| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said quietly [quietly]" |
| | dialogueSentences | 8 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1061 | | 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) | |
| 43.45% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1061 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "silence" | | 1 | "pulse" | | 2 | "flickered" | | 3 | "pulsed" | | 4 | "measured" | | 5 | "shimmered" | | 6 | "echo" | | 7 | "weight" | | 8 | "could feel" |
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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 | 104 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 104 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 108 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 22 | | totalWords | 1061 | | ratio | 0.021 | | matches | | 0 | "Three oaks, then left at the lightning-split one. Listen for water that isn't there." | | 1 | "listen for water that isn't there" | | 2 | "Don't run" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 10 | | wordCount | 1034 | | uniqueNames | 9 | | maxNameDensity | 0.19 | | worstName | "Silas" | | maxWindowNameDensity | 0.5 | | worstWindowName | "Silas" | | discoveredNames | | Rory | 1 | | Robin | 1 | | Hood | 1 | | Gate | 1 | | Silas | 2 | | Richmond | 1 | | Park | 1 | | November | 1 | | Cardiff | 1 |
| | persons | | 0 | "Rory" | | 1 | "Robin" | | 2 | "Hood" | | 3 | "Gate" | | 4 | "Silas" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "November" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1061 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 108 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 24.67 | | std | 22.89 | | cv | 0.928 | | sampleLengths | | 0 | 11 | | 1 | 7 | | 2 | 49 | | 3 | 20 | | 4 | 18 | | 5 | 83 | | 6 | 3 | | 7 | 30 | | 8 | 4 | | 9 | 53 | | 10 | 7 | | 11 | 3 | | 12 | 62 | | 13 | 5 | | 14 | 25 | | 15 | 13 | | 16 | 30 | | 17 | 83 | | 18 | 3 | | 19 | 44 | | 20 | 7 | | 21 | 8 | | 22 | 60 | | 23 | 13 | | 24 | 6 | | 25 | 49 | | 26 | 8 | | 27 | 24 | | 28 | 13 | | 29 | 1 | | 30 | 63 | | 31 | 6 | | 32 | 35 | | 33 | 47 | | 34 | 17 | | 35 | 56 | | 36 | 2 | | 37 | 3 | | 38 | 30 | | 39 | 11 | | 40 | 34 | | 41 | 12 | | 42 | 3 |
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| 98.52% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 104 | | matches | | 0 | "was meant" | | 1 | "been dipped" |
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| 49.34% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 177 | | matches | | 0 | "wasn't laughing" | | 1 | "was happening" | | 2 | "was walking" | | 3 | "was burning" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 108 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1038 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 39 | | adverbRatio | 0.03757225433526012 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005780346820809248 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 108 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 108 | | mean | 9.82 | | std | 9.56 | | cv | 0.973 | | sampleLengths | | 0 | 11 | | 1 | 7 | | 2 | 25 | | 3 | 8 | | 4 | 12 | | 5 | 4 | | 6 | 10 | | 7 | 10 | | 8 | 13 | | 9 | 5 | | 10 | 23 | | 11 | 4 | | 12 | 32 | | 13 | 24 | | 14 | 3 | | 15 | 6 | | 16 | 4 | | 17 | 17 | | 18 | 2 | | 19 | 1 | | 20 | 4 | | 21 | 4 | | 22 | 24 | | 23 | 25 | | 24 | 4 | | 25 | 3 | | 26 | 3 | | 27 | 39 | | 28 | 23 | | 29 | 5 | | 30 | 2 | | 31 | 1 | | 32 | 18 | | 33 | 4 | | 34 | 13 | | 35 | 3 | | 36 | 1 | | 37 | 1 | | 38 | 23 | | 39 | 2 | | 40 | 24 | | 41 | 15 | | 42 | 6 | | 43 | 24 | | 44 | 9 | | 45 | 5 | | 46 | 3 | | 47 | 3 | | 48 | 1 | | 49 | 10 |
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| 74.38% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.46296296296296297 | | totalSentences | 108 | | uniqueOpeners | 50 | |
| 82.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 81 | | matches | | 0 | "Just the shimmer between two" | | 1 | "Properly burning, the kind of" |
| | ratio | 0.025 | |
| 96.54% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 25 | | totalSentences | 81 | | matches | | 0 | "She'd come in through the" | | 1 | "She wasn't laughing now." | | 2 | "she muttered, because her own" | | 3 | "She could hear traffic on" | | 4 | "She smacked the side of" | | 5 | "She clicked it off." | | 6 | "Her eyes took a long" | | 7 | "She moved forward." | | 8 | "Her boots found a path" | | 9 | "Her thumb hadn't moved." | | 10 | "she said quietly" | | 11 | "She passed one tree with" | | 12 | "She didn't mean to brush" | | 13 | "Her hand just did it." | | 14 | "She kept walking." | | 15 | "She stopped at the edge" | | 16 | "She hadn't stepped across the" | | 17 | "She rubbed it with her" | | 18 | "She turned her head." | | 19 | "She turned back." |
| | ratio | 0.309 | |
| 83.46% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 61 | | totalSentences | 81 | | matches | | 0 | "The torch beam swept across" | | 1 | "Something about the silence here" | | 2 | "She'd come in through the" | | 3 | "She wasn't laughing now." | | 4 | "The pendant at her throat" | | 5 | "she muttered, because her own" | | 6 | "Richmond Park after dark was" | | 7 | "This was something else." | | 8 | "The bracken had gone still" | | 9 | "She could hear traffic on" | | 10 | "The torch flickered." | | 11 | "She smacked the side of" | | 12 | "The beam steadied, then narrowed," | | 13 | "She clicked it off." | | 14 | "Her eyes took a long" | | 15 | "The pendant pulsed again." | | 16 | "She moved forward." | | 17 | "Her boots found a path" | | 18 | "A twig snapped behind her." | | 19 | "The torch came on without" |
| | ratio | 0.753 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 81 | | matches | (empty) | | ratio | 0 | |
| 46.33% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 5 | | matches | | 0 | "The bracken had gone still in a way that bracken didn't, not with the wind moving the way it was moving, pushing her fringe against her forehead but leaving the…" | | 1 | "She could hear traffic on the A3, faint, wrong-sided, as if the motorway had somehow slipped behind her when she knew it lay ahead." | | 2 | "There was a greenish cast to everything, low and sourceless, as if the grass itself had been dipped in something radioactive and left to dry." | | 3 | "Packed earth, narrow, winding between gorse bushes that leaned in from either side like people at a bus stop pretending not to listen." | | 4 | "A sweet smell came off them as they crushed, honey and rot and something older, something that reminded her, absurdly, of her grandmother's linen cupboard in Ca…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 25.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 8 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.25 | | effectiveRatio | 0.25 | |