| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 16 | | tagDensity | 0.188 | | leniency | 0.375 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1003 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 75.07% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1003 | | totalAiIsms | 5 | | found | | | highlights | | 0 | "scanned" | | 1 | "weight" | | 2 | "mosaic" | | 3 | "echoes" | | 4 | "footsteps" |
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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 | 1 | | narrationSentences | 93 | | matches | | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 93 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1003 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 19 | | wordCount | 924 | | uniqueNames | 12 | | maxNameDensity | 0.54 | | worstName | "Quinn" | | maxWindowNameDensity | 1 | | worstWindowName | "Street" | | discoveredNames | | Camden | 1 | | High | 1 | | Street | 2 | | Purple | 1 | | Turtle | 1 | | Inverness | 1 | | Morris | 2 | | Tube | 1 | | Old | 2 | | Veil | 1 | | Market | 1 | | Quinn | 5 |
| | persons | | | places | | 0 | "Camden" | | 1 | "High" | | 2 | "Street" | | 3 | "Purple" | | 4 | "Inverness" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 61 | | glossingSentenceCount | 1 | | matches | | 0 | "quite see under the hood" |
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| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 3 | | per1kWords | 2.991 | | wordCount | 1003 | | matches | | 0 | "Not toward her, not away, but sideways" | | 1 | "not away, but sideways" | | 2 | "not with guilt but with something closer to pity" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 23.33 | | std | 19.56 | | cv | 0.839 | | sampleLengths | | 0 | 15 | | 1 | 52 | | 2 | 3 | | 3 | 56 | | 4 | 2 | | 5 | 9 | | 6 | 43 | | 7 | 3 | | 8 | 37 | | 9 | 35 | | 10 | 4 | | 11 | 6 | | 12 | 4 | | 13 | 25 | | 14 | 4 | | 15 | 49 | | 16 | 4 | | 17 | 48 | | 18 | 42 | | 19 | 3 | | 20 | 56 | | 21 | 6 | | 22 | 48 | | 23 | 3 | | 24 | 54 | | 25 | 61 | | 26 | 26 | | 27 | 5 | | 28 | 20 | | 29 | 7 | | 30 | 1 | | 31 | 31 | | 32 | 34 | | 33 | 43 | | 34 | 13 | | 35 | 33 | | 36 | 10 | | 37 | 8 | | 38 | 5 | | 39 | 52 | | 40 | 15 | | 41 | 18 | | 42 | 10 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 93 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 168 | | matches | | 0 | "was watching" | | 1 | "was coming" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 106 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 526 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.026615969581749048 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0019011406844106464 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 9.46 | | std | 6.59 | | cv | 0.696 | | sampleLengths | | 0 | 15 | | 1 | 9 | | 2 | 18 | | 3 | 4 | | 4 | 8 | | 5 | 13 | | 6 | 3 | | 7 | 9 | | 8 | 17 | | 9 | 16 | | 10 | 14 | | 11 | 2 | | 12 | 2 | | 13 | 7 | | 14 | 4 | | 15 | 18 | | 16 | 2 | | 17 | 7 | | 18 | 12 | | 19 | 1 | | 20 | 2 | | 21 | 7 | | 22 | 2 | | 23 | 14 | | 24 | 14 | | 25 | 2 | | 26 | 13 | | 27 | 7 | | 28 | 4 | | 29 | 9 | | 30 | 4 | | 31 | 6 | | 32 | 4 | | 33 | 6 | | 34 | 4 | | 35 | 15 | | 36 | 4 | | 37 | 2 | | 38 | 22 | | 39 | 17 | | 40 | 8 | | 41 | 4 | | 42 | 9 | | 43 | 21 | | 44 | 18 | | 45 | 12 | | 46 | 12 | | 47 | 12 | | 48 | 6 | | 49 | 3 |
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| 89.31% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5471698113207547 | | totalSentences | 106 | | uniqueOpeners | 58 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 79 | | matches | | 0 | "Actually laughed, and ducked into" | | 1 | "Somewhere behind her, a door" | | 2 | "Then he was through." | | 3 | "Further along, crates of weapons" |
| | ratio | 0.051 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 79 | | matches | | 0 | "Her worn leather watch caught" | | 1 | "She didn't stop." | | 2 | "He cut through a knot" | | 3 | "She mirrored him, close enough" | | 4 | "Her target slowed at the" | | 5 | "He raised both hands, empty," | | 6 | "His accent curled around the" | | 7 | "It weighed a ton, oak" | | 8 | "She'd stood in the doorway" | | 9 | "She went down." | | 10 | "Her torch beam bounced off" | | 11 | "She slapped the casing." | | 12 | "It thickened as she descended," | | 13 | "She knew the name the" | | 14 | "Her grey hoodie slipped between" | | 15 | "He held out his hand" | | 16 | "Her suspect reached the far" | | 17 | "She hit the platform running," | | 18 | "Her suspect heard it too." | | 19 | "He risked a look back." |
| | ratio | 0.291 | |
| 73.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 79 | | matches | | 0 | "The suspect vaulted the barrier" | | 1 | "Quinn slammed her palm on" | | 2 | "Her worn leather watch caught" | | 3 | "Rain needled her face." | | 4 | "Boots pounded wet tarmac behind" | | 5 | "Backups, giving up at the" | | 6 | "She didn't stop." | | 7 | "The profile she'd built over" | | 8 | "He cut through a knot" | | 9 | "She mirrored him, close enough" | | 10 | "The alley swallowed sound." | | 11 | "Brick walls rose on both" | | 12 | "Her target slowed at the" | | 13 | "Men who slow at dead" | | 14 | "Quinn pulled up short, hand" | | 15 | "Rain ran down a narrow" | | 16 | "He raised both hands, empty," | | 17 | "A gesture of surrender." | | 18 | "His accent curled around the" | | 19 | "Seville, or near enough." |
| | ratio | 0.772 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 79 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 7 | | matches | | 0 | "Brick walls rose on both sides, slick with runoff that tasted of rust when it hit her lips." | | 1 | "A bookshelf, of all things, pivoting out of a wall that had looked solid two seconds ago." | | 2 | "It weighed a ton, oak and knowledge and secrets, and behind it yawned a stairwell that descended into warm amber light." | | 3 | "A woman with too many rings arranged glass phials of something that moved against the inside." | | 4 | "Her grey hoodie slipped between the stalls, twenty metres ahead and losing ground to a crowd that didn't part for him the way normal crowds do." | | 5 | "Quinn hit the bottom step as he hit the top, and the tunnel beyond stretched into darkness and echoes and the distant rumble of trains that belonged to lines cl…" | | 6 | "Above her, the suspect ran, and from the tunnel's black throat came a sound that wasn't his footsteps." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 87.50% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 16 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 0.5 | | effectiveRatio | 0.125 | |