| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 22 | | adverbTagCount | 1 | | adverbTags | | 0 | "She gestured around [around]" |
| | dialogueSentences | 47 | | tagDensity | 0.468 | | leniency | 0.936 | | rawRatio | 0.045 | | effectiveRatio | 0.043 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1448 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 51.66% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1448 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "footsteps" | | 1 | "pulse" | | 2 | "familiar" | | 3 | "measured" | | 4 | "methodical" | | 5 | "perfect" | | 6 | "stark" | | 7 | "eyebrow" | | 8 | "unreadable" | | 9 | "whisper" | | 10 | "echoes" | | 11 | "mosaic" | | 12 | "warmth" | | 13 | "scanning" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 88 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 88 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 110 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1443 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 17 | | wordCount | 995 | | uniqueNames | 5 | | maxNameDensity | 0.8 | | worstName | "Silas" | | maxWindowNameDensity | 2 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Eva | 2 | | Silas | 8 | | Rory | 5 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Eva" | | 3 | "Silas" | | 4 | "Rory" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 36.36% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a portrait of a man, solid an" | | 1 | "felt like it belonged to strangers" | | 2 | "sounded like a warning" |
| |
| 61.40% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.386 | | wordCount | 1443 | | matches | | 0 | "not a weapon or a dossier, but a small, worn photograph" | | 1 | "not painfully, but with an unbreakable grip" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 98.82% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 41 | | mean | 35.2 | | std | 17.45 | | cv | 0.496 | | sampleLengths | | 0 | 64 | | 1 | 84 | | 2 | 40 | | 3 | 1 | | 4 | 73 | | 5 | 25 | | 6 | 37 | | 7 | 38 | | 8 | 20 | | 9 | 26 | | 10 | 38 | | 11 | 23 | | 12 | 40 | | 13 | 44 | | 14 | 23 | | 15 | 36 | | 16 | 26 | | 17 | 17 | | 18 | 2 | | 19 | 38 | | 20 | 17 | | 21 | 44 | | 22 | 65 | | 23 | 26 | | 24 | 42 | | 25 | 15 | | 26 | 38 | | 27 | 53 | | 28 | 33 | | 29 | 30 | | 30 | 27 | | 31 | 14 | | 32 | 55 | | 33 | 25 | | 34 | 46 | | 35 | 25 | | 36 | 19 | | 37 | 58 | | 38 | 41 | | 39 | 42 | | 40 | 33 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 88 | | matches | (empty) | |
| 64.86% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 148 | | matches | | 0 | "wasn’t looking" | | 1 | "was looking" | | 2 | "wasn’t asking" |
| |
| 64.94% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 110 | | ratio | 0.027 | | matches | | 0 | "She’d been staring at a particular photograph—a group of men in trench coats, squinting against a sun that wasn’t there—when the swing of the door brushed a different kind of air against her neck." | | 1 | "The background noise of the bar—the low murmur of conversation, the clink of glasses, the muted jazz from unseen speakers—seemed to recede." | | 2 | "Before Silas could answer, a heavy, deliberate cough came from the direction of the hidden back room—the bookshelf that wasn’t a bookshelf." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1006 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 29 | | adverbRatio | 0.02882703777335984 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.006958250497017893 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 110 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 110 | | mean | 13.12 | | std | 8 | | cv | 0.609 | | sampleLengths | | 0 | 8 | | 1 | 24 | | 2 | 25 | | 3 | 7 | | 4 | 17 | | 5 | 9 | | 6 | 24 | | 7 | 34 | | 8 | 3 | | 9 | 3 | | 10 | 18 | | 11 | 12 | | 12 | 4 | | 13 | 1 | | 14 | 17 | | 15 | 18 | | 16 | 17 | | 17 | 10 | | 18 | 11 | | 19 | 19 | | 20 | 6 | | 21 | 7 | | 22 | 10 | | 23 | 11 | | 24 | 9 | | 25 | 3 | | 26 | 22 | | 27 | 10 | | 28 | 3 | | 29 | 20 | | 30 | 18 | | 31 | 8 | | 32 | 16 | | 33 | 12 | | 34 | 10 | | 35 | 11 | | 36 | 9 | | 37 | 3 | | 38 | 3 | | 39 | 21 | | 40 | 16 | | 41 | 23 | | 42 | 21 | | 43 | 12 | | 44 | 11 | | 45 | 20 | | 46 | 6 | | 47 | 10 | | 48 | 20 | | 49 | 6 |
| |
| 45.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.33636363636363636 | | totalSentences | 110 | | uniqueOpeners | 37 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 8.51% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 46 | | totalSentences | 87 | | matches | | 0 | "It was a bar built" | | 1 | "She’d come for anonymity, a" | | 2 | "She’d been staring at a" | | 3 | "She didn’t turn." | | 4 | "His name left her mouth" | | 5 | "He was taller than she" | | 6 | "He looked like a portrait" | | 7 | "His voice was the same," | | 8 | "She felt the old scar" | | 9 | "She gestured to the empty" | | 10 | "He didn’t smile." | | 11 | "He moved to the stool" | | 12 | "He signalled to the bartender" | | 13 | "he said, not looking at" | | 14 | "She nodded at the walls" | | 15 | "He took a sip, finally" | | 16 | "His hazel eyes, once sharp" | | 17 | "She softened them with a" | | 18 | "He studied her face, a" | | 19 | "She’d rehearsed it a hundred" |
| | ratio | 0.529 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 87 | | matches | | 0 | "The Raven’s Nest lived up" | | 1 | "A perpetual twilight clung to" | | 2 | "Maps of places that no" | | 3 | "It was a bar built" | | 4 | "Rory perched on a worn" | | 5 | "The condensation made cold, slick" | | 6 | "She’d come for anonymity, a" | | 7 | "She’d been staring at a" | | 8 | "She didn’t turn." | | 9 | "A slight hesitation on the" | | 10 | "The old knee injury." | | 11 | "His name left her mouth" | | 12 | "The man at the door" | | 13 | "He was taller than she" | | 14 | "The grey-streaked auburn hair was" | | 15 | "He looked like a portrait" | | 16 | "His voice was the same," | | 17 | "The jab was precise, a" | | 18 | "She felt the old scar" | | 19 | "She gestured to the empty" |
| | ratio | 0.966 | |
| 57.47% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 87 | | matches | | 0 | "Before Silas could answer, a" |
| | ratio | 0.011 | |
| 65.64% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 4 | | matches | | 0 | "She’d been staring at a particular photograph—a group of men in trench coats, squinting against a sun that wasn’t there—when the swing of the door brushed a dif…" | | 1 | "Before Silas could answer, a heavy, deliberate cough came from the direction of the hidden back room—the bookshelf that wasn’t a bookshelf." | | 2 | "He moved with a speed that belied his limp, snatching the photograph off the bar and pocketing it in one fluid motion." | | 3 | "The two men at the door started moving towards the bar, their eyes scanning the room with cold, professional indifference." |
| |
| 79.55% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 22 | | uselessAdditionCount | 2 | | matches | | 0 | "she said, her voice lower" | | 1 | "Rory said, the pieces clicking into a terrifying mosaic" |
| |
| 86.17% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 3 | | fancyTags | | 0 | "He corrected (correct)" | | 1 | "She laughed (laugh)" | | 2 | "Silas murmured (murmur)" |
| | dialogueSentences | 47 | | tagDensity | 0.213 | | leniency | 0.426 | | rawRatio | 0.3 | | effectiveRatio | 0.128 | |