39 | 7 | | 40 | 10 | | 41 | 4 | | 42 | 4 | | 43 | 23 | | 44 | 18 | | 45 | 10 | | 46 | 2 | | 47 | 4 | | 48 | 4 | | 49 | 27 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 137 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 163 | | 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) | |
| 97.51% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 957 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 41 | | adverbRatio | 0.042842215256008356 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.014629049111807733 | |
| 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 | 7.19 | | std | 4.25 | | cv | 0.591 | | sampleLengths | | 0 | 20 | | 1 | 19 | | 2 | 13 | | 3 | 1 | | 4 | 9 | | 5 | 11 | | 6 | 11 | | 7 | 14 | | 8 | 11 | | 9 | 5 | | 10 | 12 | | 11 | 6 | | 12 | 10 | | 13 | 8 | | 14 | 16 | | 15 | 3 | | 16 | 2 | | 17 | 5 | | 18 | 4 | | 19 | 2 | | 20 | 5 | | 21 | 4 | | 22 | 2 | | 23 | 12 | | 24 | 3 | | 25 | 4 | | 26 | 6 | | 27 | 4 | | 28 | 14 | | 29 | 5 | | 30 | 5 | | 31 | 8 | | 32 | 7 | | 33 | 10 | | 34 | 5 | | 35 | 1 | | 36 | 14 | | 37 | 13 | | 38 | 5 | | 39 | 5 | | 40 | 13 | | 41 | 5 | | 42 | 5 | | 43 | 7 | | 44 | 4 | | 45 | 14 | | 46 | 11 | | 47 | 7 | | 48 | 2 | | 49 | 3 |
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| 63.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.4305555555555556 | | totalSentences | 144 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 113 | | matches | | 0 | "Too many lungs, or not" | | 1 | "Too tall to be human." | | 2 | "Too fluid to be animal." | | 3 | "*FINALLY* the grass wrote." |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 113 | | matches | | 0 | "she muttered, but Eva's text" | | 1 | "Her voice came out steadier" | | 2 | "She checked her phone." | | 3 | "She tapped the screen." | | 4 | "she said to the silence" | | 5 | "She turned left, saw nothing." | | 6 | "She'd faced down drunks, dealers," | | 7 | "She looked down." | | 8 | "*HE ASKED TOO MANY QUESTIONS*" | | 9 | "Her eyes watered trying to" | | 10 | "They hung between the oak" | | 11 | "Their bodies shifted constantly, never" | | 12 | "It stopped just outside arm's" | | 13 | "*HE ASKED ABOUT THE HEARTSTONE*" | | 14 | "Their breathing-laughter grew louder, a" | | 15 | "she realised aloud" | | 16 | "*YOU CROSSED THE BOUNDARY*" | | 17 | "*YOU'VE BEEN HERE BEFORE*" | | 18 | "*YOU JUST DON'T REMEMBER*" | | 19 | "*SHE BEGINS TO UNDERSTAND*" |
| | ratio | 0.177 | |
| 88.32% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 113 | | matches | | 0 | "The standing stones loomed against" | | 1 | "Aurora's breath misted in the" | | 2 | "she muttered, but Eva's text" | | 3 | "The Grove will show you" | | 4 | "The wildflowers brushed her ankles," | | 5 | "The clearing stretched before her," | | 6 | "Time felt syrupy here, each" | | 7 | "A branch cracked behind her." | | 8 | "Aurora spun, hand instinctively reaching" | | 9 | "Nothing but shadows between the" | | 10 | "The pendant pulsed harder, its" | | 11 | "Her voice came out steadier" | | 12 | "Years of Brendan Carter's courtroom" | | 13 | "The wildflowers rustled without wind." | | 14 | "She checked her phone." | | 15 | "The clock read 00:00, frozen." | | 16 | "She tapped the screen." | | 17 | "The battery icon flickered between" | | 18 | "Another sound, softer." | | 19 | "Aurora forced herself forward." |
| | ratio | 0.743 | |
| 44.25% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 113 | | matches | | | ratio | 0.009 | |
| 71.43% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 4 | | matches | | 0 | "The standing stones loomed against Richmond Park's darkness, their ancient oak forms twisted into shapes that shouldn't exist in nature." | | 1 | "The thing had too many joints, bending in directions that made her stomach turn." | | 2 | "Their breathing-laughter grew louder, a symphony of wrongness that made her ears bleed." | | 3 | "The watchers pressed closer, their faces-that-weren't-faces cycling faster through their silent screams." |
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| 83.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 12 | | uselessAdditionCount | 1 | | matches | | 0 | "she muttered, but Eva's text had been clear: *Tonight" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 4 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she lied (lie)" | | 2 | "Aurora demanded (demand)" | | 3 | "Aurora whispered (whisper)" |
| | dialogueSentences | 19 | | tagDensity | 0.474 | | leniency | 0.947 | | rawRatio | 0.444 | | effectiveRatio | 0.421 | |