| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.154 | | leniency | 0.308 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 92.51% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1336 | | 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) | |
| 36.38% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1336 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "echoing" | | 1 | "shattered" | | 2 | "pristine" | | 3 | "crystalline" | | 4 | "charm" | | 5 | "glint" | | 6 | "tracing" | | 7 | "crystal" | | 8 | "warmth" | | 9 | "standard" | | 10 | "traced" | | 11 | "wavered" | | 12 | "aligned" | | 13 | "calculated" |
| |
| 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 | 78 | | matches | (empty) | |
| 87.91% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 78 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 89 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 67 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1336 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 4 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 1066 | | uniqueNames | 4 | | maxNameDensity | 0.66 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 7 | | Camden | 1 | | Tube | 1 |
| | persons | | | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 79.58% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 71 | | glossingSentenceCount | 2 | | matches | | 0 | "as if staring into something invisible" | | 1 | "appeared behind her at the alcove door" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1336 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 89 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 60.73 | | std | 32.46 | | cv | 0.535 | | sampleLengths | | 0 | 109 | | 1 | 49 | | 2 | 40 | | 3 | 57 | | 4 | 27 | | 5 | 104 | | 6 | 88 | | 7 | 23 | | 8 | 73 | | 9 | 22 | | 10 | 25 | | 11 | 55 | | 12 | 100 | | 13 | 15 | | 14 | 71 | | 15 | 91 | | 16 | 25 | | 17 | 72 | | 18 | 110 | | 19 | 15 | | 20 | 100 | | 21 | 65 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 172 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 89 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1068 | | adjectiveStacks | 1 | | stackExamples | | 0 | "usual damp concrete scent." |
| | adverbCount | 35 | | adverbRatio | 0.03277153558052434 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.009363295880149813 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 89 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 89 | | mean | 15.01 | | std | 8.57 | | cv | 0.571 | | sampleLengths | | 0 | 19 | | 1 | 21 | | 2 | 17 | | 3 | 36 | | 4 | 16 | | 5 | 6 | | 6 | 14 | | 7 | 13 | | 8 | 16 | | 9 | 14 | | 10 | 26 | | 11 | 9 | | 12 | 15 | | 13 | 7 | | 14 | 26 | | 15 | 6 | | 16 | 21 | | 17 | 14 | | 18 | 14 | | 19 | 9 | | 20 | 20 | | 21 | 3 | | 22 | 25 | | 23 | 19 | | 24 | 8 | | 25 | 18 | | 26 | 11 | | 27 | 23 | | 28 | 10 | | 29 | 18 | | 30 | 6 | | 31 | 17 | | 32 | 4 | | 33 | 15 | | 34 | 13 | | 35 | 14 | | 36 | 19 | | 37 | 8 | | 38 | 5 | | 39 | 17 | | 40 | 10 | | 41 | 15 | | 42 | 32 | | 43 | 23 | | 44 | 12 | | 45 | 7 | | 46 | 14 | | 47 | 15 | | 48 | 19 | | 49 | 4 |
| |
| 64.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 1 | | diversityRatio | 0.39325842696629215 | | totalSentences | 89 | | uniqueOpeners | 35 | |
| 42.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 78 | | matches | | 0 | "All pointed to calculated presence" |
| | ratio | 0.013 | |
| 25.13% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 38 | | totalSentences | 78 | | matches | | 0 | "Her leather watch slid against" | | 1 | "She noted the fresh chalk" | | 2 | "She lifted one edge of" | | 3 | "She stood and turned her" | | 4 | "She kept her eyes on" | | 5 | "He shrugged and descended two" | | 6 | "She prodded one piece aside" | | 7 | "She glanced upward." | | 8 | "She returned to the body" | | 9 | "She flashed the torch once" | | 10 | "Its surface bore carved lines" | | 11 | "She nudged it free without" | | 12 | "Her colleague reached the platform" | | 13 | "She checked the watch again" | | 14 | "She reached up, fingers probing," | | 15 | "She held it toward him." | | 16 | "He took the scrap between" | | 17 | "She gestured with the torch" | | 18 | "She moved to the service" | | 19 | "It gave inward with a" |
| | ratio | 0.487 | |
| 30.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 78 | | matches | | 0 | "Detective Harlow Quinn stepped over" | | 1 | "Her leather watch slid against" | | 2 | "The concrete walls bore old" | | 3 | "She noted the fresh chalk" | | 4 | "Blood pooled neater than gravity" | | 5 | "Quinn lowered the torch and" | | 6 | "The victim showed no defensive" | | 7 | "She lifted one edge of" | | 8 | "She stood and turned her" | | 9 | "The light revealed his notebook" | | 10 | "She kept her eyes on" | | 11 | "He shrugged and descended two" | | 12 | "Quinn walked the length of" | | 13 | "The shards formed a scattered" | | 14 | "She prodded one piece aside" | | 15 | "She glanced upward." | | 16 | "An old ventilation grate hung" | | 17 | "Grit sifted down in a" | | 18 | "She returned to the body" | | 19 | "The skin around the neck" |
| | ratio | 0.859 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 78 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 2 | | matches | | 0 | "She noted the fresh chalk line surrounding the body first, then the positioning: the victim sprawled on the track bed with limbs rigid, head tilted unnaturally …" | | 1 | "An old ventilation grate hung loose directly above the blood pool, its blades bent inward as if something shoved against them from the shaft above." |
| |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 1 | | matches | | 0 | "said her colleague from the upper concourse, his voice echoing down the stairs" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 13 | | tagDensity | 0.077 | | leniency | 0.154 | | rawRatio | 0 | | effectiveRatio | 0 | |