| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1067 | | 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) | |
| 67.20% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1067 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pulse" | | 1 | "silence" | | 2 | "weight" | | 3 | "resolved" |
| |
| 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 | 71 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 71 | | filterMatches | (empty) | | 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 | 61 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1067 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 27 | | wordCount | 987 | | uniqueNames | 12 | | maxNameDensity | 0.51 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Seven" | | discoveredNames | | Rory | 5 | | London | 2 | | Marek | 4 | | Richmond | 1 | | Park | 1 | | Empress | 2 | | Yu-Fei | 1 | | February | 2 | | Silas | 3 | | Golden | 2 | | Belfast | 1 | | Seven | 3 |
| | persons | | 0 | "Rory" | | 1 | "Marek" | | 2 | "Empress" | | 3 | "Yu-Fei" | | 4 | "February" | | 5 | "Silas" | | 6 | "Seven" |
| | places | | 0 | "London" | | 1 | "Richmond" | | 2 | "Park" | | 3 | "Belfast" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 47 | | 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 | 1067 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 82 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 24.81 | | std | 24.15 | | cv | 0.973 | | sampleLengths | | 0 | 31 | | 1 | 11 | | 2 | 76 | | 3 | 39 | | 4 | 12 | | 5 | 67 | | 6 | 8 | | 7 | 7 | | 8 | 3 | | 9 | 18 | | 10 | 16 | | 11 | 8 | | 12 | 7 | | 13 | 25 | | 14 | 2 | | 15 | 2 | | 16 | 54 | | 17 | 5 | | 18 | 69 | | 19 | 7 | | 20 | 18 | | 21 | 54 | | 22 | 10 | | 23 | 43 | | 24 | 7 | | 25 | 60 | | 26 | 3 | | 27 | 59 | | 28 | 1 | | 29 | 12 | | 30 | 22 | | 31 | 2 | | 32 | 12 | | 33 | 60 | | 34 | 7 | | 35 | 75 | | 36 | 1 | | 37 | 2 | | 38 | 44 | | 39 | 12 | | 40 | 61 | | 41 | 1 | | 42 | 34 |
| |
| 90.44% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 71 | | matches | | 0 | "was marked" | | 1 | "was gone" | | 2 | "been touched" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 152 | | matches | | 0 | "was not pulling" | | 1 | "was pulling" |
| |
| 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) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 837 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.03106332138590203 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.005973715651135006 | |
| 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 | 13.01 | | std | 13.35 | | cv | 1.026 | | sampleLengths | | 0 | 15 | | 1 | 16 | | 2 | 11 | | 3 | 6 | | 4 | 45 | | 5 | 25 | | 6 | 7 | | 7 | 16 | | 8 | 7 | | 9 | 9 | | 10 | 12 | | 11 | 3 | | 12 | 4 | | 13 | 23 | | 14 | 3 | | 15 | 34 | | 16 | 4 | | 17 | 4 | | 18 | 7 | | 19 | 3 | | 20 | 18 | | 21 | 9 | | 22 | 7 | | 23 | 8 | | 24 | 7 | | 25 | 6 | | 26 | 19 | | 27 | 2 | | 28 | 2 | | 29 | 12 | | 30 | 5 | | 31 | 37 | | 32 | 5 | | 33 | 10 | | 34 | 29 | | 35 | 12 | | 36 | 9 | | 37 | 9 | | 38 | 7 | | 39 | 18 | | 40 | 15 | | 41 | 3 | | 42 | 2 | | 43 | 34 | | 44 | 10 | | 45 | 5 | | 46 | 1 | | 47 | 30 | | 48 | 1 | | 49 | 5 |
| |
| 65.45% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.45121951219512196 | | totalSentences | 82 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 62 | | matches | | 0 | "Just a vertical absence of" | | 1 | "Then a voice, Marek's voice," | | 2 | "Then again, sharper, with her" |
| | ratio | 0.048 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 62 | | matches | | 0 | "She snatched her hand back" | | 1 | "It had hung cold and" | | 2 | "He'd texted the restaurant at" | | 3 | "Her breath plumed." | | 4 | "She thumbed her phone." | | 5 | "She put the phone away." | | 6 | "She crouched, ran two fingers" | | 7 | "It sprang upright under her" | | 8 | "she said, and heard her" | | 9 | "She counted the standing stones." | | 10 | "She turned a slow circle." | | 11 | "Her phone rang." | | 12 | "She answered on instinct and" | | 13 | "It was pulling her toward" | | 14 | "It began low, a vibration" | | 15 | "It said her surname." |
| | ratio | 0.258 | |
| 80.97% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 62 | | matches | | 0 | "The standing stone beneath Rory's" | | 1 | "February bark, frozen London air," | | 2 | "She snatched her hand back" | | 3 | "The pendant had led her" | | 4 | "It had hung cold and" | | 5 | "Tonight it had gone from" | | 6 | "Marek had been on his" | | 7 | "He'd texted the restaurant at" | | 8 | "Her breath plumed." | | 9 | "The wildflowers that shouldn't have" | | 10 | "She thumbed her phone." | | 11 | "Silas picked up on the" | | 12 | "A glass set down hard" | | 13 | "Silence stretched, the kind that" | | 14 | "The line collapsed into a" | | 15 | "Rory tried him twice more." | | 16 | "The second time, the screen" | | 17 | "She put the phone away." | | 18 | "The path Marek's scooter must" | | 19 | "A channel of flattened flowers" |
| | ratio | 0.758 | |
| 80.65% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 62 | | matches | | 0 | "Now Rory stood between the" |
| | ratio | 0.016 | |
| 40.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 28 | | technicalSentenceCount | 4 | | matches | | 0 | "Golden Empress, order four-oh-seven, delivered to a postcode that didn't exist in any system Yu-Fei owned." | | 1 | "The wildflowers that shouldn't have been flowering in a London February pressed up around her boots in a dense white carpet, and where her feet disturbed them, …" | | 2 | "She answered on instinct and heard breathing, wet and thick, as though the lungs producing it were full of water, and beneath the breathing, faintly, the clatte…" | | 3 | "Something filled it shoulder to shoulder with the trunks, far too tall to fit, folding itself down into the space the way a body folds into a car, and it said h…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0 | | effectiveRatio | 0 | |