| 66.67% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "Silas said quietly [quietly]" | | 1 | "Silas said dryly [dryly]" |
| | dialogueSentences | 30 | | tagDensity | 0.433 | | leniency | 0.867 | | rawRatio | 0.154 | | effectiveRatio | 0.133 | |
| 93.99% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1664 | | totalAiIsmAdverbs | 2 | | 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) | |
| 12.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1664 | | totalAiIsms | 29 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | |
| | highlights | | 0 | "echoes" | | 1 | "tapestry" | | 2 | "weight" | | 3 | "tracing" | | 4 | "familiar" | | 5 | "glint" | | 6 | "silence" | | 7 | "fractured" | | 8 | "etched" | | 9 | "tension" | | 10 | "navigating" | | 11 | "scanned" | | 12 | "pulse" | | 13 | "unspoken" | | 14 | "flickered" | | 15 | "dancing" | | 16 | "pulsed" | | 17 | "reminder" | | 18 | "echoed" |
| |
| 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 | 76 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 76 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 91 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1664 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1127 | | uniqueNames | 15 | | maxNameDensity | 1.24 | | worstName | "Rory" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Cardiff | 1 | | Yu-Fei | 1 | | Cheung | 1 | | Golden | 1 | | Empress | 1 | | Eastern | 1 | | Europe | 1 | | Evan | 1 | | Blackwood | 1 | | Prague | 1 | | London | 1 | | Rory | 14 | | Silas | 14 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Yu-Fei" | | 3 | "Cheung" | | 4 | "Evan" | | 5 | "Blackwood" | | 6 | "Rory" | | 7 | "Silas" |
| | places | | 0 | "Cardiff" | | 1 | "Eastern" | | 2 | "Europe" | | 3 | "Prague" | | 4 | "London" |
| | globalScore | 0.879 | | windowScore | 0.5 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 59 | | glossingSentenceCount | 5 | | matches | | 0 | "looked like they'd been carved from grani" | | 1 | "felt like it was closing in" | | 2 | "looked like a man who had carried the wor" | | 3 | "looked like a woman who had picked the wo" | | 4 | "as if weighing the word" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1664 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 30 | | mean | 55.47 | | std | 31.19 | | cv | 0.562 | | sampleLengths | | 0 | 126 | | 1 | 112 | | 2 | 22 | | 3 | 90 | | 4 | 96 | | 5 | 2 | | 6 | 83 | | 7 | 26 | | 8 | 47 | | 9 | 37 | | 10 | 75 | | 11 | 65 | | 12 | 62 | | 13 | 22 | | 14 | 94 | | 15 | 82 | | 16 | 45 | | 17 | 68 | | 18 | 71 | | 19 | 44 | | 20 | 72 | | 21 | 56 | | 22 | 45 | | 23 | 61 | | 24 | 23 | | 25 | 11 | | 26 | 57 | | 27 | 11 | | 28 | 8 | | 29 | 51 |
| |
| 72.95% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 7 | | totalSentences | 76 | | matches | | 0 | "was pulled" | | 1 | "were draped" | | 2 | "been carved" | | 3 | "was supposed" | | 4 | "was hunched" | | 5 | "been gone" | | 6 | "been redacted" | | 7 | "was rasped" | | 8 | "was etched" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 182 | | matches | | 0 | "was closing" | | 1 | "were carrying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 5 | | flaggedSentences | 5 | | totalSentences | 93 | | ratio | 0.054 | | matches | | 0 | "The MI6 files had been redacted; the rumors had died." | | 1 | "But in this room, silence was not the absence of sound; it was a discipline." | | 2 | "Silas looked older than fifty-eight; he looked like a man who had carried the world and set it down too hard." | | 3 | "He didn't offer it; he simply slid it across the table toward her." | | 4 | "Her fingers brushed his; his skin was cool, calloused, the skin of a man who had done the things men did in the shadows." |
| |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1134 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small crescent-shaped scar" |
| | adverbCount | 33 | | adverbRatio | 0.0291005291005291 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.013227513227513227 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 17.89 | | std | 14.1 | | cv | 0.788 | | sampleLengths | | 0 | 35 | | 1 | 14 | | 2 | 10 | | 3 | 32 | | 4 | 35 | | 5 | 21 | | 6 | 38 | | 7 | 7 | | 8 | 9 | | 9 | 37 | | 10 | 7 | | 11 | 4 | | 12 | 11 | | 13 | 20 | | 14 | 24 | | 15 | 23 | | 16 | 23 | | 17 | 3 | | 18 | 29 | | 19 | 38 | | 20 | 26 | | 21 | 2 | | 22 | 11 | | 23 | 4 | | 24 | 26 | | 25 | 10 | | 26 | 32 | | 27 | 11 | | 28 | 15 | | 29 | 12 | | 30 | 18 | | 31 | 17 | | 32 | 3 | | 33 | 22 | | 34 | 12 | | 35 | 4 | | 36 | 15 | | 37 | 25 | | 38 | 24 | | 39 | 7 | | 40 | 11 | | 41 | 12 | | 42 | 42 | | 43 | 18 | | 44 | 7 | | 45 | 37 | | 46 | 15 | | 47 | 7 | | 48 | 4 | | 49 | 90 |
