| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 93 | | tagDensity | 0.226 | | leniency | 0.452 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.36% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1897 | | totalAiIsmAdverbs | 1 | | 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) | |
| 100.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1897 | | totalAiIsms | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "room fell silent" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 89 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 89 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 158 | | 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 | 1906 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 55 | | wordCount | 1051 | | uniqueNames | 15 | | maxNameDensity | 1.81 | | worstName | "Silas" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Tuesday | 1 | | Greek | 1 | | Street | 1 | | Rory | 10 | | Raven | 1 | | Nest | 1 | | Silas | 19 | | Wenceslas | 2 | | Square | 2 | | November | 1 | | National | 1 | | Museum | 1 | | Marek | 12 | | Kozel | 1 | | Brass | 1 |
| | persons | | | places | | 0 | "Greek" | | 1 | "Street" | | 2 | "Raven" | | 3 | "Wenceslas" |
| | globalScore | 0.596 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like they were underwater" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1906 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 158 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 100 | | mean | 19.06 | | std | 19.86 | | cv | 1.042 | | sampleLengths | | 0 | 53 | | 1 | 22 | | 2 | 48 | | 3 | 6 | | 4 | 1 | | 5 | 2 | | 6 | 5 | | 7 | 35 | | 8 | 92 | | 9 | 3 | | 10 | 8 | | 11 | 20 | | 12 | 1 | | 13 | 71 | | 14 | 3 | | 15 | 3 | | 16 | 5 | | 17 | 51 | | 18 | 3 | | 19 | 15 | | 20 | 12 | | 21 | 5 | | 22 | 16 | | 23 | 8 | | 24 | 50 | | 25 | 24 | | 26 | 11 | | 27 | 2 | | 28 | 9 | | 29 | 2 | | 30 | 6 | | 31 | 3 | | 32 | 18 | | 33 | 27 | | 34 | 10 | | 35 | 1 | | 36 | 18 | | 37 | 66 | | 38 | 2 | | 39 | 15 | | 40 | 43 | | 41 | 2 | | 42 | 6 | | 43 | 28 | | 44 | 19 | | 45 | 6 | | 46 | 33 | | 47 | 15 | | 48 | 10 | | 49 | 12 |
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| 97.38% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 89 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 159 | | matches | (empty) | |
| 34.36% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 7 | | semicolonCount | 1 | | flaggedSentences | 6 | | totalSentences | 158 | | ratio | 0.038 | | matches | | 0 | "The man in the doorway was wrong for the hour — long gray coat gone shiny at the cuffs, city shoes drowned through, a canvas bag held the way a man holds a bag when everything he owns fits in it." | | 1 | "He crossed to the far wall, to the photographs, and stopped in front of the one of Wenceslas Square — the November, flags and smoke and the National Museum behind it all — and laid two fingers on the frame." | | 2 | "He had been a big man once — Rory could see the architecture of it, the shoulders of a wardrobe — but the filling had gone out of him, and his hands, coming out of his pockets, carried a tremor he made no attempt to hide." | | 3 | "\"Excuse me a moment.\" Silas pressed the shelving behind the optics; a section of wall swung inward on darkness and closed behind him like the wall had never opened." | | 4 | "Brass, worn smooth — a tram token, older than Rory." | | 5 | "The rain took him in pieces — coat, shoulders, gray head, the reflection in the puddle." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1048 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.02480916030534351 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 158 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 158 | | mean | 12.06 | | std | 10.76 | | cv | 0.892 | | sampleLengths | | 0 | 15 | | 1 | 38 | | 2 | 12 | | 3 | 10 | | 4 | 10 | | 5 | 9 | | 6 | 26 | | 7 | 3 | | 8 | 6 | | 9 | 1 | | 10 | 2 | | 11 | 5 | | 12 | 4 | | 13 | 17 | | 14 | 7 | | 15 | 7 | | 16 | 41 | | 17 | 6 | | 18 | 5 | | 19 | 40 | | 20 | 3 | | 21 | 8 | | 22 | 20 | | 23 | 1 | | 24 | 3 | | 25 | 46 | | 26 | 19 | | 27 | 3 | | 28 | 3 | | 29 | 3 | | 30 | 5 | | 31 | 12 | | 32 | 24 | | 33 | 7 | | 34 | 8 | | 35 | 3 | | 36 | 15 | | 37 | 8 | | 38 | 4 | | 39 | 5 | | 40 | 16 | | 41 | 8 | | 42 | 17 | | 43 | 7 | | 44 | 26 | | 45 | 10 | | 46 | 14 | | 47 | 11 | | 48 | 2 | | 49 | 9 |
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| 53.16% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.36075949367088606 | | totalSentences | 158 | | uniqueOpeners | 57 | |
| 37.45% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 89 | | matches | | | ratio | 0.011 | |
| 76.18% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 89 | | matches | | 0 | "She propped the moped under" | | 1 | "she announced, setting them on" | | 2 | "He had the till open" | | 3 | "His eyes went first to" | | 4 | "He didn't come to the" | | 5 | "He crossed to the far" | | 6 | "His voice had been kept" | | 7 | "He had been a big" | | 8 | "She swapped stools without argument." | | 9 | "He poured it into a" | | 10 | "He poured a second and" | | 11 | "He hung his rag on" | | 12 | "He ate one" | | 13 | "He glanced at the window," | | 14 | "He wiped his fingers, one" | | 15 | "he touched his own chest," | | 16 | "His mouth bent without finishing" | | 17 | "His eyes went up to" | | 18 | "He worked a telephone out" | | 19 | "He looked at the door," |
| | ratio | 0.36 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 89 | | matches | | 0 | "Half eleven on a wet" | | 1 | "She propped the moped under" | | 2 | "she announced, setting them on" | | 3 | "Silas took the bag anyway" | | 4 | "He had the till open" | | 5 | "Rain ran the window, and" | | 6 | "The bell over the door." | | 7 | "Silas's head came up." | | 8 | "His eyes went first to" | | 9 | "The glass in his hand" | | 10 | "A muscle moved under the" | | 11 | "The man in the doorway" | | 12 | "He didn't come to the" | | 13 | "Customers come to the bar." | | 14 | "He crossed to the far" | | 15 | "His voice had been kept" | | 16 | "The stranger turned." | | 17 | "He had been a big" | | 18 | "Silas came last." | | 19 | "Silas came around the bar," |
| | ratio | 0.955 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 89 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 1 | | matches | | 0 | "He hung his rag on its hook as if the hook mattered." |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "she announced (announce)" | | 1 | "Silas pressed (press)" |
| | dialogueSentences | 93 | | tagDensity | 0.022 | | leniency | 0.043 | | rawRatio | 1 | | effectiveRatio | 0.043 | |