| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said aloud [aloud]" |
| | dialogueSentences | 10 | | tagDensity | 0.5 | | leniency | 1 | | rawRatio | 0.2 | | effectiveRatio | 0.2 | |
| 87.09% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1162 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | adverb | "reluctantly" | | count | 1 |
| | 2 | |
| | highlights | | 0 | "slowly" | | 1 | "reluctantly" | | 2 | "perfectly" |
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| 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) | |
| 56.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1162 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "footsteps" | | 1 | "pulsed" | | 2 | "throbbed" | | 3 | "silence" | | 4 | "echo" | | 5 | "perfect" | | 6 | "pulse" | | 7 | "flickered" | | 8 | "stomach" |
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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 | 128 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 128 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 133 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 28 | | totalWords | 1162 | | ratio | 0.024 | | matches | | 0 | "RICHMOND PARK, OAK STONES, LEAVE INSIDE THE CIRCLE." | | 1 | "Twenty quid for a stroll," | | 2 | "Don't be precious." | | 3 | "Sound bouncing off the stones. Acoustics." | | 4 | "That's all it is." | | 5 | "Suo Gân." |
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| 97.22% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 1 | | matches | | 0 | "The stones were not moving, she told herself, they were standing perfectly still, but each time she looked away and back…" |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 1125 | | uniqueNames | 9 | | maxNameDensity | 0.71 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Yu-Fei" | | discoveredNames | | Chinatown | 1 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 2 | | Heartstone | 2 | | Welsh | 1 | | Rory | 8 | | Cardiff | 2 | | Six | 3 |
| | persons | | | places | | 0 | "Chinatown" | | 1 | "Yu-Fei" | | 2 | "Welsh" | | 3 | "Cardiff" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 73 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.861 | | wordCount | 1162 | | matches | | 0 | "not moving, she told herself, they were standing perfectly still, but each time she looked away" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 133 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 23.24 | | std | 21.79 | | cv | 0.938 | | sampleLengths | | 0 | 5 | | 1 | 47 | | 2 | 22 | | 3 | 1 | | 4 | 53 | | 5 | 11 | | 6 | 3 | | 7 | 90 | | 8 | 14 | | 9 | 13 | | 10 | 32 | | 11 | 3 | | 12 | 51 | | 13 | 21 | | 14 | 8 | | 15 | 5 | | 16 | 25 | | 17 | 2 | | 18 | 36 | | 19 | 12 | | 20 | 24 | | 21 | 43 | | 22 | 27 | | 23 | 2 | | 24 | 37 | | 25 | 6 | | 26 | 8 | | 27 | 70 | | 28 | 4 | | 29 | 32 | | 30 | 8 | | 31 | 6 | | 32 | 59 | | 33 | 2 | | 34 | 5 | | 35 | 45 | | 36 | 3 | | 37 | 17 | | 38 | 2 | | 39 | 72 | | 40 | 10 | | 41 | 38 | | 42 | 25 | | 43 | 4 | | 44 | 63 | | 45 | 10 | | 46 | 41 | | 47 | 22 | | 48 | 15 | | 49 | 8 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 128 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 184 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 133 | | ratio | 0 | | matches | (empty) | |
| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1131 | | adjectiveStacks | 1 | | stackExamples | | 0 | "warm pressed against her" |
