| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 2 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said aloud [aloud]" |
| | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0.5 | | effectiveRatio | 0.5 | |
| 80.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1036 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "perfectly" | | 1 | "slowly" | | 2 | "carefully" | | 3 | "very" |
| |
| 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) | |
| 51.74% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1036 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "velvet" | | 1 | "warmth" | | 2 | "throbbed" | | 3 | "stomach" | | 4 | "footsteps" | | 5 | "weight" | | 6 | "whisper" | | 7 | "pulsed" | | 8 | "pulse" |
| |
| 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 | 81 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 81 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 6 | | totalWords | 1036 | | ratio | 0.006 | | matches | | 0 | "come and eat, it's getting cold" |
| |
| 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 | 14 | | wordCount | 1029 | | uniqueNames | 11 | | maxNameDensity | 0.39 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Pen | 1 | | Ponds | 1 | | Kingston | 1 | | Road | 1 | | Tube | 1 | | Yu-Fei | 1 | | November | 1 | | Eva | 1 | | Welsh | 1 | | Cardiff | 1 | | Rory | 4 |
| | persons | | | places | | 0 | "Kingston" | | 1 | "Road" | | 2 | "Welsh" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 53 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.965 | | wordCount | 1036 | | matches | | 0 | "not carved but grown around, bark knotted over the stone as though the tree" |
| |
| 85.37% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 82 | | matches | | 0 | "was that she" | | 1 | "learned that much" |
| |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 34.53 | | std | 28.81 | | cv | 0.834 | | sampleLengths | | 0 | 82 | | 1 | 10 | | 2 | 79 | | 3 | 7 | | 4 | 86 | | 5 | 25 | | 6 | 19 | | 7 | 3 | | 8 | 98 | | 9 | 37 | | 10 | 17 | | 11 | 30 | | 12 | 24 | | 13 | 69 | | 14 | 7 | | 15 | 9 | | 16 | 93 | | 17 | 17 | | 18 | 36 | | 19 | 38 | | 20 | 3 | | 21 | 11 | | 22 | 48 | | 23 | 3 | | 24 | 45 | | 25 | 32 | | 26 | 34 | | 27 | 55 | | 28 | 11 | | 29 | 8 |
| |
| 79.27% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 81 | | matches | | 0 | "was wrapped" | | 1 | "was allowed" | | 2 | "been told" | | 3 | "was gone" | | 4 | "was gone" | | 5 | "was frightened" | | 6 | "been when" |
| |
| 0.40% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 167 | | matches | | 0 | "was listening" | | 1 | "was like walking" | | 2 | "were not coming" | | 3 | "were going" | | 4 | "was watching" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 82 | | ratio | 0 | | matches | (empty) | |
| 85.80% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1033 | | adjectiveStacks | 1 | | stackExamples | | | adverbCount | 51 | | adverbRatio | 0.049370764762826716 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.010648596321393998 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 12.63 | | std | 11.61 | | cv | 0.919 | | sampleLengths | | 0 | 22 | | 1 | 43 | | 2 | 7 | | 3 | 5 | | 4 | 5 | | 5 | 10 | | 6 | 22 | | 7 | 28 | | 8 | 12 | | 9 | 17 | | 10 | 7 | | 11 | 42 | | 12 | 26 | | 13 | 3 | | 14 | 15 | | 15 | 7 | | 16 | 3 | | 17 | 2 | | 18 | 13 | | 19 | 6 | | 20 | 8 | | 21 | 5 | | 22 | 3 | | 23 | 5 | | 24 | 11 | | 25 | 33 | | 26 | 15 | | 27 | 24 | | 28 | 3 | | 29 | 7 | | 30 | 5 | | 31 | 32 | | 32 | 6 | | 33 | 11 | | 34 | 10 | | 35 | 8 | | 36 | 4 | | 37 | 1 | | 38 | 7 | | 39 | 24 | | 40 | 4 | | 41 | 44 | | 42 | 9 | | 43 | 12 | | 44 | 7 | | 45 | 9 | | 46 | 6 | | 47 | 39 | | 48 | 15 | | 49 | 14 |
| |
| 69.11% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.45121951219512196 | | totalSentences | 82 | | uniqueOpeners | 37 | |
| 91.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 73 | | matches | | 0 | "Even the wind had stopped." | | 1 | "Then, from somewhere behind the" |
| | ratio | 0.027 | |
| 44.66% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 73 | | matches | | 0 | "She stood at the boundary" | | 1 | "She'd noticed the warmth on" | | 2 | "She closed her fist around" | | 3 | "It was warm." | | 4 | "she said aloud, to nobody" | | 5 | "Her voice came out smaller" | | 6 | "She stepped through." | | 7 | "She could see clearly even" | | 8 | "It was November." | | 9 | "She had passed frost on" | | 10 | "She had expected a grove," | | 11 | "She tested it, lifting her" | | 12 | "She tried again, harder." | | 13 | "It was like walking on" | | 14 | "She told herself that was" | | 15 | "She made herself go slowly" | | 16 | "She crouched and reached for" | | 17 | "She did not turn her" | | 18 | "She had learned that much" | | 19 | "It did not walk so" |
| | ratio | 0.438 | |
| 55.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 59 | | totalSentences | 73 | | matches | | 0 | "The directions had been simple" | | 1 | "Rory had followed them with" | | 2 | "She stood at the boundary" | | 3 | "Each was wrapped in oak," | | 4 | "The gap between two of" | | 5 | "The pendant lay warm against" | | 6 | "She'd noticed the warmth on" | | 7 | "Heartstone, she thought." | | 8 | "She closed her fist around" | | 9 | "It was warm." | | 10 | "she said aloud, to nobody" | | 11 | "Her voice came out smaller" | | 12 | "She stepped through." | | 13 | "The change was not dramatic." | | 14 | "The bracken simply gave way" | | 15 | "She could see clearly even" | | 16 | "Wildflowers covered the clearing in" | | 17 | "It was November." | | 18 | "She had passed frost on" | | 19 | "The clearing was perfectly round." |
| | ratio | 0.808 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 73 | | matches | (empty) | | ratio | 0 | |
| 79.83% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 34 | | technicalSentenceCount | 3 | | matches | | 0 | "Each was wrapped in oak, not carved but grown around, bark knotted over the stone as though the tree had swallowed it and thought better of the digestion." | | 1 | "The pendant beat against her skin, once, twice, and then held still, every pulse fading at once, as though whatever it had been signalling had finally arrived a…" | | 2 | "Its surface, which had been smooth and pale, was now marked with a fresh set of small prints, all pointing towards her, as if something had walked up to her whi…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 2 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 3 | | tagDensity | 0.667 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |