| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.44 | | leniency | 0.88 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 91.80% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1220 | | totalAiIsmAdverbs | 2 | | 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) | |
| 50.82% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1220 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flickered" | | 1 | "silence" | | 2 | "weight" | | 3 | "constructed" | | 4 | "blown wide" | | 5 | "macabre" | | 6 | "etched" | | 7 | "echoing" | | 8 | "trembled" | | 9 | "whisper" | | 10 | "shattered" | | 11 | "pulsed" |
| |
| 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 | 0 | | narrationSentences | 86 | | matches | (empty) | |
| 93.02% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 86 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1220 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 48.79% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 988 | | uniqueNames | 13 | | maxNameDensity | 2.02 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 1 | | Tube | 2 | | Veil | 3 | | Market | 3 | | Harlow | 1 | | Quinn | 20 | | Morris | 3 | | Kowalski | 1 | | Eva | 11 | | Compass | 1 | | Shade | 1 | | Underground | 1 | | Met | 1 |
| | persons | | 0 | "Market" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Morris" | | 4 | "Kowalski" | | 5 | "Eva" | | 6 | "Compass" | | 7 | "Met" |
| | places | (empty) | | globalScore | 0.488 | | windowScore | 0.667 | |
| 30.95% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 63 | | glossingSentenceCount | 3 | | matches | | 0 | "as if searching for a centre point it couldn't find" | | 1 | "as if trying to drill through the brass" | | 2 | "patterns that seemed to move when she looked away" |
| |
| 36.07% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.639 | | wordCount | 1220 | | matches | | 0 | "Not wobbling like a faulty magnet affected by the old Underground lines, but rotating in slow, deliberate circles, pointing first toward" | | 1 | "not earth or brick but a darkness" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 99 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 31 | | mean | 39.35 | | std | 26.6 | | cv | 0.676 | | sampleLengths | | 0 | 79 | | 1 | 73 | | 2 | 99 | | 3 | 38 | | 4 | 1 | | 5 | 69 | | 6 | 66 | | 7 | 11 | | 8 | 14 | | 9 | 57 | | 10 | 2 | | 11 | 34 | | 12 | 62 | | 13 | 28 | | 14 | 51 | | 15 | 15 | | 16 | 45 | | 17 | 72 | | 18 | 45 | | 19 | 16 | | 20 | 8 | | 21 | 54 | | 22 | 6 | | 23 | 47 | | 24 | 30 | | 25 | 23 | | 26 | 44 | | 27 | 6 | | 28 | 53 | | 29 | 2 | | 30 | 70 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 155 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 99 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 990 | | adjectiveStacks | 2 | | stackExamples | | 0 | "head-down, dark hair" | | 1 | "lay crushed beneath Quinn's" |
| | adverbCount | 17 | | adverbRatio | 0.01717171717171717 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.00404040404040404 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 12.32 | | std | 8.76 | | cv | 0.711 | | sampleLengths | | 0 | 12 | | 1 | 23 | | 2 | 25 | | 3 | 19 | | 4 | 9 | | 5 | 15 | | 6 | 15 | | 7 | 15 | | 8 | 3 | | 9 | 6 | | 10 | 10 | | 11 | 9 | | 12 | 16 | | 13 | 16 | | 14 | 20 | | 15 | 10 | | 16 | 15 | | 17 | 8 | | 18 | 5 | | 19 | 17 | | 20 | 11 | | 21 | 10 | | 22 | 1 | | 23 | 25 | | 24 | 15 | | 25 | 29 | | 26 | 17 | | 27 | 13 | | 28 | 17 | | 29 | 13 | | 30 | 6 | | 31 | 11 | | 32 | 3 | | 33 | 11 | | 34 | 21 | | 35 | 36 | | 36 | 2 | | 37 | 10 | | 38 | 24 | | 39 | 2 | | 40 | 9 | | 41 | 9 | | 42 | 17 | | 43 | 13 | | 44 | 12 | | 45 | 9 | | 46 | 19 | | 47 | 4 | | 48 | 47 | | 49 | 4 |
| |
| 56.46% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.3877551020408163 | | totalSentences | 98 | | uniqueOpeners | 38 | |
| 87.72% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 76 | | matches | | 0 | "Just the body, swaying in" | | 1 | "Then the needle began to" |
| | ratio | 0.026 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 76 | | matches | | 0 | "Her worn leather watch ticked" | | 1 | "She had found him in" | | 2 | "Her freckled fingers clutched a" | | 3 | "She spoke in the clipped," | | 4 | "Her eyes were open, pupils" | | 5 | "she said to Eva" | | 6 | "It hung rigid, a macabre" | | 7 | "She reached into the pocket" | | 8 | "Her jaw tightened." | | 9 | "Her palm was clammy, cold." | | 10 | "She turned the compass over" | | 11 | "Her breath caught, a sharp" | | 12 | "It pointed directly at the" | | 13 | "She walked to the wall," | | 14 | "She placed her palm against" | | 15 | "They felt normal." | | 16 | "She pressed the glowing compass" |
| | ratio | 0.224 | |
| 58.68% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 76 | | matches | | 0 | "Quinn ducked beneath the yellow" | | 1 | "Ozone and wet rust, thick" | | 2 | "The abandoned Camden Tube station" | | 3 | "Detective Harlow Quinn stopped three" | | 4 | "Her worn leather watch ticked" | | 5 | "The corpse hung head-down, dark" | | 6 | "Stalls constructed from salvaged Tube" | | 7 | "A bone token lay crushed" | | 8 | "The air tasted of ozone" | | 9 | "Quinn had entered this station" | | 10 | "She had found him in" | | 11 | "The case had been closed" | | 12 | "Quinn had never believed it." | | 13 | "Eva Kowalski looked up from" | | 14 | "Her freckled fingers clutched a" | | 15 | "Eva tucked a strand of" | | 16 | "She spoke in the clipped," | | 17 | "Quinn circled the body with" | | 18 | "The victim, female, mid-thirties, wore" | | 19 | "Her eyes were open, pupils" |
| | ratio | 0.803 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | | ratio | 0.013 | |
| 48.87% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 5 | | matches | | 0 | "Fluorescent tubes flickered overhead, casting the suspended corpse in strobing shadows that made the air shimmer like heat haze." | | 1 | "Not wobbling like a faulty magnet affected by the old Underground lines, but rotating in slow, deliberate circles, pointing first toward the northern tunnel, th…" | | 2 | "It pointed directly at the far wall of the station, at a section of tiled concrete that looked solid, unremarkable, covered in decades of grime, pigeon dropping…" | | 3 | "The sigils on the compass face flared brighter, burning afterimages into Quinn's retinas, geometric patterns that seemed to move when she looked away." | | 4 | "The tiles shattered outward, revealing not earth or brick but a darkness that breathed, a void that pulsed with a rhythm like a heartbeat." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 4 | | matches | | 0 | "Eva tucked, her nervous habit betraying the academic certainty in her voice" | | 1 | "Eva's voice sharpened, her glasses sliding down her nose" | | 2 | "Eva grabbed, her academic composure cracking" | | 3 | "Eva said, her voice rising" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 25 | | tagDensity | 0.12 | | leniency | 0.24 | | rawRatio | 0 | | effectiveRatio | 0 | |