| |
| 39.25% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.26881720430107525 | | totalSentences | 93 | | uniqueOpeners | 25 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 92.46% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 69 | | matches | | 0 | "She hadn't descended to the" | | 1 | "Her straight, shoulder-length black hair" | | 2 | "She knew the stories that" | | 3 | "She was supposed to be" | | 4 | "She moved silently, her boots" | | 5 | "He shifted, and the motion" | | 6 | "Her fingers instinctively drifted to" | | 7 | "He had been gone." | | 8 | "She had spent three years" | | 9 | "She thought she had remained" | | 10 | "His voice was rasped, worn" | | 11 | "His hazel eyes, clouded by" | | 12 | "They scanned her face, dissecting" | | 13 | "He saw the bright blue" | | 14 | "He saw the woman who" | | 15 | "She stepped forward, emerging from" | | 16 | "He unscrewed the cap with" | | 17 | "He didn't offer it; he" | | 18 | "She looked at Silas, really" | | 19 | "he repeated, as if weighing" |
| | ratio | 0.319 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 65 | | totalSentences | 69 | | matches | | 0 | "The green neon sign above" | | 1 | "Rory stood in the shadow" | | 2 | "She hadn't descended to the" | | 3 | "Her straight, shoulder-length black hair" | | 4 | "The walls were draped in" | | 5 | "Rory knew every crease in" | | 6 | "She knew the stories that" | | 7 | "She was supposed to be" | | 8 | "A scrape of weight." | | 9 | "A sound too heavy for" | | 10 | "She moved silently, her boots" | | 11 | "A figure sat in the" | | 12 | "The man was hunched over" | | 13 | "He shifted, and the motion" | | 14 | "Rory's breath hitched." | | 15 | "Her fingers instinctively drifted to" | | 16 | "The profile was familiar, even" | | 17 | "The man raised his hand" | | 18 | "The name hit her with" | | 19 | "He had been gone." |
| | ratio | 0.942 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 69 | | matches | (empty) | | ratio | 0 | |
| 12.99% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 44 | | technicalSentenceCount | 8 | | matches | | 0 | "The green neon sign above the door of The Raven's Nest buzzed with the persistent, erratic hum of a trapped wasp, casting a sickly luminescence over the dust mo…" | | 1 | "Her straight, shoulder-length black hair was pulled back in a severe knot, pulling the skin at her temples tight, emphasizing the sharp angles of a face that ha…" | | 2 | "The walls were draped in the usual tapestry of her life's geography: oil paintings of old maps where coastlines bled into classified zones, and black-and-white …" | | 3 | "The profile was familiar, even through the grey-streaked auburn hair that fell heavier than she remembered, and the neatly trimmed beard that obscured the jawli…" | | 4 | "They scanned her face, dissecting the changes, searching for the girl who had arrived in London with a suitcase and a heart full of fractures." | | 5 | "He saw the bright blue eyes that no longer darted for exits, the cool intelligence that had replaced the frantic energy of her flight." | | 6 | "Silas looked older than fifty-eight; he looked like a man who had carried the world and set it down too hard." | | 7 | "The green neon hummed on, indifferent to the past, illuminating two people who had survived the fire and found, unexpectedly, each other in the ashes." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 5 | | matches | | 0 | "Rory said, her voice steady, though her pulse hammered against her ribs" | | 1 | "Silas tested, a faint crinkle appearing at the corners of his eyes" | | 2 | "Rory said, the admission slipping out before she could cage it" | | 3 | "Rory said, her hand hovering over the glass" | | 4 | "he repeated, as if weighing the word" |
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| 83.33% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 11 | | fancyCount | 2 | | fancyTags | | 0 | "Silas murmured (murmur)" | | 1 | "he repeated (repeat)" |
| | dialogueSentences | 30 | | tagDensity | 0.367 | | leniency | 0.733 | | rawRatio | 0.182 | | effectiveRatio | 0.133 | |