| 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 | 931 | | 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) | |
| 8.70% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 931 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "velvet" | | 1 | "pulsed" | | 2 | "warmth" | | 3 | "silence" | | 4 | "pulse" | | 5 | "throbbed" | | 6 | "dance" | | 7 | "echoed" | | 8 | "weight" | | 9 | "shimmered" |
| |
| 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 | 254 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 254 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 267 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 10 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 931 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 901 | | uniqueNames | 7 | | maxNameDensity | 0.44 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 4 | | London | 1 | | Black | 3 | | Click | 3 | | Silence | 4 | | Hand | 3 | | Faces | 3 |
| | persons | | 0 | "Rory" | | 1 | "Silence" | | 2 | "Hand" | | 3 | "Faces" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 22 | | 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 | 931 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 267 | | matches | (empty) | |
| 39.06% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 29 | | mean | 32.1 | | std | 9.2 | | cv | 0.287 | | sampleLengths | | 0 | 36 | | 1 | 11 | | 2 | 30 | | 3 | 34 | | 4 | 38 | | 5 | 23 | | 6 | 28 | | 7 | 29 | | 8 | 18 | | 9 | 38 | | 10 | 24 | | 11 | 22 | | 12 | 30 | | 13 | 20 | | 14 | 38 | | 15 | 47 | | 16 | 39 | | 17 | 24 | | 18 | 35 | | 19 | 35 | | 20 | 37 | | 21 | 48 | | 22 | 31 | | 23 | 32 | | 24 | 39 | | 25 | 25 | | 26 | 49 | | 27 | 25 | | 28 | 46 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 254 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 221 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 267 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 901 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.02885682574916759 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003329633740288568 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 267 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 267 | | mean | 3.49 | | std | 1.61 | | cv | 0.461 | | sampleLengths | | 0 | 5 | | 1 | 2 | | 2 | 3 | | 3 | 6 | | 4 | 3 | | 5 | 7 | | 6 | 1 | | 7 | 1 | | 8 | 8 | | 9 | 2 | | 10 | 2 | | 11 | 4 | | 12 | 1 | | 13 | 2 | | 14 | 1 | | 15 | 7 | | 16 | 3 | | 17 | 6 | | 18 | 5 | | 19 | 8 | | 20 | 3 | | 21 | 4 | | 22 | 2 | | 23 | 3 | | 24 | 3 | | 25 | 5 | | 26 | 6 | | 27 | 1 | | 28 | 2 | | 29 | 5 | | 30 | 4 | | 31 | 6 | | 32 | 4 | | 33 | 4 | | 34 | 4 | | 35 | 5 | | 36 | 7 | | 37 | 4 | | 38 | 2 | | 39 | 6 | | 40 | 3 | | 41 | 7 | | 42 | 3 | | 43 | 2 | | 44 | 6 | | 45 | 4 | | 46 | 4 | | 47 | 8 | | 48 | 6 | | 49 | 3 |
| |
| 40.95% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 49 | | diversityRatio | 0.35580524344569286 | | totalSentences | 267 | | uniqueOpeners | 95 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 187 | | matches | | 0 | "Just across the seam." | | 1 | "Away from her." | | 2 | "Then the other found no" | | 3 | "Only the footprints." | | 4 | "Only the footprints." | | 5 | "Only the footprints." |
| | ratio | 0.032 | |
| 25.35% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 91 | | totalSentences | 187 | | matches | | 0 | "She stopped moving." | | 1 | "She liked how it felt" | | 2 | "She clamped her hand over" | | 3 | "It told her somewhere the" | | 4 | "She held the ticket." | | 5 | "Her watch ticked." | | 6 | "She remembered the way it" | | 7 | "She shook the thought." | | 8 | "She spotted the shift first." | | 9 | "She leaned forward." | | 10 | "She felt her wrist." | | 11 | "It stopped at the standing" | | 12 | "She took the step back." | | 13 | "She kept walking." | | 14 | "She whispered the name." | | 15 | "She knew it not." | | 16 | "She checked the signs." | | 17 | "She pointed the bare foot." | | 18 | "She left a footprint." | | 19 | "She saw the bone reach" |
| | ratio | 0.487 | |
| 26.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 162 | | totalSentences | 187 | | matches | | 0 | "The air bit Rory's skin." | | 1 | "She stopped moving." | | 2 | "Breath fogged in the London" | | 3 | "Moss covered everything." | | 4 | "The moss grew between the" | | 5 | "She liked how it felt" | | 6 | "The pines dropped shadows." | | 7 | "She clamped her hand over" | | 8 | "The gem pulsed." | | 9 | "Warmth trickled down her wrist." | | 10 | "It told her somewhere the" | | 11 | "She held the ticket." | | 12 | "Her watch ticked." | | 13 | "The grove time was different." | | 14 | "She remembered the way it" | | 15 | "Time stretched here like taffy." | | 16 | "Birds did not sing." | | 17 | "A dead silence pressed against" | | 18 | "She shook the thought." | | 19 | "She spotted the shift first." |
| | ratio | 0.866 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 187 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 1 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |