| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 84.73% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 655 | | 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) | |
| 46.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 655 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "charged" | | 1 | "echoing" | | 2 | "lurching" | | 3 | "gloom" | | 4 | "glinting" | | 5 | "streaming" | | 6 | "unravel" |
| |
| 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 | 51 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 51 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 53 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 23 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 654 | | ratio | 0 | | matches | (empty) | |
| 62.50% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 1 | | matches | | 0 | "Carting her prisoner to the waiting squad car, Quinn vowed to unravel this mystery, whatever it took." |
| |
| 30.76% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 629 | | uniqueNames | 9 | | maxNameDensity | 2.38 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 15 | | Reaching | 1 | | Veil | 1 | | Market | 1 | | Dopplered | 1 | | Primrose | 1 | | Hill | 1 | | London | 1 |
| | persons | | | places | | 0 | "Primrose" | | 1 | "Hill" | | 2 | "London" |
| | globalScore | 0.308 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 49 | | 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 | 654 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 53 | | matches | (empty) | |
| 63.35% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 21 | | mean | 31.14 | | std | 11.58 | | cv | 0.372 | | sampleLengths | | 0 | 38 | | 1 | 10 | | 2 | 38 | | 3 | 22 | | 4 | 50 | | 5 | 29 | | 6 | 28 | | 7 | 33 | | 8 | 32 | | 9 | 26 | | 10 | 11 | | 11 | 31 | | 12 | 24 | | 13 | 27 | | 14 | 41 | | 15 | 32 | | 16 | 43 | | 17 | 15 | | 18 | 23 | | 19 | 50 | | 20 | 51 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 51 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 114 | | matches | | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 4 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 53 | | ratio | 0.075 | | matches | | 0 | "A bone token lay near a storm drain - an entry token for the Veil Market." | | 1 | "Ten minutes later, a lurching sensation seized her gut - the unmistakable presense of magic." | | 2 | "A flash of movement caught her eye - the suspect, disappearing into a curtained backroom." | | 3 | "The suspect skidded around a corner - and collided with a massive ogre blocking the way, its milky eyes glinting in the torchlight." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 630 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 8 | | adverbRatio | 0.012698412698412698 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.004761904761904762 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 53 | | echoCount | 0 | | echoWords | (empty) | |
| 67.34% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 53 | | mean | 12.34 | | std | 3.93 | | cv | 0.318 | | sampleLengths | | 0 | 14 | | 1 | 15 | | 2 | 9 | | 3 | 10 | | 4 | 15 | | 5 | 10 | | 6 | 13 | | 7 | 4 | | 8 | 8 | | 9 | 10 | | 10 | 14 | | 11 | 14 | | 12 | 16 | | 13 | 6 | | 14 | 14 | | 15 | 15 | | 16 | 7 | | 17 | 12 | | 18 | 9 | | 19 | 15 | | 20 | 9 | | 21 | 9 | | 22 | 15 | | 23 | 17 | | 24 | 13 | | 25 | 13 | | 26 | 11 | | 27 | 13 | | 28 | 18 | | 29 | 13 | | 30 | 11 | | 31 | 16 | | 32 | 11 | | 33 | 7 | | 34 | 23 | | 35 | 11 | | 36 | 15 | | 37 | 8 | | 38 | 9 | | 39 | 10 | | 40 | 17 | | 41 | 16 | | 42 | 6 | | 43 | 9 | | 44 | 23 | | 45 | 15 | | 46 | 16 | | 47 | 8 | | 48 | 11 | | 49 | 11 |
| |
| 86.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.5283018867924528 | | totalSentences | 53 | | uniqueOpeners | 28 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 50 | | matches | | 0 | "Her cry dissolved into the" | | 1 | "She descended into the stuffy" | | 2 | "She didn't belong here, amongst" | | 3 | "She slipped behind the moth-eaten" | | 4 | "She clambered out the window" | | 5 | "Her flashlight picked out a" | | 6 | "It let out a basso" | | 7 | "She threw herself forward, sliding" | | 8 | "She snapped a pair of" | | 9 | "She emerged into the humid" | | 10 | "She knew now that beneath" |
| | ratio | 0.22 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 36 | | totalSentences | 50 | | matches | | 0 | "Rain slashed against the pavement," | | 1 | "Detective Harlow Quinn charged down" | | 2 | "The suspect, a hooded figure," | | 3 | "Her cry dissolved into the" | | 4 | "Quinn plunged in after them," | | 5 | "The narrow path terminated at" | | 6 | "The suspect had vanished." | | 7 | "Quinn halted, her breath coming" | | 8 | "She descended into the stuffy" | | 9 | "A bone token lay near" | | 10 | "The tunnel opened into a" | | 11 | "Stalls hawking enchanted trinkets and" | | 12 | "Steam from food carts unfurled" | | 13 | "Quinn moved cautiously through the" | | 14 | "She didn't belong here, amongst" | | 15 | "A flash of movement caught" | | 16 | "Quinn shouldered her way through" | | 17 | "She slipped behind the moth-eaten" | | 18 | "The suspect leapt onto a" | | 19 | "Quinn barked, her gun clearing" |
| | ratio | 0.72 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 50 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn barked (bark)" | | 1 | "Quinn panted (pant)" |
| | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 1 | | effectiveRatio | 0.8 | |