| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 102 | | tagDensity | 0.059 | | leniency | 0.118 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1927 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 79.24% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1927 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "trembled" | | 1 | "restrained" | | 2 | "chill" | | 3 | "pulsed" | | 4 | "standard" | | 5 | "velvet" | | 6 | "mechanical" | | 7 | "quivered" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "eyes widened" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 189 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 189 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 285 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1927 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 48.53% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 68 | | wordCount | 1429 | | uniqueNames | 10 | | maxNameDensity | 2.03 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 29 | | Ellis | 21 | | Taser | 1 | | Eva | 8 | | Veil | 1 | | Compass | 1 | | Morris | 2 | | One | 3 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Ellis" | | 3 | "Eva" | | 4 | "Compass" | | 5 | "Morris" |
| | places | (empty) | | globalScore | 0.485 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 115 | | glossingSentenceCount | 2 | | matches | | 0 | "appeared acceptable forms of payment" | | 1 | "sounded like metal remembering pain" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1927 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 285 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 202 | | mean | 9.54 | | std | 10.82 | | cv | 1.134 | | sampleLengths | | 0 | 12 | | 1 | 3 | | 2 | 20 | | 3 | 16 | | 4 | 2 | | 5 | 5 | | 6 | 31 | | 7 | 8 | | 8 | 5 | | 9 | 3 | | 10 | 1 | | 11 | 6 | | 12 | 55 | | 13 | 21 | | 14 | 4 | | 15 | 26 | | 16 | 2 | | 17 | 9 | | 18 | 3 | | 19 | 4 | | 20 | 2 | | 21 | 7 | | 22 | 19 | | 23 | 2 | | 24 | 5 | | 25 | 6 | | 26 | 2 | | 27 | 2 | | 28 | 5 | | 29 | 47 | | 30 | 53 | | 31 | 3 | | 32 | 2 | | 33 | 2 | | 34 | 9 | | 35 | 28 | | 36 | 9 | | 37 | 3 | | 38 | 2 | | 39 | 7 | | 40 | 36 | | 41 | 1 | | 42 | 2 | | 43 | 6 | | 44 | 2 | | 45 | 13 | | 46 | 7 | | 47 | 2 | | 48 | 9 | | 49 | 3 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 189 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 250 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 285 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1432 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small red light pulsed" |
| | adverbCount | 28 | | adverbRatio | 0.019553072625698324 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002094972067039106 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 285 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 285 | | mean | 6.76 | | std | 4.86 | | cv | 0.718 | | sampleLengths | | 0 | 12 | | 1 | 3 | | 2 | 14 | | 3 | 6 | | 4 | 5 | | 5 | 11 | | 6 | 2 | | 7 | 5 | | 8 | 14 | | 9 | 5 | | 10 | 12 | | 11 | 8 | | 12 | 5 | | 13 | 3 | | 14 | 1 | | 15 | 6 | | 16 | 5 | | 17 | 13 | | 18 | 6 | | 19 | 17 | | 20 | 14 | | 21 | 4 | | 22 | 17 | | 23 | 4 | | 24 | 26 | | 25 | 2 | | 26 | 9 | | 27 | 3 | | 28 | 4 | | 29 | 2 | | 30 | 7 | | 31 | 7 | | 32 | 12 | | 33 | 2 | | 34 | 5 | | 35 | 6 | | 36 | 2 | | 37 | 2 | | 38 | 5 | | 39 | 11 | | 40 | 12 | | 41 | 5 | | 42 | 11 | | 43 | 8 | | 44 | 4 | | 45 | 19 | | 46 | 5 | | 47 | 4 | | 48 | 21 | | 49 | 3 |
| |
| 57.43% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.36140350877192984 | | totalSentences | 285 | | uniqueOpeners | 103 | |
| 38.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 172 | | matches | | 0 | "Then his eyes rolled back," | | 1 | "Then his voice came through" |
| | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 36 | | totalSentences | 172 | | matches | | 0 | "His complexion had acquired the" | | 1 | "His left eyelid trembled twice." | | 2 | "She crouched beside the corpse." | | 3 | "He wore a neat charcoal" | | 4 | "His white beard had yellowed" | | 5 | "He aimed his torch at" | | 6 | "It had bitten deep into" | | 7 | "He raised his torch." | | 8 | "His answer came too fast." | | 9 | "His radio hung from his" | | 10 | "He kept one hand close" | | 11 | "It did not move to" | | 12 | "It moved to the radio." | | 13 | "She twisted, drove him against" | | 14 | "Its little door swung open." | | 15 | "He stared beyond her shoulder." | | 16 | "Its head lolled against its" | | 17 | "His finger shifted towards a" | | 18 | "He grabbed her shoulder." | | 19 | "She drove an elbow into" |
| | ratio | 0.209 | |
| 29.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 148 | | totalSentences | 172 | | matches | | 0 | "The corpse opened its eyes" | | 1 | "Quinn stopped with one boot" | | 2 | "PC Ellis lowered his camera." | | 3 | "His complexion had acquired the" | | 4 | "The dead man’s cloudy gaze" | | 5 | "His left eyelid trembled twice." | | 6 | "Quinn planted her foot beyond" | | 7 | "Quinn looked along the platform." | | 8 | "Iron columns divided the platform" | | 9 | "Stalls crowded the old concourse" | | 10 | "Copper stung her nostrils." | | 11 | "Ellis checked his phone." | | 12 | "Quinn glanced at her worn" | | 13 | "The second hand ticked on," | | 14 | "She crouched beside the corpse." | | 15 | "A man of about sixty" | | 16 | "He wore a neat charcoal" | | 17 | "Someone had removed his shoes." | | 18 | "His white beard had yellowed" | | 19 | "The wound looked theatrical." |
| | ratio | 0.86 | |
| 29.07% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 172 | | matches | | 0 | "Whoever had abandoned the place" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 53 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Eva shouted (shout)" | | 1 | "he whispered (whisper)" |
| | dialogueSentences | 102 | | tagDensity | 0.039 | | leniency | 0.078 | | rawRatio | 0.5 | | effectiveRatio | 0.039 | |