| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1586 | | 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) | |
| 90.54% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1586 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "warmth" | | 1 | "vibrated" | | 2 | "footsteps" |
| |
| 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 | 162 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 162 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 171 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 28 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1586 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.13% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 1547 | | uniqueNames | 5 | | maxNameDensity | 1.36 | | worstName | "Rory" | | maxWindowNameDensity | 2 | | worstWindowName | "Rory" | | discoveredNames | | January | 1 | | Richmond | 1 | | Park | 1 | | Rory | 21 | | Yu-Fei | 3 |
| | persons | | | places | | 0 | "January" | | 1 | "Richmond" | | 2 | "Park" |
| | globalScore | 0.821 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 123 | | glossingSentenceCount | 1 | | matches | | 0 | "appeared against the toe of her boot" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1586 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 171 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 79 | | mean | 20.08 | | std | 14.63 | | cv | 0.729 | | sampleLengths | | 0 | 44 | | 1 | 34 | | 2 | 3 | | 3 | 5 | | 4 | 35 | | 5 | 31 | | 6 | 51 | | 7 | 9 | | 8 | 23 | | 9 | 46 | | 10 | 22 | | 11 | 32 | | 12 | 6 | | 13 | 46 | | 14 | 16 | | 15 | 4 | | 16 | 11 | | 17 | 50 | | 18 | 7 | | 19 | 13 | | 20 | 3 | | 21 | 33 | | 22 | 12 | | 23 | 39 | | 24 | 7 | | 25 | 26 | | 26 | 39 | | 27 | 3 | | 28 | 56 | | 29 | 8 | | 30 | 34 | | 31 | 10 | | 32 | 2 | | 33 | 3 | | 34 | 40 | | 35 | 13 | | 36 | 31 | | 37 | 11 | | 38 | 26 | | 39 | 35 | | 40 | 11 | | 41 | 38 | | 42 | 6 | | 43 | 25 | | 44 | 9 | | 45 | 4 | | 46 | 17 | | 47 | 25 | | 48 | 5 | | 49 | 6 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 162 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 262 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 1 | | flaggedSentences | 1 | | totalSentences | 171 | | ratio | 0.006 | | matches | | 0 | "Her phone had not landed on top; she would have seen it there." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1550 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.027741935483870966 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.001935483870967742 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 171 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 171 | | mean | 9.27 | | std | 5.61 | | cv | 0.605 | | sampleLengths | | 0 | 17 | | 1 | 27 | | 2 | 6 | | 3 | 16 | | 4 | 12 | | 5 | 3 | | 6 | 5 | | 7 | 3 | | 8 | 7 | | 9 | 25 | | 10 | 5 | | 11 | 13 | | 12 | 13 | | 13 | 8 | | 14 | 25 | | 15 | 18 | | 16 | 9 | | 17 | 19 | | 18 | 4 | | 19 | 6 | | 20 | 12 | | 21 | 20 | | 22 | 8 | | 23 | 7 | | 24 | 15 | | 25 | 8 | | 26 | 16 | | 27 | 8 | | 28 | 6 | | 29 | 2 | | 30 | 10 | | 31 | 21 | | 32 | 13 | | 33 | 7 | | 34 | 4 | | 35 | 5 | | 36 | 4 | | 37 | 6 | | 38 | 5 | | 39 | 9 | | 40 | 13 | | 41 | 15 | | 42 | 13 | | 43 | 7 | | 44 | 6 | | 45 | 7 | | 46 | 3 | | 47 | 5 | | 48 | 7 | | 49 | 21 |
| |
| 41.23% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 15 | | diversityRatio | 0.21052631578947367 | | totalSentences | 171 | | uniqueOpeners | 36 | |
| 42.19% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 158 | | matches | | 0 | "Somewhere beyond the trees, a" | | 1 | "Then a voice spoke, so" |
| | ratio | 0.013 | |
| 68.10% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 60 | | totalSentences | 158 | | matches | | 0 | "She checked the path behind" | | 1 | "She stepped between the stones." | | 2 | "Her torch picked out the" | | 3 | "She had dropped her phone" | | 4 | "She remembered lifting it to" | | 5 | "she had told Rory, pressing" | | 6 | "She kept its beam low" | | 7 | "She had walked from the" | | 8 | "She found her footprints near" | | 9 | "They led to the tree" | | 10 | "They followed her tracks towards" | | 11 | "She pressed a finger into" | | 12 | "Her fingertip came away wet." | | 13 | "She rose and swept the" | | 14 | "Its trunk lay across the" | | 15 | "She remembered the pale wood" | | 16 | "Her phone had not landed" | | 17 | "She knelt and shone the" | | 18 | "Her fingers closed around a" | | 19 | "She pulled it out and" |
| | ratio | 0.38 | |
| 1.14% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 145 | | totalSentences | 158 | | matches | | 0 | "Rory reached the standing stones" | | 1 | "The torch in her bare" | | 2 | "She checked the path behind" | | 3 | "The gate into Richmond Park" | | 4 | "A bus passed on the" | | 5 | "She stepped between the stones." | | 6 | "The bus vanished." | | 7 | "Her torch picked out the" | | 8 | "Rory turned in a circle." | | 9 | "Oak trunks crowded the edge" | | 10 | "The sky showed through in" | | 11 | "She had dropped her phone" | | 12 | "She remembered lifting it to" | | 13 | "Yu-Fei had offered to lend" | | 14 | "she had told Rory, pressing" | | 15 | "Rory had borrowed the torch" | | 16 | "She kept its beam low" | | 17 | "She had walked from the" | | 18 | "The phone had to be" | | 19 | "A damp smell rose from" |
| | ratio | 0.918 | |
| 31.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 158 | | matches | | 0 | "By the time she reached" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 50.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 10 | | tagDensity | 0.1 | | leniency | 0.2 | | rawRatio | 1 | | effectiveRatio | 0.2 | |