| | adverbCount | 42 | | adverbRatio | 0.03713527851458886 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005305039787798408 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 133 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 133 | | mean | 8.74 | | std | 7.1 | | cv | 0.813 | | sampleLengths | | 0 | 5 | | 1 | 7 | | 2 | 29 | | 3 | 11 | | 4 | 3 | | 5 | 15 | | 6 | 4 | | 7 | 1 | | 8 | 4 | | 9 | 32 | | 10 | 2 | | 11 | 15 | | 12 | 8 | | 13 | 3 | | 14 | 3 | | 15 | 17 | | 16 | 4 | | 17 | 22 | | 18 | 7 | | 19 | 14 | | 20 | 4 | | 21 | 22 | | 22 | 8 | | 23 | 6 | | 24 | 5 | | 25 | 8 | | 26 | 8 | | 27 | 16 | | 28 | 1 | | 29 | 7 | | 30 | 3 | | 31 | 6 | | 32 | 27 | | 33 | 6 | | 34 | 12 | | 35 | 7 | | 36 | 14 | | 37 | 8 | | 38 | 5 | | 39 | 10 | | 40 | 4 | | 41 | 11 | | 42 | 2 | | 43 | 1 | | 44 | 11 | | 45 | 12 | | 46 | 10 | | 47 | 2 | | 48 | 4 | | 49 | 8 |
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| 60.65% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.41353383458646614 | | totalSentences | 133 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 105 | | matches | | 0 | "Then came the stones." | | 1 | "Just one, soft and deliberate," | | 2 | "Even the insects had gone" | | 3 | "Somewhere behind her, in perfect" | | 4 | "Then the smell changed." |
| | ratio | 0.048 | |
| 86.67% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 105 | | matches | | 0 | "Her voice fell flat, as" | | 1 | "She checked her phone." | | 2 | "She kept walking." | | 3 | "They were oak, she realised," | | 4 | "Her breath, meanwhile, did not" | | 5 | "She pulled the chain from" | | 6 | "It had never done that" | | 7 | "She'd worn it out of" | | 8 | "She tucked it back under" | | 9 | "Her hand shook, and she" | | 10 | "She stepped across the ring." | | 11 | "She turned her head slowly," | | 12 | "She took another step." | | 13 | "She walked to the centre," | | 14 | "She lowered the phone and" | | 15 | "It had shoulders." | | 16 | "She lowered the phone again." | | 17 | "she said aloud" | | 18 | "Her voice sounded thin." | | 19 | "She backed toward the boundary," |
| | ratio | 0.333 | |
| 74.29% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 81 | | totalSentences | 105 | | matches | | 0 | "The bag was still hot." | | 1 | "Rory noticed it halfway across" | | 2 | "The sweet and sour should" | | 3 | "Her voice fell flat, as" | | 4 | "She checked her phone." | | 5 | "The screen showed the address" | | 6 | "She kept walking." | | 7 | "The path had ended without" | | 8 | "They were oak, she realised," | | 9 | "Wildflowers crowded their bases." | | 10 | "Foxgloves, poppies, bluebells, all open" | | 11 | "The air smelled of cut" | | 12 | "Her breath, meanwhile, did not" | | 13 | "Rory stopped at the boundary." | | 14 | "Something small and warm pressed" | | 15 | "She pulled the chain from" | | 16 | "The Heartstone lay in her" | | 17 | "A slow beat, like a" | | 18 | "It had never done that" | | 19 | "The unknown benefactor who'd posted" |
| | ratio | 0.771 | |
| 47.62% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 105 | | matches | | 0 | "Now it throbbed against her" |
| | ratio | 0.01 | |
| 43.19% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 6 | | matches | | 0 | "The screen showed the address in Yu-Fei's careful capitals: *RICHMOND PARK, OAK STONES, LEAVE INSIDE THE CIRCLE.* Below it, paid in full, a tip that made her ch…" | | 1 | "The path had ended without ceremony, the gravel giving way to soft turf that swallowed her footsteps." | | 2 | "Foxgloves, poppies, bluebells, all open together, all at the wrong season, all pale silver in a light that had no obvious source." | | 3 | "The unknown benefactor who'd posted it to her flat had included no note, no instructions, only a jeweller's box and a dead moth pressed inside the lid." | | 4 | "The paper lay folded back in neat, careful creases, and the foil lids of the containers were peeled away, one after another, as though by fingers." | | 5 | "Rory clawed at the chain, and the silver snapped, and the pendant dropped into her palm, throbbing, crimson light spilling between her fingers and staining the …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0 | | effectiveRatio | 0 | |