| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 4 | | adverbTags | | 0 | "Patel's laugh echoed too [too]" | | 1 | "She advanced slowly [slowly]" | | 2 | "The words tasted like [like]" | | 3 | "she said quietly [quietly]" |
| | dialogueSentences | 36 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.25 | | effectiveRatio | 0.222 | |
| 92.81% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2086 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "completely" | | 1 | "carefully" | | 2 | "slowly" |
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| 80.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 40.08% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2086 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | word | "down her spine" | | count | 1 |
| | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "echoing" | | 1 | "fluttered" | | 2 | "etched" | | 3 | "weight" | | 4 | "scanned" | | 5 | "shimmered" | | 6 | "pulse" | | 7 | "charged" | | 8 | "tracing" | | 9 | "shattered" | | 10 | "racing" | | 11 | "echoed" | | 12 | "quickened" | | 13 | "vibrated" | | 14 | "aftermath" | | 15 | "silence" | | 16 | "down her spine" | | 17 | "gloom" | | 18 | "footsteps" | | 19 | "aligned" |
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| 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 | 197 | | matches | (empty) | |
| 92.10% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 5 | | narrationSentences | 197 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "appeared to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 216 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 43 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 11 | | totalWords | 2087 | | ratio | 0.005 | | matches | | 0 | "Rift convergence at Camden - full moon peak. Compass will confirm." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 17 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 63 | | wordCount | 1625 | | uniqueNames | 20 | | maxNameDensity | 0.68 | | worstName | "Patel" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 8 | | Tube | 1 | | Camden | 4 | | Veil | 4 | | Market | 7 | | Patel | 11 | | Polished | 1 | | London | 3 | | Underground | 1 | | British | 1 | | Museum | 1 | | Kowalski | 4 | | Ancient | 2 | | History | 1 | | Oxford | 1 | | Morris | 2 | | Compass | 2 | | Eva | 4 | | One | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Market" | | 3 | "Patel" | | 4 | "Underground" | | 5 | "Museum" | | 6 | "Kowalski" | | 7 | "Morris" | | 8 | "Compass" | | 9 | "Eva" |
| | places | | 0 | "Camden" | | 1 | "London" | | 2 | "Ancient" | | 3 | "Oxford" |
| | globalScore | 1 | | windowScore | 1 | |
| 90.48% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 126 | | glossingSentenceCount | 3 | | matches | | 0 | "shadows that seemed to swallow the beam of her torch" | | 1 | "sounded like he'd seen a ghost" | | 2 | "shadows that seemed to move independently" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.479 | | wordCount | 2087 | | matches | | 0 | "not into a simple murder, but into something vast" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 216 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 38.65 | | std | 22.46 | | cv | 0.581 | | sampleLengths | | 0 | 99 | | 1 | 37 | | 2 | 61 | | 3 | 40 | | 4 | 68 | | 5 | 27 | | 6 | 74 | | 7 | 34 | | 8 | 58 | | 9 | 25 | | 10 | 45 | | 11 | 9 | | 12 | 73 | | 13 | 57 | | 14 | 59 | | 15 | 15 | | 16 | 18 | | 17 | 63 | | 18 | 55 | | 19 | 5 | | 20 | 37 | | 21 | 9 | | 22 | 47 | | 23 | 34 | | 24 | 63 | | 25 | 87 | | 26 | 7 | | 27 | 42 | | 28 | 17 | | 29 | 61 | | 30 | 37 | | 31 | 4 | | 32 | 30 | | 33 | 51 | | 34 | 53 | | 35 | 14 | | 36 | 18 | | 37 | 51 | | 38 | 55 | | 39 | 37 | | 40 | 9 | | 41 | 68 | | 42 | 28 | | 43 | 9 | | 44 | 47 | | 45 | 24 | | 46 | 43 | | 47 | 39 | | 48 | 37 | | 49 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 197 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 281 | | matches | | 0 | "was photographing" | | 1 | "was already moving" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 216 | | ratio | 0.005 | | matches | | 0 | "*Rift convergence at Camden - full moon peak." