| 77.55% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 21 | | adverbTagCount | 3 | | adverbTags | | 0 | "he said finally [finally]" | | 1 | "She gestured around [around]" | | 2 | "he said quietly [quietly]" |
| | dialogueSentences | 49 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0.143 | | effectiveRatio | 0.122 | |
| 86.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2181 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "slowly" | | 1 | "completely" | | 2 | "very" | | 3 | "quickly" |
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| 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) | |
| 47.27% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2181 | | totalAiIsms | 23 | | found | | | highlights | | 0 | "fractured" | | 1 | "scanned" | | 2 | "weight" | | 3 | "measured" | | 4 | "flickered" | | 5 | "silence" | | 6 | "sentinel" | | 7 | "clandestine" | | 8 | "traced" | | 9 | "tension" | | 10 | "reminder" | | 11 | "familiar" | | 12 | "unspoken" | | 13 | "tracing" | | 14 | "unreadable" | | 15 | "beacon" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 113 | | matches | (empty) | |
| 79.65% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 5 | | narrationSentences | 113 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 141 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2181 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 23 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 33 | | wordCount | 1423 | | uniqueNames | 13 | | maxNameDensity | 0.7 | | worstName | "Silas" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Silas" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Soho | 2 | | Carter | 2 | | Blackwood | 2 | | Irish | 1 | | Silas | 10 | | Spymaster | 2 | | Europe | 1 | | Aurora | 8 | | Charles | 1 | | Bridge | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Blackwood" | | 4 | "Silas" | | 5 | "Spymaster" | | 6 | "Aurora" |
| | places | | 0 | "Soho" | | 1 | "Europe" | | 2 | "Charles" | | 3 | "Bridge" | | 4 | "London" |
| | globalScore | 1 | | windowScore | 1 | |
| 17.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 94 | | glossingSentenceCount | 5 | | matches | | 0 | "felt like a museum to other people's se" | | 1 | "not quite reaching his eyes" | | 2 | "tasted like memories she had tried to out" | | 3 | "something like hope, a reminder that not eve" | | 4 | "looked like the Charles Bridge" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.459 | | wordCount | 2181 | | matches | | 0 | "Not that I let you go, but" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 141 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 51 | | mean | 42.76 | | std | 23.29 | | cv | 0.545 | | sampleLengths | | 0 | 93 | | 1 | 59 | | 2 | 4 | | 3 | 87 | | 4 | 26 | | 5 | 45 | | 6 | 47 | | 7 | 81 | | 8 | 17 | | 9 | 52 | | 10 | 53 | | 11 | 28 | | 12 | 30 | | 13 | 52 | | 14 | 36 | | 15 | 45 | | 16 | 67 | | 17 | 51 | | 18 | 25 | | 19 | 53 | | 20 | 26 | | 21 | 2 | | 22 | 2 | | 23 | 91 | | 24 | 8 | | 25 | 22 | | 26 | 38 | | 27 | 57 | | 28 | 58 | | 29 | 42 | | 30 | 39 | | 31 | 61 | | 32 | 59 | | 33 | 24 | | 34 | 64 | | 35 | 7 | | 36 | 27 | | 37 | 58 | | 38 | 24 | | 39 | 29 | | 40 | 85 | | 41 | 29 | | 42 | 54 | | 43 | 40 | | 44 | 39 | | 45 | 43 | | 46 | 42 | | 47 | 4 | | 48 | 48 | | 49 | 82 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 113 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 237 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 141 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1427 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 51 | | adverbRatio | 0.035739313244569026 | | lyAdverbCount | 14 | | lyAdverbRatio | 0.009810791871058164 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 141 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 141 | | mean | 15.47 | | std | 9.5 | | cv | 0.614 | | sampleLengths | | 0 | 21 | | 1 | 28 | | 2 | 12 | | 3 | 32 | | 4 | 17 | | 5 | 16 | | 6 | 10 | | 7 | 16 | | 8 | 4 | | 9 | 19 | | 10 | 23 | | 11 | 14 | | 12 | 10 | | 13 | 21 | | 14 | 14 | | 15 | 12 | | 16 | 13 | | 17 | 23 | | 18 | 9 | | 19 | 20 | | 20 | 21 | | 21 | 6 | | 22 | 6 | | 23 | 9 | | 24 | 11 | | 25 | 8 | | 26 | 17 | | 27 | 30 | | 28 | 8 | | 29 | 9 | | 30 | 24 | | 31 | 28 | | 32 | 11 | | 33 | 10 | | 34 | 32 | | 35 | 9 | | 36 | 16 | | 37 | 3 | | 38 | 13 | | 39 | 17 | | 40 | 6 | | 41 | 13 | | 42 | 24 | | 43 | 9 | | 44 | 6 | | 45 | 12 | | 46 | 18 | | 47 | 10 | | 48 | 35 | | 49 | 15 |
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| 62.88% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.3900709219858156 | | totalSentences | 141 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 108 | | matches | | 0 | "Then she saw him." | | 1 | "Instead he reached under the" | | 2 | "So many words left unspoken." | | 3 | "Instead she spoke." | | 4 | "Simply the recognition that some" |
| | ratio | 0.046 | |
| 64.44% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 108 | | matches | | 0 | "She had only meant to" | | 1 | "She scanned the room out" | | 2 | "His auburn hair had gone" | | 3 | "He looked up, hazel eyes" | | 4 | "His voice carried that same" | | 5 | "He set the glass down" | | 6 | "She froze near the door," | | 7 | "He gestured to a stool" | | 8 | "Her boots left faint wet" | | 9 | "She slid onto the stool," | | 10 | "He moved with that same" | | 11 | "she said, accepting the glass" | | 12 | "He leaned on the bar," | | 13 | "She took a sip, letting" | | 14 | "He glanced down at her" | | 15 | "She pulled her sleeve down" | | 16 | "She wondered if he still" | | 17 | "he said finally" | | 18 | "His voice stayed even, but" | | 19 | "He straightened, the limp more" |
| | ratio | 0.389 | |
| 57.22% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 108 | | matches | | 0 | "The green neon glow of" | | 1 | "Aurora Carter pushed open the" | | 2 | "Rain dripped from her straight" | | 3 | "She had only meant to" | | 4 | "Maps yellowed with age lined" | | 5 | "The place felt like a" | | 6 | "She scanned the room out" | | 7 | "Silas Blackwood stood behind the" | | 8 | "His auburn hair had gone" | | 9 | "The slight limp showed when" | | 10 | "A silver signet ring caught" | | 11 | "He looked up, hazel eyes" | | 12 | "His voice carried that same" | | 13 | "He set the glass down" | | 14 | "She froze near the door," | | 15 | "The small crescent scar on" | | 16 | "A faint smile tugged at" | | 17 | "He gestured to a stool" | | 18 | "Aurora hesitated, then crossed the" | | 19 | "Her boots left faint wet" |
| | ratio | 0.806 | |
| 92.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 108 | | matches | | 0 | "Now they sat as strangers" | | 1 | "Before everything fractured." |
| | ratio | 0.019 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 61 | | technicalSentenceCount | 3 | | matches | | 0 | "Behind Silas, the bookshelf that hid his secret room stood like a sentinel." | | 1 | "The contact sent years rushing back, memories of stolen afternoons in this very bar, conversations that stretched until dawn." | | 2 | "Inside, two people who had once meant everything to each other began the slow work of bridging the chasm time had carved between them." |
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| 53.57% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 21 | | uselessAdditionCount | 3 | | matches | | 0 | "A faint smile tugged, not quite reaching his eyes" | | 1 | "His fingers brushed, a gesture so automatic she doubted he noticed it" | | 2 | "Aurora leaned, her voice dropping" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 49 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.143 | | effectiveRatio | 0.041 | |