| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 28 | | tagDensity | 0.464 | | leniency | 0.929 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.79% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 986 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "loosely" | | 1 | "sharply" | | 2 | "suddenly" |
| |
| 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) | |
| 44.22% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 986 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "oppressive" | | 1 | "sturdy" | | 2 | "etched" | | 3 | "unwavering" | | 4 | "scanned" | | 5 | "raced" | | 6 | "beacon" | | 7 | "depths" | | 8 | "quivered" | | 9 | "flickered" | | 10 | "echoed" |
| |
| 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 | 1 | | narrationSentences | 73 | | matches | | |
| 84.15% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 73 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 976 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 85.99% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 703 | | uniqueNames | 6 | | maxNameDensity | 1.28 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Quinn | 9 | | Fletcher | 4 | | London | 1 | | Textbooks | 1 | | Morris | 1 |
| | persons | | 0 | "Detective" | | 1 | "Quinn" | | 2 | "Fletcher" | | 3 | "Morris" |
| | places | | | globalScore | 0.86 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 1 | | matches | | 0 | "sigils that seemed to writhe in the torchlight" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 976 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 29.58 | | std | 18.89 | | cv | 0.639 | | sampleLengths | | 0 | 18 | | 1 | 47 | | 2 | 28 | | 3 | 28 | | 4 | 48 | | 5 | 64 | | 6 | 9 | | 7 | 12 | | 8 | 50 | | 9 | 8 | | 10 | 24 | | 11 | 42 | | 12 | 4 | | 13 | 30 | | 14 | 30 | | 15 | 48 | | 16 | 23 | | 17 | 65 | | 18 | 3 | | 19 | 20 | | 20 | 42 | | 21 | 44 | | 22 | 6 | | 23 | 5 | | 24 | 46 | | 25 | 5 | | 26 | 56 | | 27 | 52 | | 28 | 11 | | 29 | 26 | | 30 | 3 | | 31 | 34 | | 32 | 45 |
| |
| 86.04% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 73 | | matches | | 0 | "were clutched" | | 1 | "was dressed" | | 2 | "was patinated" | | 3 | "was tucked" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 111 | | matches | (empty) | |
| 78.65% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 2 | | totalSentences | 89 | | ratio | 0.022 | | matches | | 0 | "A worn leather satchel lay a few feet away, its contents—a jumble of books and papers—spilled across the grimy concrete." | | 1 | "She noted the quality of the woman’s clothes—well-made but practical." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 441 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Ancient, leather-bound volumes" |
| | adverbCount | 14 | | adverbRatio | 0.031746031746031744 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.006802721088435374 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 10.97 | | std | 6.71 | | cv | 0.612 | | sampleLengths | | 0 | 14 | | 1 | 4 | | 2 | 8 | | 3 | 1 | | 4 | 15 | | 5 | 15 | | 6 | 8 | | 7 | 21 | | 8 | 7 | | 9 | 28 | | 10 | 14 | | 11 | 12 | | 12 | 12 | | 13 | 10 | | 14 | 20 | | 15 | 2 | | 16 | 9 | | 17 | 13 | | 18 | 20 | | 19 | 9 | | 20 | 4 | | 21 | 8 | | 22 | 16 | | 23 | 3 | | 24 | 5 | | 25 | 12 | | 26 | 14 | | 27 | 3 | | 28 | 5 | | 29 | 14 | | 30 | 10 | | 31 | 9 | | 32 | 10 | | 33 | 9 | | 34 | 8 | | 35 | 6 | | 36 | 4 | | 37 | 10 | | 38 | 20 | | 39 | 21 | | 40 | 9 | | 41 | 5 | | 42 | 17 | | 43 | 7 | | 44 | 19 | | 45 | 11 | | 46 | 12 | | 47 | 18 | | 48 | 21 | | 49 | 5 |
| |
| 64.79% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.449438202247191 | | totalSentences | 89 | | uniqueOpeners | 40 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 69 | | matches | | 0 | "She was still breaking him" | | 1 | "She clipped her badge back" | | 2 | "Her curly red hair fanned" | | 3 | "She didn’t look at him," | | 4 | "Her hands were clutched loosely" | | 5 | "She noted the quality of" | | 6 | "She was dressed for a" | | 7 | "He came to stand beside" | | 8 | "She moved to the books." | | 9 | "Its casing was patinated with" | | 10 | "It spun in a lazy," | | 11 | "She held it steady" | | 12 | "Her eyes scanned the area" | | 13 | "Her gaze fell on the" | | 14 | "She’d missed it before." | | 15 | "She looked from the bizarre" | | 16 | "She stood, her bearing rigid" |
| | ratio | 0.246 | |
| 32.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 69 | | matches | | 0 | "The voice belonged to Fletcher," | | 1 | "She was still breaking him" | | 2 | "The corridor they stood in" | | 3 | "She clipped her badge back" | | 4 | "Quinn moved past him, her" | | 5 | "The platform was a cavernous" | | 6 | "The tracks were dark, empty" | | 7 | "The woman was slight, with" | | 8 | "Her curly red hair fanned" | | 9 | "A worn leather satchel lay" | | 10 | "Quinn asked, her voice flat" | | 11 | "Fletcher consulted his notes." | | 12 | "She didn’t look at him," | | 13 | "The woman’s round glasses were" | | 14 | "Her hands were clutched loosely" | | 15 | "Something was off." | | 16 | "The whole tableau felt staged." | | 17 | "A forensics tech in a" | | 18 | "Quinn crouched by the body," | | 19 | "She noted the quality of" |
| | ratio | 0.855 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 66.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 3 | | matches | | 0 | "Its casing was patinated with green verdigris, its face etched with strange, angular sigils that seemed to writhe in the torchlight." | | 1 | "A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information." | | 2 | "From the depth of the tunnel the compass pointed to, a soft, shuffling sound echoed, followed by the distinct, wet click-click of something that was most defini…" |
| |
| 9.62% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 3 | | matches | | 0 | "Quinn asked, her voice flat" | | 1 | "Fletcher said, a hint of dismissal in his tone" | | 2 | "She stood, her bearing rigid with military precision" |
| |
| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Fletcher observed (observe)" | | 1 | "Quinn murmured (murmur)" |
| | dialogueSentences | 28 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.5 | | effectiveRatio | 0.143 | |