| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 20 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1191 | | 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) | |
| 66.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1191 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flickered" | | 1 | "racing" | | 2 | "scanned" | | 3 | "weight" | | 4 | "echoes" | | 5 | "silence" | | 6 | "throb" |
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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 | 99 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 99 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 46 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1191 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 26 | | wordCount | 1001 | | uniqueNames | 9 | | maxNameDensity | 0.9 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Herrera | 2 | | Raven | 1 | | Nest | 1 | | Silas | 1 | | Quinn | 9 | | Tomás | 9 | | Saint | 1 | | Christopher | 1 | | English | 1 |
| | persons | | 0 | "Herrera" | | 1 | "Raven" | | 2 | "Nest" | | 3 | "Silas" | | 4 | "Quinn" | | 5 | "Tomás" | | 6 | "Saint" | | 7 | "Christopher" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 1 | | matches | | 0 | "smelled like vinegar and copper" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1191 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 114 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 23.82 | | std | 19.12 | | cv | 0.803 | | sampleLengths | | 0 | 65 | | 1 | 7 | | 2 | 9 | | 3 | 21 | | 4 | 44 | | 5 | 12 | | 6 | 48 | | 7 | 22 | | 8 | 10 | | 9 | 11 | | 10 | 51 | | 11 | 10 | | 12 | 17 | | 13 | 75 | | 14 | 32 | | 15 | 3 | | 16 | 61 | | 17 | 56 | | 18 | 53 | | 19 | 40 | | 20 | 17 | | 21 | 26 | | 22 | 51 | | 23 | 29 | | 24 | 7 | | 25 | 28 | | 26 | 11 | | 27 | 2 | | 28 | 3 | | 29 | 20 | | 30 | 2 | | 31 | 4 | | 32 | 12 | | 33 | 27 | | 34 | 32 | | 35 | 12 | | 36 | 43 | | 37 | 13 | | 38 | 5 | | 39 | 46 | | 40 | 10 | | 41 | 19 | | 42 | 15 | | 43 | 14 | | 44 | 1 | | 45 | 3 | | 46 | 9 | | 47 | 22 | | 48 | 47 | | 49 | 14 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 183 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 114 | | ratio | 0.009 | | matches | | 0 | "Old maps and black-and-white photographs lined the bar walls inside; she could smell the sour tang of spilled ale through the grates as she passed." |
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| 96.73% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1006 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 44 | | adverbRatio | 0.0437375745526839 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.007952286282306162 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 10.45 | | std | 7.56 | | cv | 0.723 | | sampleLengths | | 0 | 23 | | 1 | 24 | | 2 | 18 | | 3 | 2 | | 4 | 2 | | 5 | 3 | | 6 | 6 | | 7 | 3 | | 8 | 7 | | 9 | 4 | | 10 | 10 | | 11 | 9 | | 12 | 25 | | 13 | 10 | | 14 | 12 | | 15 | 5 | | 16 | 8 | | 17 | 7 | | 18 | 2 | | 19 | 22 | | 20 | 4 | | 21 | 11 | | 22 | 5 | | 23 | 6 | | 24 | 10 | | 25 | 5 | | 26 | 6 | | 27 | 19 | | 28 | 9 | | 29 | 14 | | 30 | 9 | | 31 | 10 | | 32 | 9 | | 33 | 8 | | 34 | 12 | | 35 | 16 | | 36 | 6 | | 37 | 11 | | 38 | 30 | | 39 | 7 | | 40 | 12 | | 41 | 13 | | 42 | 2 | | 43 | 1 | | 44 | 7 | | 45 | 4 | | 46 | 10 | | 47 | 9 | | 48 | 31 | | 49 | 10 |
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| 55.26% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3684210526315789 | | totalSentences | 114 | | uniqueOpeners | 42 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 90 | | matches | | 0 | "She followed, lungs burning, the" | | 1 | "He had to know the" | | 2 | "She did not." | | 3 | "she called out once, voice" | | 4 | "She regretted it immediately." | | 5 | "He glanced back, but the" | | 6 | "She gained on the alley" | | 7 | "She reached the same door." | | 8 | "She tried the obvious first," | | 9 | "She followed the line of" | | 10 | "She had never reported the" | | 11 | "She had never mentioned Tomás" | | 12 | "She breathed once, then twice," | | 13 | "Her hand stayed on the" | | 14 | "His olive skin caught the" | | 15 | "She saw the flash of" | | 16 | "She moved fast, drawing the" | | 17 | "She ignored him." | | 18 | "Her shoulder clipped a hanging" | | 19 | "she said under her breath," |
| | ratio | 0.4 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 90 | | matches | | 0 | "Quinn's shoes slapped against the" | | 1 | "The suspect cut left at" | | 2 | "She followed, lungs burning, the" | | 3 | "The streets narrowed." | | 4 | "He had to know the" | | 5 | "She did not." | | 6 | "she called out once, voice" | | 7 | "She regretted it immediately." | | 8 | "He glanced back, but the" | | 9 | "She gained on the alley" | | 10 | "The green neon sign overhead" | | 11 | "Tomás Herrera slipped through a" | | 12 | "She reached the same door." | | 13 | "Metal, dented, no handle on" | | 14 | "A keypad glowed faintly in" | | 15 | "She tried the obvious first," | | 16 | "The lock refused her." | | 17 | "Sometime in the last month" | | 18 | "The papers mentioned Silas, nothing" | | 19 | "Quinn backed away, heart still" |
| | ratio | 0.922 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 90 | | matches | (empty) | | ratio | 0 | |
| 95.24% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 45 | | technicalSentenceCount | 3 | | matches | | 0 | "The last detective who tried to follow a similar case without paperwork vanished from the logs three years ago, and no one filed the loss except the department …" | | 1 | "The hush of commerce whispered along the platform, but beneath it ran another sound, the low throb of something that might have been a generator or might have b…" | | 2 | "Tomás was already moving again, threading between crates of dried roots that smelled like vinegar and copper." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "she called out, voice low" |
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| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she called out (call out)" | | 1 | "Quinn continued (continue)" |
| | dialogueSentences | 20 | | tagDensity | 0.25 | | leniency | 0.5 | | rawRatio | 0.4 | | effectiveRatio | 0.2 | |