| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 15 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 31 | | tagDensity | 0.484 | | leniency | 0.968 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1362 | | totalAiIsmAdverbs | 3 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1362 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "echoes" | | 1 | "clandestine" | | 2 | "navigating" | | 3 | "scanned" | | 4 | "potential" | | 5 | "reminder" | | 6 | "echo" | | 7 | "furrowed" | | 8 | "weight" | | 9 | "stark" | | 10 | "etched" | | 11 | "intricate" | | 12 | "spectral" | | 13 | "flickered" | | 14 | "complex" | | 15 | "glinting" | | 16 | "trepidation" | | 17 | "echoed" | | 18 | "unwavering" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "air was thick with" | | count | 1 |
| | 1 | | label | "couldn't help but" | | count | 1 |
|
| | highlights | | 0 | "The air was thick with" | | 1 | "couldn't help but notice" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 67 | | matches | (empty) | |
| 57.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 67 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 83 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1362 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 1 | | matches | | 0 | "The images were grainy, but as they flickered across the surface, they revealed a story." |
| |
| 47.75% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 978 | | uniqueNames | 13 | | maxNameDensity | 2.04 | | worstName | "Eva" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Eva" | | discoveredNames | | Veil | 3 | | Market | 3 | | Tube | 1 | | Camden | 1 | | Harlow | 18 | | Quinn | 5 | | Detective | 2 | | Eva | 20 | | Kowalski | 1 | | British | 1 | | Museum | 1 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Detective" | | 3 | "Eva" | | 4 | "Kowalski" | | 5 | "Museum" |
| | places | | | globalScore | 0.478 | | windowScore | 0.5 | |
| 73.08% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 65 | | glossingSentenceCount | 2 | | matches | | 0 | "chamber that seemed to defy the confines of the underground station" | | 1 | "pattern that seemed to pulsate gently" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.734 | | wordCount | 1362 | | matches | | 0 | "not her typical crime scene, but then again, nothing in the underground markets could be cons" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 83 | | matches | (empty) | |
| 75.47% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 35 | | mean | 38.91 | | std | 16.12 | | cv | 0.414 | | sampleLengths | | 0 | 77 | | 1 | 65 | | 2 | 12 | | 3 | 68 | | 4 | 37 | | 5 | 41 | | 6 | 37 | | 7 | 34 | | 8 | 59 | | 9 | 29 | | 10 | 49 | | 11 | 59 | | 12 | 13 | | 13 | 36 | | 14 | 41 | | 15 | 53 | | 16 | 24 | | 17 | 13 | | 18 | 34 | | 19 | 41 | | 20 | 42 | | 21 | 35 | | 22 | 41 | | 23 | 24 | | 24 | 42 | | 25 | 30 | | 26 | 43 | | 27 | 18 | | 28 | 36 | | 29 | 42 | | 30 | 21 | | 31 | 54 | | 32 | 27 | | 33 | 20 | | 34 | 65 |
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| 84.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 67 | | matches | | 0 | "been alerted" | | 1 | "were flushed" | | 2 | "were lined" | | 3 | "was etched" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 158 | | matches | | 0 | "was slowly creeping" | | 1 | "was aligning" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 83 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 980 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 20 | | adverbRatio | 0.02040816326530612 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.01020408163265306 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 83 | | echoCount | 0 | | echoWords | (empty) | |
