| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 25 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 138 | | tagDensity | 0.181 | | leniency | 0.362 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2239 | | 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) | |
| 91.07% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2239 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "coded" | | 1 | "etched" | | 2 | "trembled" | | 3 | "weight" |
| |
| 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 | 154 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 154 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 266 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 30 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2239 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 32 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 80 | | wordCount | 1199 | | uniqueNames | 7 | | maxNameDensity | 2.92 | | worstName | "Quinn" | | maxWindowNameDensity | 6 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 35 | | Tube | 1 | | Sergeant | 1 | | Bell | 25 | | Price | 6 | | Eva | 11 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Sergeant" | | 3 | "Bell" | | 4 | "Price" | | 5 | "Eva" |
| | places | (empty) | | globalScore | 0.04 | | windowScore | 0 | |
| 95.05% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | glossingSentenceCount | 2 | | matches | | 0 | "something like cold pennies held in a closed" | | 1 | "not quite" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.447 | | wordCount | 2239 | | matches | | 0 | "not from damp but from a fine black residue rubbed into the seams" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 266 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 155 | | mean | 14.45 | | std | 12.78 | | cv | 0.885 | | sampleLengths | | 0 | 15 | | 1 | 41 | | 2 | 23 | | 3 | 7 | | 4 | 12 | | 5 | 30 | | 6 | 10 | | 7 | 41 | | 8 | 3 | | 9 | 30 | | 10 | 47 | | 11 | 8 | | 12 | 8 | | 13 | 13 | | 14 | 52 | | 15 | 11 | | 16 | 4 | | 17 | 12 | | 18 | 6 | | 19 | 10 | | 20 | 32 | | 21 | 7 | | 22 | 16 | | 23 | 11 | | 24 | 11 | | 25 | 52 | | 26 | 5 | | 27 | 1 | | 28 | 15 | | 29 | 16 | | 30 | 11 | | 31 | 60 | | 32 | 45 | | 33 | 6 | | 34 | 2 | | 35 | 1 | | 36 | 3 | | 37 | 8 | | 38 | 11 | | 39 | 16 | | 40 | 42 | | 41 | 2 | | 42 | 9 | | 43 | 7 | | 44 | 16 | | 45 | 44 | | 46 | 47 | | 47 | 8 | | 48 | 4 | | 49 | 4 |
| |
| 93.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 154 | | matches | | 0 | "been carved" | | 1 | "was tied" | | 2 | "been tied" | | 3 | "been disturbed" | | 4 | "been etched" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 212 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 266 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1201 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 21 | | adverbRatio | 0.017485428809325562 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0008326394671107411 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 266 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 266 | | mean | 8.42 | | std | 5.75 | | cv | 0.683 | | sampleLengths | | 0 | 15 | | 1 | 18 | | 2 | 13 | | 3 | 10 | | 4 | 9 | | 5 | 14 | | 6 | 3 | | 7 | 4 | | 8 | 8 | | 9 | 4 | | 10 | 6 | | 11 | 19 | | 12 | 5 | | 13 | 10 | | 14 | 3 | | 15 | 11 | | 16 | 27 | | 17 | 3 | | 18 | 30 | | 19 | 6 | | 20 | 14 | | 21 | 15 | | 22 | 12 | | 23 | 4 | | 24 | 4 | | 25 | 4 | | 26 | 4 | | 27 | 13 | | 28 | 11 | | 29 | 17 | | 30 | 7 | | 31 | 17 | | 32 | 4 | | 33 | 7 | | 34 | 4 | | 35 | 12 | | 36 | 6 | | 37 | 5 | | 38 | 5 | | 39 | 6 | | 40 | 16 | | 41 | 10 | | 42 | 7 | | 43 | 16 | | 44 | 6 | | 45 | 5 | | 46 | 11 | | 47 | 4 | | 48 | 8 | | 49 | 17 |
| |
| 48.87% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.2894736842105263 | | totalSentences | 266 | | uniqueOpeners | 77 | |
| 50.13% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 133 | | matches | | 0 | "Somewhere beyond the tiled arch," | | 1 | "Just the arcs, pale against" |
| | ratio | 0.015 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 31 | | totalSentences | 133 | | matches | | 0 | "Their light caught the damp" | | 1 | "He was a broad man" | | 2 | "His mouth tightened." | | 3 | "He set the cup on" | | 4 | "Her worn leather watch pressed" | | 5 | "His other hand rested near" | | 6 | "She kept her hands off" | | 7 | "She studied the body." | | 8 | "His shirt was open at" | | 9 | "Its surface wasn’t metal, not" | | 10 | "She’d never seen one with" | | 11 | "It was tied to a" | | 12 | "It had been tied to" | | 13 | "She walked along the platform," | | 14 | "It ended beside a tiled" | | 15 | "It was no bigger than" | | 16 | "It swung in a quick" | | 17 | "It aimed towards a section" | | 18 | "Her gaze caught on a" | | 19 | "She held her palm near" |
| | ratio | 0.233 | |
| 20.15% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 117 | | totalSentences | 133 | | matches | | 0 | "Detective Harlow Quinn ducked beneath" | | 1 | "The platform lamps had no" | | 2 | "Their light caught the damp" | | 3 | "Quinn looked down." | | 4 | "The platform was dry." | | 5 | "Bell turned from the ticket-office" | | 6 | "He was a broad man" | | 7 | "His mouth tightened." | | 8 | "He set the cup on" | | 9 | "Quinn moved towards the ticket" | | 10 | "Her worn leather watch pressed" | | 11 | "The building smelled of wet" | | 12 | "Bell followed her in." | | 13 | "The ticket office had a" | | 14 | "Gideon Price lay on his" | | 15 | "A dark stain spread over" | | 16 | "His other hand rested near" | | 17 | "Quinn crouched beside him." | | 18 | "She kept her hands off" | | 19 | "Bell glanced at the floor." |
| | ratio | 0.88 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 133 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 40 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 25 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 18 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 138 | | tagDensity | 0.13 | | leniency | 0.261 | | rawRatio | 0 | | effectiveRatio | 0 | |