| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 34 | | adverbTagCount | 2 | | adverbTags | | 0 | "Quinn turned back [back]" | | 1 | "the voice said again [again]" |
| | dialogueSentences | 73 | | tagDensity | 0.466 | | leniency | 0.932 | | rawRatio | 0.059 | | effectiveRatio | 0.055 | |
| 96.75% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1540 | | totalAiIsmAdverbs | 1 | | 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) | |
| 54.55% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1540 | | totalAiIsms | 14 | | found | | | highlights | | 0 | "standard" | | 1 | "vibrated" | | 2 | "scanned" | | 3 | "etched" | | 4 | "traced" | | 5 | "footsteps" | | 6 | "echoed" | | 7 | "silence" | | 8 | "flickered" |
| |
| 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 | 287 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 287 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 327 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 16 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1540 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 30 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 72 | | wordCount | 1285 | | uniqueNames | 7 | | maxNameDensity | 2.96 | | worstName | "Quinn" | | maxWindowNameDensity | 6.5 | | worstWindowName | "Miller" | | discoveredNames | | Tube | 1 | | Camden | 1 | | Miller | 27 | | Quinn | 38 | | Morris | 1 | | Bermondsey | 1 | | Three | 3 |
| | persons | | 0 | "Miller" | | 1 | "Quinn" | | 2 | "Morris" |
| | places | | | globalScore | 0.021 | | windowScore | 0 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 66 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1540 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 327 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 143 | | mean | 10.77 | | std | 9.47 | | cv | 0.879 | | sampleLengths | | 0 | 55 | | 1 | 30 | | 2 | 12 | | 3 | 19 | | 4 | 16 | | 5 | 22 | | 6 | 4 | | 7 | 21 | | 8 | 3 | | 9 | 5 | | 10 | 57 | | 11 | 29 | | 12 | 25 | | 13 | 3 | | 14 | 3 | | 15 | 36 | | 16 | 8 | | 17 | 7 | | 18 | 3 | | 19 | 6 | | 20 | 25 | | 21 | 16 | | 22 | 6 | | 23 | 12 | | 24 | 11 | | 25 | 5 | | 26 | 12 | | 27 | 22 | | 28 | 6 | | 29 | 8 | | 30 | 31 | | 31 | 4 | | 32 | 37 | | 33 | 8 | | 34 | 2 | | 35 | 3 | | 36 | 3 | | 37 | 27 | | 38 | 12 | | 39 | 8 | | 40 | 7 | | 41 | 3 | | 42 | 19 | | 43 | 8 | | 44 | 4 | | 45 | 3 | | 46 | 28 | | 47 | 10 | | 48 | 7 | | 49 | 25 |
| |
| 89.37% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 13 | | totalSentences | 287 | | matches | | 0 | "were splayed" | | 1 | "was rusted" | | 2 | "was torn" | | 3 | "been removed" | | 4 | "been slashed" | | 5 | "was etched" | | 6 | "were dilated" | | 7 | "been marked" | | 8 | "was gone" | | 9 | "was gone" | | 10 | "was gone" | | 11 | "were gone" | | 12 | "were gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 280 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 327 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 318 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 4 | | adverbRatio | 0.012578616352201259 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 327 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 327 | | mean | 4.71 | | std | 2.35 | | cv | 0.499 | | sampleLengths | | 0 | 16 | | 1 | 14 | | 2 | 10 | | 3 | 5 | | 4 | 10 | | 5 | 9 | | 6 | 7 | | 7 | 14 | | 8 | 12 | | 9 | 6 | | 10 | 6 | | 11 | 7 | | 12 | 5 | | 13 | 7 | | 14 | 4 | | 15 | 4 | | 16 | 4 | | 17 | 6 | | 18 | 8 | | 19 | 4 | | 20 | 3 | | 21 | 7 | | 22 | 5 | | 23 | 6 | | 24 | 3 | | 25 | 3 | | 26 | 2 | | 27 | 3 | | 28 | 8 | | 29 | 15 | | 30 | 4 | | 31 | 3 | | 32 | 8 | | 33 | 7 | | 34 | 9 | | 35 | 7 | | 36 | 9 | | 37 | 13 | | 38 | 8 | | 39 | 2 | | 40 | 3 | | 41 | 12 | | 42 | 3 | | 43 | 3 | | 44 | 5 | | 45 | 4 | | 46 | 3 | | 47 | 2 | | 48 | 4 | | 49 | 4 |
| |
| 38.69% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 37 | | diversityRatio | 0.2324159021406728 | | totalSentences | 327 | | uniqueOpeners | 76 | |
| 85.11% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 235 | | matches | | 0 | "Just the unnatural stillness of" | | 1 | "Slowly at first, then faster." | | 2 | "Then they faded." | | 3 | "Just smooth skin where the" | | 4 | "Only the clothes remained." | | 5 | "Only the compass remained." |
| | ratio | 0.026 | |
| 66.81% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 90 | | totalSentences | 235 | | matches | | 0 | "She tapped the leather watch" | | 1 | "His boots crunched on broken" | | 2 | "He held a notepad like" | | 3 | "She kept her eyes on" | | 4 | "He crouched beside her." | | 5 | "She reached out." | | 6 | "Her gloved fingers hovered over" | | 7 | "She remembered DS Morris." | | 8 | "He stood up and brushed" | | 9 | "Her joints popped." | | 10 | "She scanned the tunnel walls." | | 11 | "She moved closer to the" | | 12 | "She ran her hand along" | | 13 | "She knelt again." | | 14 | "She scraped a sample from" | | 15 | "It glowed faintly in the" | | 16 | "She walked to the victim's" | | 17 | "She picked it up." | | 18 | "It pointed toward the tunnel" | | 19 | "He stepped closer." |
| | ratio | 0.383 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 217 | | totalSentences | 235 | | matches | | 0 | "Quinn pressed her knee against" | | 1 | "The light caught the pale" | | 2 | "She tapped the leather watch" | | 3 | "a voice said from the" | | 4 | "DS Miller stepped into the" | | 5 | "His boots crunched on broken" | | 6 | "He held a notepad like" | | 7 | "She kept her eyes on" | | 8 | "He crouched beside her." | | 9 | "The torchlight reflected in his" | | 10 | "Miller leaned in." | | 11 | "The victim's fingers were splayed," | | 12 | "The skin was grey, waxy." | | 13 | "A fine dust coated the" | | 14 | "She reached out." | | 15 | "Her gloved fingers hovered over" | | 16 | "A faint hum vibrated through" | | 17 | "She remembered DS Morris." | | 18 | "A similar hum in a" | | 19 | "The partner she lost under" |
| | ratio | 0.923 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 235 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 10 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 34 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 31 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 73 | | tagDensity | 0.425 | | leniency | 0.849 | | rawRatio | 0 | | effectiveRatio | 0 | |