| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 935 | | 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) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 935 | | totalAiIsms | 22 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | |
| | highlights | | 0 | "flicker" | | 1 | "footsteps" | | 2 | "echoed" | | 3 | "whisper" | | 4 | "weight" | | 5 | "lurched" | | 6 | "charged" | | 7 | "gloom" | | 8 | "pulse" | | 9 | "flicked" | | 10 | "etched" | | 11 | "tracing" | | 12 | "flickered" | | 13 | "echoing" | | 14 | "scanning" | | 15 | "trembled" | | 16 | "raced" | | 17 | "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 | 116 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 116 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 124 | | 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 | 929 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 7 | | wordCount | 902 | | uniqueNames | 6 | | maxNameDensity | 0.22 | | worstName | "Quinn" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Quinn" | | discoveredNames | | Detective | 1 | | Harlow | 1 | | Quinn | 2 | | Morris | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Market" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 76 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 929 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 124 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 28 | | mean | 33.18 | | std | 37.56 | | cv | 1.132 | | sampleLengths | | 0 | 105 | | 1 | 1 | | 2 | 8 | | 3 | 58 | | 4 | 3 | | 5 | 2 | | 6 | 6 | | 7 | 47 | | 8 | 4 | | 9 | 2 | | 10 | 36 | | 11 | 112 | | 12 | 63 | | 13 | 3 | | 14 | 7 | | 15 | 4 | | 16 | 2 | | 17 | 19 | | 18 | 115 | | 19 | 101 | | 20 | 4 | | 21 | 6 | | 22 | 6 | | 23 | 59 | | 24 | 69 | | 25 | 27 | | 26 | 53 | | 27 | 7 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 187 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 2 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 124 | | ratio | 0.008 | | matches | | 0 | "A voice in her head—DS Morris’s—flickered." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 908 | | adjectiveStacks | 1 | | stackExamples | | 0 | "against graffiti-tagged walls." |
| | adverbCount | 11 | | adverbRatio | 0.012114537444933921 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0022026431718061676 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 124 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 124 | | mean | 7.49 | | std | 3.92 | | cv | 0.523 | | sampleLengths | | 0 | 23 | | 1 | 19 | | 2 | 13 | | 3 | 8 | | 4 | 11 | | 5 | 11 | | 6 | 7 | | 7 | 5 | | 8 | 8 | | 9 | 1 | | 10 | 5 | | 11 | 3 | | 12 | 10 | | 13 | 2 | | 14 | 8 | | 15 | 4 | | 16 | 4 | | 17 | 8 | | 18 | 12 | | 19 | 10 | | 20 | 3 | | 21 | 2 | | 22 | 6 | | 23 | 6 | | 24 | 6 | | 25 | 6 | | 26 | 5 | | 27 | 9 | | 28 | 8 | | 29 | 7 | | 30 | 4 | | 31 | 2 | | 32 | 9 | | 33 | 3 | | 34 | 3 | | 35 | 4 | | 36 | 2 | | 37 | 10 | | 38 | 5 | | 39 | 15 | | 40 | 4 | | 41 | 5 | | 42 | 8 | | 43 | 5 | | 44 | 14 | | 45 | 5 | | 46 | 2 | | 47 | 5 | | 48 | 6 | | 49 | 9 |
| |
| 51.61% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.3629032258064516 | | totalSentences | 124 | | uniqueOpeners | 45 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 111 | | matches | (empty) | | ratio | 0 | |
| 25.41% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 111 | | matches | | 0 | "She angled her worn leather" | | 1 | "She shifted weight, boots squelching" | | 2 | "She leapt, shoulder driving into" | | 3 | "He lurched away, coat flaring." | | 4 | "He bolted into the street," | | 5 | "She closed the gap." | | 6 | "She gulped cold air that" | | 7 | "She swung her arm, lamp" | | 8 | "He lunged between two idling" | | 9 | "He veered down a narrow" | | 10 | "He charged past rain-sodden bins." | | 11 | "She twisted through them, thumb" | | 12 | "He cleared a low fence" | | 13 | "She vaulted after, fingers scraping" | | 14 | "She raised her voice." | | 15 | "He swore, yanked the handle" | | 16 | "He went inside." | | 17 | "She stabbed the lock." | | 18 | "She slipped in behind him." | | 19 | "She flicked on her torch." |
| | ratio | 0.486 | |
| 14.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 99 | | totalSentences | 111 | | matches | | 0 | "Droplets trickled from her closely" | | 1 | "She angled her worn leather" | | 2 | "Footsteps echoed behind the bar’s" | | 3 | "A hidden panel in the" | | 4 | "A man slipped through, shoulders" | | 5 | "She shifted weight, boots squelching" | | 6 | "Flashlight pinched between her teeth." | | 7 | "She leapt, shoulder driving into" | | 8 | "He lurched away, coat flaring." | | 9 | "The chase began." | | 10 | "He bolted into the street," | | 11 | "Taillights smeared like red bruises" | | 12 | "She closed the gap." | | 13 | "She gulped cold air that" | | 14 | "She swung her arm, lamp" | | 15 | "He lunged between two idling" | | 16 | "He veered down a narrow" | | 17 | "The alley yawned like a" | | 18 | "Trash lay piled against graffiti-tagged" | | 19 | "An oily sheen coated the" |
| | ratio | 0.892 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 111 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 1 | | matches | | 0 | "His coat brushed frayed banners that drooped from iron hooks overhead." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |