| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 18 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 48 | | tagDensity | 0.375 | | leniency | 0.75 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1268 | | 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) | |
| 88.17% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1268 | | totalAiIsms | 3 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "gloom" |
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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 | 82 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 82 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 112 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 57 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 4 | | markdownWords | 11 | | totalWords | 1268 | | ratio | 0.009 | | matches | | 0 | "Harl, they're not corpses, they're offerings." | | 1 | "unresolved" | | 2 | "don't" | | 3 | "foreign coin, one" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 18 | | unquotedAttributions | 0 | | matches | (empty) | |
| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 30 | | wordCount | 858 | | uniqueNames | 11 | | maxNameDensity | 1.28 | | worstName | "Vance" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Vance" | | discoveredNames | | Vance | 11 | | Old | 1 | | Quinn | 8 | | Deptford | 1 | | Ines | 1 | | Ferreira | 1 | | Morris | 2 | | Six | 1 | | Met | 1 | | Northern | 2 | | Macmillan | 1 |
| | persons | | 0 | "Vance" | | 1 | "Quinn" | | 2 | "Ines" | | 3 | "Ferreira" | | 4 | "Morris" | | 5 | "Met" |
| | places | | | globalScore | 0.859 | | windowScore | 0.833 | |
| 97.92% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1268 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 112 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 22.25 | | std | 21.26 | | cv | 0.956 | | sampleLengths | | 0 | 29 | | 1 | 39 | | 2 | 38 | | 3 | 3 | | 4 | 3 | | 5 | 3 | | 6 | 35 | | 7 | 55 | | 8 | 6 | | 9 | 10 | | 10 | 10 | | 11 | 5 | | 12 | 1 | | 13 | 6 | | 14 | 37 | | 15 | 6 | | 16 | 65 | | 17 | 18 | | 18 | 4 | | 19 | 49 | | 20 | 5 | | 21 | 21 | | 22 | 59 | | 23 | 7 | | 24 | 71 | | 25 | 1 | | 26 | 7 | | 27 | 49 | | 28 | 3 | | 29 | 37 | | 30 | 1 | | 31 | 26 | | 32 | 64 | | 33 | 13 | | 34 | 7 | | 35 | 6 | | 36 | 10 | | 37 | 49 | | 38 | 3 | | 39 | 10 | | 40 | 61 | | 41 | 4 | | 42 | 67 | | 43 | 7 | | 44 | 2 | | 45 | 2 | | 46 | 15 | | 47 | 26 | | 48 | 30 | | 49 | 45 |
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| 83.87% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 82 | | matches | | 0 | "been taught" | | 1 | "been found" | | 2 | "was gone" | | 3 | "was faced" | | 4 | "been sealed" | | 5 | "been taught" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 155 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 112 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 865 | | adjectiveStacks | 1 | | stackExamples | | 0 | "Fast, smooth, tireless, like" |
| | adverbCount | 27 | | adverbRatio | 0.03121387283236994 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.003468208092485549 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 112 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 112 | | mean | 11.32 | | std | 10.79 | | cv | 0.953 | | sampleLengths | | 0 | 29 | | 1 | 13 | | 2 | 26 | | 3 | 4 | | 4 | 9 | | 5 | 25 | | 6 | 3 | | 7 | 3 | | 8 | 3 | | 9 | 4 | | 10 | 5 | | 11 | 17 | | 12 | 9 | | 13 | 5 | | 14 | 23 | | 15 | 12 | | 16 | 15 | | 17 | 6 | | 18 | 10 | | 19 | 10 | | 20 | 5 | | 21 | 1 | | 22 | 6 | | 23 | 13 | | 24 | 24 | | 25 | 6 | | 26 | 47 | | 27 | 2 | | 28 | 10 | | 29 | 6 | | 30 | 3 | | 31 | 5 | | 32 | 9 | | 33 | 1 | | 34 | 4 | | 35 | 27 | | 36 | 22 | | 37 | 5 | | 38 | 8 | | 39 | 13 | | 40 | 17 | | 41 | 4 | | 42 | 11 | | 43 | 10 | | 44 | 2 | | 45 | 15 | | 46 | 2 | | 47 | 3 | | 48 | 2 | | 49 | 56 |
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| 94.94% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.5803571428571429 | | totalSentences | 112 | | uniqueOpeners | 65 | |
| 52.91% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 63 | | matches | | | ratio | 0.016 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 63 | | matches | | 0 | "He'd said it twice already," | | 1 | "His overshoes crackled on tile." | | 2 | "He was twenty-nine, keen as" | | 3 | "He came, reluctant, hunkering with" | | 4 | "She watched his face change," | | 5 | "She stood, knees clicking, and" | | 6 | "She let that settle" | | 7 | "She circled the body, keeping" | | 8 | "She held her own hand" | | 9 | "She heard how flat that" | | 10 | "She'd been ignoring it since" | | 11 | "He came round, gloved, and" | | 12 | "She held out an evidence" | | 13 | "She met his eyes and" | | 14 | "She turned back to the" | | 15 | "It weighed too much for" | | 16 | "It came round through a" |
| | ratio | 0.27 | |
| 86.98% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 63 | | matches | | 0 | "The body sat upright at" | | 1 | "Quinn crouched three feet from" | | 2 | "He'd said it twice already," | | 3 | "Vance shifted his weight." | | 4 | "His overshoes crackled on tile." | | 5 | "He was twenty-nine, keen as" | | 6 | "Quinn tilted her torch" | | 7 | "The beam skimmed the floor," | | 8 | "Dust lay across the tiles" | | 9 | "The only tracks in it" | | 10 | "None belonged to the dead" | | 11 | "He came, reluctant, hunkering with" | | 12 | "The buzz of the lamps" | | 13 | "She watched his face change," | | 14 | "She stood, knees clicking, and" | | 15 | "Vance leaned in." | | 16 | "The dead man wore brogues." | | 17 | "Brown, cracked across the vamp," | | 18 | "She let that settle" | | 19 | "Quinn allowed herself a fraction" |
| | ratio | 0.746 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 63 | | matches | (empty) | | ratio | 0 | |
| 73.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 31 | | technicalSentenceCount | 3 | | matches | | 0 | "The body sat upright at the foot of the dead escalator, hands folded in its lap like a commuter waiting for a train that had stopped running in 1962." | | 1 | "The beam skimmed the floor, low and flat, the way she'd been taught by a man who was no longer available for comment." | | 2 | "Palm-sized, the casing furred green with verdigris, the face cut about with tiny symbols that weren't degrees and weren't letters." |
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| 13.89% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 18 | | uselessAdditionCount | 4 | | matches | | 0 | "She stood, knees clicking, and rolled her shoulders once" | | 1 | "She held, a foot of air between palm and tile" | | 2 | "She held out, glad to be rid of it" | | 3 | "the tunnel took, and the dust came rolling out around it, and from inside the dark a voice she had buried three years ago said, quite clearly," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 8 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 48 | | tagDensity | 0.167 | | leniency | 0.333 | | rawRatio | 0.125 | | effectiveRatio | 0.042 | |