| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 30 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn said quietly [quietly]" | | 1 | "Quinn moved systematically [systematically]" |
| | dialogueSentences | 63 | | tagDensity | 0.476 | | leniency | 0.952 | | rawRatio | 0.067 | | effectiveRatio | 0.063 | |
| 95.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1097 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 60.00% | 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) | |
| 49.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1097 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "echoed" | | 1 | "gloom" | | 2 | "trembled" | | 3 | "etched" | | 4 | "magnetic" | | 5 | "shimmered" | | 6 | "flickered" | | 7 | "silk" |
| |
| 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 | 94 | | matches | (empty) | |
| 97.26% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 94 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 126 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1090 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 0 | | matches | (empty) | |
| 12.83% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 729 | | uniqueNames | 15 | | maxNameDensity | 2.74 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Marketplace | 1 | | Chen | 9 | | Greek | 2 | | Market | 1 | | Transport | 1 | | London | 1 | | Eva | 13 | | Quinn | 20 | | Veil | 2 | | Compass | 6 | | Camden | 1 | | Webb | 2 | | Parkway | 1 | | Clenched | 1 | | Victorian | 1 |
| | persons | | 0 | "Chen" | | 1 | "Market" | | 2 | "Eva" | | 3 | "Quinn" | | 4 | "Compass" | | 5 | "Webb" |
| | places | | | globalScore | 0.128 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 16.51% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.835 | | wordCount | 1090 | | matches | | 0 | "not north, but down" | | 1 | "not toward magnetic north, but toward the body with magnetic insistence" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 126 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 24.77 | | std | 19.33 | | cv | 0.78 | | sampleLengths | | 0 | 50 | | 1 | 39 | | 2 | 51 | | 3 | 24 | | 4 | 47 | | 5 | 9 | | 6 | 28 | | 7 | 13 | | 8 | 61 | | 9 | 20 | | 10 | 33 | | 11 | 7 | | 12 | 29 | | 13 | 45 | | 14 | 54 | | 15 | 9 | | 16 | 23 | | 17 | 39 | | 18 | 12 | | 19 | 56 | | 20 | 8 | | 21 | 7 | | 22 | 4 | | 23 | 7 | | 24 | 1 | | 25 | 61 | | 26 | 25 | | 27 | 5 | | 28 | 15 | | 29 | 5 | | 30 | 14 | | 31 | 84 | | 32 | 14 | | 33 | 21 | | 34 | 11 | | 35 | 13 | | 36 | 9 | | 37 | 43 | | 38 | 12 | | 39 | 14 | | 40 | 27 | | 41 | 15 | | 42 | 12 | | 43 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 94 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 125 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 126 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 735 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.01904761904761905 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.010884353741496598 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 126 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 126 | | mean | 8.65 | | std | 5.3 | | cv | 0.613 | | sampleLengths | | 0 | 8 | | 1 | 1 | | 2 | 1 | | 3 | 23 | | 4 | 2 | | 5 | 10 | | 6 | 1 | | 7 | 2 | | 8 | 2 | | 9 | 10 | | 10 | 15 | | 11 | 14 | | 12 | 18 | | 13 | 11 | | 14 | 15 | | 15 | 7 | | 16 | 4 | | 17 | 11 | | 18 | 9 | | 19 | 11 | | 20 | 6 | | 21 | 2 | | 22 | 8 | | 23 | 12 | | 24 | 8 | | 25 | 9 | | 26 | 15 | | 27 | 13 | | 28 | 7 | | 29 | 6 | | 30 | 14 | | 31 | 23 | | 32 | 7 | | 33 | 17 | | 34 | 11 | | 35 | 9 | | 36 | 17 | | 37 | 16 | | 38 | 5 | | 39 | 2 | | 40 | 18 | | 41 | 11 | | 42 | 9 | | 43 | 8 | | 44 | 13 | | 45 | 7 | | 46 | 4 | | 47 | 4 | | 48 | 13 | | 49 | 4 |
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| 89.68% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.5714285714285714 | | totalSentences | 126 | | uniqueOpeners | 72 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 10 | | totalSentences | 73 | | matches | | 0 | "It skittered against the third" | | 1 | "She adjusted her worn leather" | | 2 | "She clutched her worn leather" | | 3 | "Her green eyes adjusted to" | | 4 | "She checked Webb's jacket." | | 5 | "She used her pocket knife" | | 6 | "She pulled it out." | | 7 | "They rolled the corpse." | | 8 | "She knelt, her satchel bumping" | | 9 | "She turned slowly, counting the" |
| | ratio | 0.137 | |
| 62.74% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 73 | | matches | | 0 | "Quinn pressed two fingers against" | | 1 | "The flesh beneath her touch" | | 2 | "DC Chen kicked a loose" | | 3 | "It skittered against the third" | | 4 | "Quinn lifted the chin, her" | | 5 | "The wound gaped, ragged at" | | 6 | "The spray pattern on the" | | 7 | "Chen's beam swept up." | | 8 | "Quinn stood, the sharp line" | | 9 | "She adjusted her worn leather" | | 10 | "The full moon had waned" | | 11 | "The Market should have shifted" | | 12 | "Quinn had flash-banged her authority" | | 13 | "A scuff echoed from the" | | 14 | "Quinn's hand dropped to her" | | 15 | "Eva's voice preceded her, breathless," | | 16 | "She clutched her worn leather" | | 17 | "Her green eyes adjusted to" | | 18 | "Quinn didn't turn" | | 19 | "Eva's shoes crunched on broken" |
| | ratio | 0.795 | |
| 68.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 73 | | matches | | 0 | "Now it pointed not north," |
| | ratio | 0.014 | |
| 77.92% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 22 | | technicalSentenceCount | 2 | | matches | | 0 | "The needle trembled against its brass housing, pulling not toward magnetic north, but toward the body with magnetic insistence." | | 1 | "And underneath, carved fresh into the concrete with impossible precision, a spiral that matched the Compass face exactly, surrounded by five concentric rings." |
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| 58.33% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 30 | | uselessAdditionCount | 4 | | matches | | 0 | "Eva's shoes crunched, though her hands trembled" | | 1 | "Quinn moved systematically, her torch beam cutting through dust motes" | | 2 | "Eva said, her face pale" | | 3 | "Eva said, her voice trembling" |
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| 86.51% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 4 | | fancyTags | | 0 | "Eva whispered (whisper)" | | 1 | "Quinn ordered (order)" | | 2 | "Eva whispered (whisper)" | | 3 | "Quinn shouted (shout)" |
| | dialogueSentences | 63 | | tagDensity | 0.238 | | leniency | 0.476 | | rawRatio | 0.267 | | effectiveRatio | 0.127 | |