| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 46 | | tagDensity | 0.239 | | leniency | 0.478 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1128 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 42.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1128 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "flickered" | | 1 | "pulse" | | 2 | "traced" | | 3 | "stomach" | | 4 | "eyebrow" | | 5 | "unreadable" | | 6 | "dance" | | 7 | "flicked" | | 8 | "weight" | | 9 | "scanning" | | 10 | "tension" |
| |
| 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 | 100 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 100 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 133 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 6 | | totalWords | 1115 | | ratio | 0.005 | | matches | | 0 | "The Raven’s Nest" | | 1 | "You’re leaving me" |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 78.96% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 36 | | wordCount | 915 | | uniqueNames | 11 | | maxNameDensity | 1.42 | | worstName | "Silas" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Rory | 12 | | Carter | 1 | | Silas | 13 | | Blackwood | 1 | | Prague | 1 | | Kensington | 1 | | London | 1 | | Evan | 1 | | Cardiff | 1 | | Should | 3 |
| | persons | | 0 | "Raven" | | 1 | "Rory" | | 2 | "Carter" | | 3 | "Silas" | | 4 | "Blackwood" | | 5 | "Evan" | | 6 | "Should" |
| | places | | 0 | "Prague" | | 1 | "Kensington" | | 2 | "London" | | 3 | "Cardiff" |
| | globalScore | 0.79 | | windowScore | 0.833 | |
| 60.71% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 56 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared beside them, sliding a fresh glass toward Silas" | | 1 | "felt like it belonged to them" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1115 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 133 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 58 | | mean | 19.22 | | std | 19.36 | | cv | 1.007 | | sampleLengths | | 0 | 81 | | 1 | 49 | | 2 | 4 | | 3 | 90 | | 4 | 16 | | 5 | 75 | | 6 | 2 | | 7 | 15 | | 8 | 18 | | 9 | 36 | | 10 | 6 | | 11 | 12 | | 12 | 30 | | 13 | 23 | | 14 | 28 | | 15 | 8 | | 16 | 6 | | 17 | 27 | | 18 | 21 | | 19 | 64 | | 20 | 6 | | 21 | 12 | | 22 | 16 | | 23 | 2 | | 24 | 24 | | 25 | 10 | | 26 | 4 | | 27 | 22 | | 28 | 14 | | 29 | 8 | | 30 | 50 | | 31 | 17 | | 32 | 15 | | 33 | 5 | | 34 | 7 | | 35 | 6 | | 36 | 10 | | 37 | 12 | | 38 | 4 | | 39 | 22 | | 40 | 21 | | 41 | 15 | | 42 | 3 | | 43 | 32 | | 44 | 8 | | 45 | 2 | | 46 | 1 | | 47 | 14 | | 48 | 14 | | 49 | 24 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 100 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 175 | | matches | (empty) | |
| 13.96% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 6 | | totalSentences | 133 | | ratio | 0.045 | | matches | | 0 | "The place hadn’t changed—same sticky floorboards, same low hum of conversation, same way the light pooled in thick, golden pools over the polished mahogany bar." | | 1 | "She ordered a gin and tonic—neat, no ice—and took a stool near the back, where the shadows clung tighter." | | 2 | "The scar above his eyebrow—she’d forgotten about that." | | 3 | "His hazel eyes—always too sharp, too knowing—locked onto hers." | | 4 | "Rory remembered the last time she’d seen him—his apartment in Kensington, the night before she left for London." | | 5 | "From Evan, from Cardiff, from the life she’d been building—from the life she’d thought she wanted." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 927 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 32 | | adverbRatio | 0.034519956850053934 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.004314994606256742 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 133 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 133 | | mean | 8.38 | | std | 6.81 | | cv | 0.813 | | sampleLengths | | 0 | 36 | | 1 | 25 | | 2 | 20 | | 3 | 19 | | 4 | 17 | | 5 | 13 | | 6 | 4 | | 7 | 22 | | 8 | 25 | | 9 | 20 | | 10 | 23 | | 11 | 3 | | 12 | 10 | | 13 | 3 | | 14 | 26 | | 15 | 8 | | 16 | 17 | | 17 | 24 | | 18 | 2 | | 19 | 9 | | 20 | 3 | | 21 | 3 | | 22 | 12 | | 23 | 6 | | 24 | 5 | | 25 | 9 | | 26 | 20 | | 27 | 1 | | 28 | 1 | | 29 | 6 | | 30 | 4 | | 31 | 8 | | 32 | 12 | | 33 | 7 | | 34 | 7 | | 35 | 4 | | 36 | 7 | | 37 | 16 | | 38 | 23 | | 39 | 5 | | 40 | 3 | | 41 | 5 | | 42 | 3 | | 43 | 3 | | 44 | 5 | | 45 | 5 | | 46 | 10 | | 47 | 7 | | 48 | 2 | | 49 | 12 |
| |
| 42.48% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.2781954887218045 | | totalSentences | 133 | | uniqueOpeners | 37 | |
| 77.52% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 86 | | matches | | 0 | "Then she saw him." | | 1 | "Instead, she reached into her" |
| | ratio | 0.023 | |
| 61.86% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 86 | | matches | | 0 | "She’d only been inside a" | | 1 | "She ordered a gin and" | | 2 | "His auburn hair, streaked now" | | 3 | "He moved with that same" | | 4 | "She should’ve left." | | 5 | "She’d pressed her fingers to" | | 6 | "His voice cut through the" | | 7 | "She finally looked at him." | | 8 | "His hazel eyes—always too sharp," | | 9 | "he said, voice low" | | 10 | "He tossed a few notes" | | 11 | "His jaw tightened." | | 12 | "She should’ve let it go." | | 13 | "They’d been drunk, laughing, his" | | 14 | "*You’re leaving me*, he’d said," | | 15 | "She’d been twenty-two." | | 16 | "He’d been thirty-five." | | 17 | "she asked, voice lighter than" | | 18 | "His gaze flicked to the" | | 19 | "She almost choked." |
| | ratio | 0.395 | |
| 23.95% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 75 | | totalSentences | 86 | | matches | | 0 | "The neon green sign of" | | 1 | "The place hadn’t changed—same sticky" | | 2 | "She’d only been inside a" | | 3 | "She ordered a gin and" | | 4 | "The bartender, a wiry man" | | 5 | "Rory traced the rim with" | | 6 | "Silas Blackwood stood at the" | | 7 | "His auburn hair, streaked now" | | 8 | "He moved with that same" | | 9 | "The limp in his left" | | 10 | "She should’ve left." | | 11 | "The man in the suit" | | 12 | "The scar above his eyebrow—she’d" | | 13 | "A souvenir from Prague, he’d" | | 14 | "She’d pressed her fingers to" | | 15 | "His voice cut through the" | | 16 | "Rory didn’t turn." | | 17 | "Silas exhaled through his nose," | | 18 | "She finally looked at him." | | 19 | "His hazel eyes—always too sharp," |
| | ratio | 0.872 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 86 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "The limp in his left leg was more pronounced than she recalled, a faint hitch in his step that made her stomach tighten." | | 1 | "*You’re leaving me*, he’d said, but she’d kissed him instead, her fingers tangling in his hair." |
| |
| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 1 | | matches | | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 46 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0 | | effectiveRatio | 0 | |