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1636 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 49 | | adverbRatio | 0.029951100244498777 | | lyAdverbCount | 25 | | lyAdverbRatio | 0.015281173594132029 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 216 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 216 | | mean | 9.66 | | std | 7.14 | | cv | 0.739 | | sampleLengths | | 0 | 21 | | 1 | 15 | | 2 | 23 | | 3 | 6 | | 4 | 34 | | 5 | 12 | | 6 | 3 | | 7 | 18 | | 8 | 4 | | 9 | 13 | | 10 | 11 | | 11 | 8 | | 12 | 19 | | 13 | 3 | | 14 | 7 | | 15 | 9 | | 16 | 18 | | 17 | 13 | | 18 | 8 | | 19 | 8 | | 20 | 7 | | 21 | 12 | | 22 | 7 | | 23 | 9 | | 24 | 4 | | 25 | 8 | | 26 | 5 | | 27 | 8 | | 28 | 19 | | 29 | 6 | | 30 | 21 | | 31 | 2 | | 32 | 6 | | 33 | 4 | | 34 | 20 | | 35 | 15 | | 36 | 4 | | 37 | 30 | | 38 | 7 | | 39 | 15 | | 40 | 18 | | 41 | 4 | | 42 | 6 | | 43 | 8 | | 44 | 3 | | 45 | 22 | | 46 | 7 | | 47 | 15 | | 48 | 2 | | 49 | 9 |
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| 66.98% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.4212962962962963 | | totalSentences | 216 | | uniqueOpeners | 91 | |
| 18.83% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 177 | | matches | | 0 | "Too heavy for its size." |
| | ratio | 0.006 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 41 | | totalSentences | 177 | | matches | | 0 | "She checked her watch, the" | | 1 | "He stood ten paces away," | | 2 | "She crouched beside the corpse," | | 3 | "She pried it free with" | | 4 | "She turned it over." | | 5 | "He shifted his weight, military" | | 6 | "She scanned the platform." | | 7 | "She straightened, salt-and-pepper hair catching" | | 8 | "She pointed to the dead" | | 9 | "She pushed the memory down," | | 10 | "He flipped a page on" | | 11 | "He gestured at the compass" | | 12 | "She slipped it into an" | | 13 | "She moved to the spilled" | | 14 | "She ignored him, tracing the" | | 15 | "Her torch beam caught something" | | 16 | "She bagged it, mind racing." | | 17 | "She approached the wall where" | | 18 | "He complied, though his expression" | | 19 | "She shot him a look" |
| | ratio | 0.232 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 124 | | totalSentences | 177 | | matches | | 0 | "Detective Harlow Quinn descended the" | | 1 | "The air hung thick with" | | 2 | "This was no ordinary crime" | | 3 | "The Veil Market had pulled" | | 4 | "She checked her watch, the" | | 5 | "The call had come in" | | 6 | "The body lay sprawled near" | | 7 | "Shards of violet glass crunched" | | 8 | "The ceiling arched fifteen feet" | | 9 | "DS Patel's voice cut through" | | 10 | "He stood ten paces away," | | 11 | "She crouched beside the corpse," | | 12 | "The man's fingers clutched a" | | 13 | "She pried it free with" | | 14 | "A compass, its casing etched" | | 15 | "The needle spun wildly, refusing" | | 16 | "Patina of verdigris coated the" | | 17 | "She turned it over." | | 18 | "He shifted his weight, military" | | 19 | "The station's currentLocation beneath Camden" |
| | ratio | 0.701 | |
| 56.50% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 177 | | matches | | 0 | "Now she understood why." | | 1 | "Before her partner had walked" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 64 | | technicalSentenceCount | 3 | | matches | | 0 | "Yellow police tape fluttered across the tunnel entrance, a feeble barrier against the shadows that seemed to swallow the beam of her torch." | | 1 | "Overturned tables, scattered herbs that shimmered unnaturally under the lights, a satchel split open with books spilling across the tiles." | | 2 | "The air grew colder, carrying whispers that might have been wind through cracks or something far worse." |
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| 93.75% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 1 | | matches | | 0 | "Her voice stayed, steady" |
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| 38.89% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 4 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she observed (observe)" | | 2 | "She conceded (concede)" | | 3 | "Patel whispered (whisper)" |
| | dialogueSentences | 36 | | tagDensity | 0.194 | | leniency | 0.389 | | rawRatio | 0.571 | | effectiveRatio | 0.222 | |