| 93.75% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 83 | | mean | 16.41 | | std | 6.31 | | cv | 0.384 | | sampleLengths | | 0 | 16 | | 1 | 17 | | 2 | 19 | | 3 | 25 | | 4 | 15 | | 5 | 11 | | 6 | 20 | | 7 | 19 | | 8 | 12 | | 9 | 11 | | 10 | 20 | | 11 | 11 | | 12 | 26 | | 13 | 20 | | 14 | 17 | | 15 | 17 | | 16 | 24 | | 17 | 7 | | 18 | 30 | | 19 | 9 | | 20 | 25 | | 21 | 23 | | 22 | 18 | | 23 | 18 | | 24 | 29 | | 25 | 21 | | 26 | 14 | | 27 | 14 | | 28 | 17 | | 29 | 17 | | 30 | 25 | | 31 | 11 | | 32 | 2 | | 33 | 17 | | 34 | 19 | | 35 | 12 | | 36 | 17 | | 37 | 12 | | 38 | 15 | | 39 | 14 | | 40 | 10 | | 41 | 14 | | 42 | 7 | | 43 | 17 | | 44 | 6 | | 45 | 7 | | 46 | 34 | | 47 | 16 | | 48 | 20 | | 49 | 5 |
| |
| 59.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.3855421686746988 | | totalSentences | 83 | | uniqueOpeners | 32 | |
| 51.28% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 65 | | matches | | 0 | "Perhaps the residue of whatever" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 12 | | totalSentences | 65 | | matches | | 0 | "She had been alerted to" | | 1 | "Her freckled cheeks were flushed," | | 2 | "She was keenly aware of" | | 3 | "She sensed the weight of" | | 4 | "she said, her voice steady," | | 5 | "She had learned early on" | | 6 | "She paused, tucking her hair" | | 7 | "They stopped near a stone" | | 8 | "Her bearing, with its military" | | 9 | "It was a woman, her" | | 10 | "Her ghostly form struggled against" | | 11 | "It was then that Harlow" |
| | ratio | 0.185 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 65 | | matches | | 0 | "The Veil Market whispered its" | | 1 | "Detective Harlow Quinn stepped into" | | 2 | "This was not her typical" | | 3 | "She had been alerted to" | | 4 | "The air was thick with" | | 5 | "Harlow's brown eyes, sharp with" | | 6 | "Stacks of ancient tomes, jars" | | 7 | "A serpentine man whispered to" | | 8 | "A voice called out, its" | | 9 | "Detective Quinn spotted her colleague," | | 10 | "Eva, with her fiery curls" | | 11 | "Her freckled cheeks were flushed," | | 12 | "Harlow had come to rely" | | 13 | "Harlow asked, her voice low," | | 14 | "The worn leather watch on" | | 15 | "Eva pulled out a notebook," | | 16 | "Harlow's eyebrows furrowed, her sharp" | | 17 | "She was keenly aware of" | | 18 | "Eva bit her lip, a" | | 19 | "Harlow's gaze swept across the" |
| | ratio | 0.938 | |
| 76.92% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 65 | | matches | | | ratio | 0.015 | |
| 82.07% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 47 | | technicalSentenceCount | 4 | | matches | | 0 | "Eva, with her fiery curls bouncing against her round glasses, approached, her satchel bumping against her side with each step." | | 1 | "Harlow's gaze swept across the market, her eyes landing on a group of humanoid creatures watching her with eyes as black as coal." | | 2 | "Eva led her through a maze of stalls, past dubious merchants and creatures that belonged in nightmares." | | 3 | "Quinn's words echoed through the chamber, the candles flickering as if in response to her determination." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 15 | | uselessAdditionCount | 9 | | matches | | 0 | "A voice called out, its urgency cutting through the market's haze" | | 1 | "Eva pulled out, her hands flipping through the pages with haste" | | 2 | "she said, her voice steady," | | 3 | "Harlow stated, a hint of accusation creeping into her voice" | | 4 | "Eva said, a note of defensiveness creeping into her tone" | | 5 | "Eva said, her voice narrating the scene" | | 6 | "Eva added, her eyes glinting with a mix of curiosity and trepidation" | | 7 | "Eva whispered, her voice carrying both awe and fear" | | 8 | "Harlow's voice carried, her determination unwavering" |
| |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 6 | | fancyTags | | 0 | "A voice called out (call out)" | | 1 | "Harlow stated (state)" | | 2 | "Eva explained (explain)" | | 3 | "Eva explained (explain)" | | 4 | "Eva added (add)" | | 5 | "Eva whispered (whisper)" |
| | dialogueSentences | 31 | | tagDensity | 0.355 | | leniency | 0.71 | | rawRatio | 0.545 | | effectiveRatio | 0.387 | |