| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 2 | | adverbTags | | 0 | "his voice went hard [hard]" | | 1 | "he said finally [finally]" |
| | dialogueSentences | 47 | | tagDensity | 0.34 | | leniency | 0.681 | | rawRatio | 0.125 | | effectiveRatio | 0.085 | |
| 87.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1187 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 70.51% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1187 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "pulse" | | 1 | "warmth" | | 2 | "silence" | | 3 | "familiar" | | 4 | "weight" | | 5 | "traced" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "knuckles turned white" | | count | 1 |
| | 1 | | label | "hung in the air" | | count | 1 |
|
| | highlights | | 0 | "knuckles went white" | | 1 | "hung in the air" |
| |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 63 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 63 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 59 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1187 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 14 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 12 | | wordCount | 715 | | uniqueNames | 5 | | maxNameDensity | 0.7 | | worstName | "Felix" | | maxWindowNameDensity | 2 | | worstWindowName | "Felix" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Cardiff | 2 | | Felix | 5 | | Rory | 3 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 43 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 31.51% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.685 | | wordCount | 1187 | | matches | | 0 | "not much, but it's mine" | | 1 | "Not the old smile, but a scarred, wiser thing" |
| |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 53 | | mean | 22.4 | | std | 17.56 | | cv | 0.784 | | sampleLengths | | 0 | 44 | | 1 | 52 | | 2 | 53 | | 3 | 4 | | 4 | 54 | | 5 | 5 | | 6 | 61 | | 7 | 4 | | 8 | 1 | | 9 | 24 | | 10 | 19 | | 11 | 24 | | 12 | 4 | | 13 | 16 | | 14 | 6 | | 15 | 10 | | 16 | 15 | | 17 | 18 | | 18 | 37 | | 19 | 8 | | 20 | 9 | | 21 | 4 | | 22 | 18 | | 23 | 40 | | 24 | 12 | | 25 | 8 | | 26 | 25 | | 27 | 7 | | 28 | 27 | | 29 | 10 | | 30 | 51 | | 31 | 27 | | 32 | 53 | | 33 | 6 | | 34 | 31 | | 35 | 21 | | 36 | 39 | | 37 | 41 | | 38 | 7 | | 39 | 27 | | 40 | 1 | | 41 | 39 | | 42 | 31 | | 43 | 11 | | 44 | 7 | | 45 | 63 | | 46 | 34 | | 47 | 4 | | 48 | 13 | | 49 | 24 |
| |
| 99.69% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 63 | | matches | | |
| 91.60% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 123 | | matches | | 0 | "was trying" | | 1 | "was feeling" |
| |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 92 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 720 | | adjectiveStacks | 1 | | stackExamples | | 0 | "known, same low murmur" |
| | adverbCount | 26 | | adverbRatio | 0.03611111111111111 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.011111111111111112 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 12.9 | | std | 10.35 | | cv | 0.802 | | sampleLengths | | 0 | 17 | | 1 | 3 | | 2 | 24 | | 3 | 17 | | 4 | 7 | | 5 | 28 | | 6 | 22 | | 7 | 5 | | 8 | 26 | | 9 | 4 | | 10 | 15 | | 11 | 25 | | 12 | 4 | | 13 | 10 | | 14 | 5 | | 15 | 20 | | 16 | 9 | | 17 | 32 | | 18 | 4 | | 19 | 1 | | 20 | 6 | | 21 | 18 | | 22 | 17 | | 23 | 2 | | 24 | 5 | | 25 | 4 | | 26 | 4 | | 27 | 11 | | 28 | 4 | | 29 | 7 | | 30 | 9 | | 31 | 6 | | 32 | 10 | | 33 | 13 | | 34 | 2 | | 35 | 6 | | 36 | 10 | | 37 | 2 | | 38 | 15 | | 39 | 22 | | 40 | 8 | | 41 | 9 | | 42 | 4 | | 43 | 7 | | 44 | 11 | | 45 | 40 | | 46 | 12 | | 47 | 8 | | 48 | 25 | | 49 | 3 |
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| 51.09% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.358695652173913 | | totalSentences | 92 | | uniqueOpeners | 33 | |
| 56.50% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 59 | | matches | | | ratio | 0.017 | |
| 16.61% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 59 | | matches | | 0 | "She ordered a whiskey from" | | 1 | "She just wanted to sit." | | 2 | "He was half-hidden in the" | | 3 | "She almost looked away." | | 4 | "His jaw had sharpened, his" | | 5 | "She stayed frozen halfway." | | 6 | "His voice cracked on her" | | 7 | "She heard herself say the" | | 8 | "He set his glass down." | | 9 | "He laughed, a hollow sound" | | 10 | "He gestured at the stool" | | 11 | "She made a decision for" | | 12 | "He turned the glass in" | | 13 | "she said, but the words" | | 14 | "It wasn't a question" | | 15 | "He nodded slowly." | | 16 | "She watched his face change," | | 17 | "She took a sip of" | | 18 | "Her scar itched, that old" | | 19 | "He said it flatly, without" |
| | ratio | 0.508 | |
| 44.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 49 | | totalSentences | 59 | | matches | | 0 | "The neon hummed through the" | | 1 | "The Raven's Nest." | | 2 | "Rory pushed through the door" | | 3 | "The place hadn't changed in" | | 4 | "She ordered a whiskey from" | | 5 | "She just wanted to sit." | | 6 | "The delivery shift had run" | | 7 | "He was half-hidden in the" | | 8 | "A familiar slope to his" | | 9 | "She almost looked away." | | 10 | "London was full of ghosts" | | 11 | "His jaw had sharpened, his" | | 12 | "She stayed frozen halfway." | | 13 | "His voice cracked on her" | | 14 | "The sound of it was" | | 15 | "She heard herself say the" | | 16 | "He set his glass down." | | 17 | "The whisky barely sloshed." | | 18 | "He laughed, a hollow sound" | | 19 | "The words hung in the" |
| | ratio | 0.831 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 59 | | matches | (empty) | | ratio | 0 | |
| 5.49% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 26 | | technicalSentenceCount | 5 | | matches | | 0 | "The neon hummed through the rain-slicked street, a green pulse that painted the pavement in sickly light." | | 1 | "Same sign, same cracked step, same smell of spilled ale and wood polish that hit you like an old memory you hadn't asked for." | | 2 | "Same maps on the walls, same black-and-white photographs of faces she'd never known, same low murmur of conversation that parted around her entrance like water …" | | 3 | "He was half-hidden in the shadows near the back, nursing a drink that looked untouched." | | 4 | "The girl retreated with the nervousness of someone who could smell old history on two strangers and wanted no part of it." |
| |
| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, but the words tasted flat" |
| |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "She heard (hear)" | | 1 | "He laughed (laugh)" |
| | dialogueSentences | 47 | | tagDensity | 0.191 | | leniency | 0.383 | | rawRatio | 0.222 | | effectiveRatio | 0.085 | |