| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "He stepped back [back]" |
| | dialogueSentences | 31 | | tagDensity | 0.161 | | leniency | 0.323 | | rawRatio | 0.2 | | effectiveRatio | 0.065 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1172 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 48.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1172 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "echo" | | 1 | "silence" | | 2 | "chill" | | 3 | "weight" | | 4 | "etched" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "familiar" | | 8 | "flicked" | | 9 | "pulse" |
| |
| 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 | 147 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 147 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 173 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 21 | | totalWords | 1179 | | ratio | 0.018 | | matches | | 0 | "The Raven’s Nest" | | 1 | "Keep time with the dead, Harlow. They’re the only ones telling the truth." | | 2 | "The Veil Market." | | 3 | "Tomás Herrera." |
| |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 915 | | uniqueNames | 12 | | maxNameDensity | 0.44 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Herrera" | | discoveredNames | | Harlow | 2 | | Quinn | 4 | | Berwick | 1 | | Street | 1 | | Raven | 1 | | Veil | 1 | | Met | 1 | | Police | 1 | | Saint | 1 | | Christopher | 1 | | Herrera | 4 | | Morris | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Raven" | | 3 | "Veil" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Herrera" | | 7 | "Morris" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a bird with too many eyes" |
| |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.545 | | wordCount | 1179 | | matches | | 0 | "not by machine but by time" | | 1 | "Not a tunnel, not a station, but a cavern" | | 2 | "not a station, but a cavern" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 173 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 72 | | mean | 16.38 | | std | 15.29 | | cv | 0.934 | | sampleLengths | | 0 | 13 | | 1 | 36 | | 2 | 38 | | 3 | 3 | | 4 | 34 | | 5 | 49 | | 6 | 5 | | 7 | 2 | | 8 | 45 | | 9 | 27 | | 10 | 7 | | 11 | 51 | | 12 | 45 | | 13 | 36 | | 14 | 4 | | 15 | 8 | | 16 | 80 | | 17 | 3 | | 18 | 26 | | 19 | 19 | | 20 | 36 | | 21 | 3 | | 22 | 30 | | 23 | 33 | | 24 | 9 | | 25 | 9 | | 26 | 18 | | 27 | 5 | | 28 | 6 | | 29 | 5 | | 30 | 21 | | 31 | 6 | | 32 | 11 | | 33 | 22 | | 34 | 9 | | 35 | 23 | | 36 | 2 | | 37 | 24 | | 38 | 7 | | 39 | 9 | | 40 | 2 | | 41 | 30 | | 42 | 6 | | 43 | 1 | | 44 | 10 | | 45 | 6 | | 46 | 13 | | 47 | 3 | | 48 | 31 | | 49 | 5 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 147 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 157 | | matches | (empty) | |
| 27.25% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 173 | | ratio | 0.04 | | matches | | 0 | "Neon signs bled in the puddles — pink, green, smeared gold — but the green one, pulsing like a slow heartbeat, held her gaze for half a second." | | 1 | "Not the absence of sound — the presence of something that swallowed it." | | 2 | "People — not all of them quite human — moved in slow currents." | | 3 | "The suspect — young, thin, moving like every shadow threatened him — handed over a small leather pouch." | | 4 | "Just turned — and ran." | | 5 | "Then — silence." | | 6 | "A cry split the air — not human, not animal." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 908 | | adjectiveStacks | 1 | | stackExamples | | 0 | "suspect — young, thin, moving like" |
| | adverbCount | 30 | | adverbRatio | 0.03303964757709251 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003303964757709251 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 173 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 173 | | mean | 6.82 | | std | 5.64 | | cv | 0.828 | | sampleLengths | | 0 | 13 | | 1 | 4 | | 2 | 3 | | 3 | 15 | | 4 | 10 | | 5 | 4 | | 6 | 26 | | 7 | 3 | | 8 | 2 | | 9 | 7 | | 10 | 3 | | 11 | 10 | | 12 | 7 | | 13 | 6 | | 14 | 11 | | 15 | 4 | | 16 | 28 | | 17 | 3 | | 18 | 1 | | 19 | 2 | | 20 | 5 | | 21 | 1 | | 22 | 5 | | 23 | 5 | | 24 | 2 | | 25 | 9 | | 26 | 11 | | 27 | 2 | | 28 | 2 | | 29 | 13 | | 30 | 2 | | 31 | 6 | | 32 | 8 | | 33 | 13 | | 34 | 6 | | 35 | 7 | | 36 | 3 | | 37 | 5 | | 38 | 13 | | 39 | 13 | | 40 | 8 | | 41 | 9 | | 42 | 10 | | 43 | 9 | | 44 | 6 | | 45 | 20 | | 46 | 5 | | 47 | 2 | | 48 | 2 | | 49 | 27 |
| |
| 74.37% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.47398843930635837 | | totalSentences | 173 | | uniqueOpeners | 82 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 111 | | matches | | 0 | "Somewhere, a pipe dripped with" | | 1 | "Then silence, thick and wrong." | | 2 | "Just an empty alley, a" | | 3 | "Just turned — and ran." | | 4 | "Then stepped into the open." | | 5 | "Then she saw it." | | 6 | "Then — silence." | | 7 | "Then back at Herrera." |
| | ratio | 0.072 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 111 | | matches | | 0 | "She didn’t look down." | | 1 | "She knew the gap between" | | 2 | "Her landing cracked through the" | | 3 | "She was already moving, coat" | | 4 | "She squeezed through, metal scraping" | | 5 | "Her fingers found the worn" | | 6 | "They’re the only ones telling" | | 7 | "She took the steps." | | 8 | "She’d heard rumours." | | 9 | "She closed in, staying low," | | 10 | "Her hand hovered over her" | | 11 | "She didn’t flinch." | | 12 | "She took out her phone." | | 13 | "She’d come across his name" | | 14 | "He wore a worn leather" | | 15 | "He stepped closer" | | 16 | "His gaze flicked to her" | | 17 | "He glanced past her, toward" | | 18 | "He stepped back" | | 19 | "Her pulse thrummed in her" |
| | ratio | 0.225 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 68 | | totalSentences | 111 | | matches | | 0 | "The fire escape groaned under" | | 1 | "She didn’t look down." | | 2 | "She knew the gap between" | | 3 | "Something heavier than a fistful" | | 4 | "Quinn launched herself." | | 5 | "Her landing cracked through the" | | 6 | "Ankles flexed, absorbed the impact," | | 7 | "She was already moving, coat" | | 8 | "Rain needled her face." | | 9 | "Neon signs bled in the" | | 10 | "*The Raven’s Nest*." | | 11 | "A crack in the world." | | 12 | "The suspect vanished into it." | | 13 | "The alley stank of rotting" | | 14 | "A rusted ventilation grate, half-pried" | | 15 | "She squeezed through, metal scraping" | | 16 | "Stone steps spiraled down, carved" | | 17 | "Graffiti tagged them in symbols" | | 18 | "Her fingers found the worn" | | 19 | "Morris had given her this" |
| | ratio | 0.613 | |
| 90.09% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 111 | | matches | | 0 | "Now, she felt the weight" | | 1 | "To the right, a narrow" |
| | ratio | 0.018 | |
| 93.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 2 | | matches | | 0 | "Not the absence of sound — the presence of something that swallowed it." | | 1 | "Just an empty alley, a single boot, and a stain on the pavement that smelled of burnt almonds and something older, like wet stone behind cathedral walls." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |