| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 77.13% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1093 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "completely" | | 1 | "slightly" | | 2 | "very" | | 3 | "slowly" |
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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) | |
| 54.25% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1093 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "pulsed" | | 1 | "warmth" | | 2 | "pulse" | | 3 | "silence" | | 4 | "resolved" | | 5 | "throb" |
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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 | 82 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1102 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 1 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 13 | | wordCount | 1102 | | uniqueNames | 7 | | maxNameDensity | 0.45 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Park | 1 | | London | 1 | | Rory | 5 | | Aurora | 1 | | Eva | 1 | | Heartstone | 1 | | Seven | 3 |
| | persons | | | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 54 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 18.51% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.815 | | wordCount | 1102 | | matches | | 0 | "not as Rory, not even as Aurora, but as a third name she'd only recently learned belonged to her" | | 1 | "not even as Aurora, but as a third name she'd only recently learned belonged to her" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 82 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 33.39 | | std | 30.27 | | cv | 0.906 | | sampleLengths | | 0 | 8 | | 1 | 54 | | 2 | 123 | | 3 | 11 | | 4 | 82 | | 5 | 10 | | 6 | 102 | | 7 | 5 | | 8 | 63 | | 9 | 15 | | 10 | 44 | | 11 | 7 | | 12 | 3 | | 13 | 50 | | 14 | 49 | | 15 | 3 | | 16 | 19 | | 17 | 30 | | 18 | 23 | | 19 | 37 | | 20 | 5 | | 21 | 51 | | 22 | 27 | | 23 | 5 | | 24 | 64 | | 25 | 46 | | 26 | 6 | | 27 | 28 | | 28 | 5 | | 29 | 66 | | 30 | 2 | | 31 | 10 | | 32 | 49 |
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| 88.15% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 82 | | matches | | 0 | "been given" | | 1 | "been slipped" | | 2 | "was gone" | | 3 | "was gone" |
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| 0.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 5 | | totalVerbs | 162 | | matches | | 0 | "was sliding" | | 1 | "were blooming" | | 2 | "were pointing" | | 3 | "were pointing" | | 4 | "was carrying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 82 | | ratio | 0.085 | | matches | | 0 | "Not hidden — absent." | | 1 | "A person could walk the park a hundred times and never find the hollow — she was certain of that, because Eva had tried twice before she'd succeeded." | | 2 | "Full, open blooms — dog violet, red campion, something pale and cup-shaped she couldn't name — spread across the ground inside the circle of stones and beyond them, into the clearing proper." | | 3 | "It wasn't silence exactly — the wind still moved through the high canopy, still pressed against the back of her neck — but all the ambient texture of the park outside dropped away, and what replaced it was a quality of listening." | | 4 | "It took three or four seconds for her eyes to begin adjusting, and in that interval the darkness was total and pressing and she became acutely aware of her own breathing — too loud, too regular, a metronome announcing position." | | 5 | "Not unpleasant — that was the wrongness of it." | | 6 | "There had been eight when she entered — she was certain of it, as certain as she was of the cold or the flower smell on her hands." |
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| 92.34% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1098 | | adjectiveStacks | 1 | | stackExamples | | 0 | "faint, half-imagined warmth" |
| | adverbCount | 46 | | adverbRatio | 0.04189435336976321 | | lyAdverbCount | 20 | | lyAdverbRatio | 0.018214936247723135 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 82 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 82 | | mean | 13.44 | | std | 11.89 | | cv | 0.885 | | sampleLengths | | 0 | 8 | | 1 | 31 | | 2 | 23 | | 3 | 6 | | 4 | 27 | | 5 | 5 | | 6 | 4 | | 7 | 41 | | 8 | 19 | | 9 | 21 | | 10 | 5 | | 11 | 6 | | 12 | 29 | | 13 | 4 | | 14 | 4 | | 15 | 33 | | 16 | 12 | | 17 | 10 | | 18 | 27 | | 19 | 28 | | 20 | 47 | | 21 | 5 | | 22 | 4 | | 23 | 32 | | 24 | 1 | | 25 | 9 | | 26 | 17 | | 27 | 15 | | 28 | 9 | | 29 | 18 | | 30 | 11 | | 31 | 6 | | 32 | 7 | | 33 | 3 | | 34 | 42 | | 35 | 5 | | 36 | 3 | | 37 | 8 | | 38 | 6 | | 39 | 10 | | 40 | 6 | | 41 | 19 | | 42 | 3 | | 43 | 7 | | 44 | 12 | | 45 | 3 | | 46 | 27 | | 47 | 13 | | 48 | 10 | | 49 | 2 |
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| 54.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.3780487804878049 | | totalSentences | 82 | | uniqueOpeners | 31 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 76 | | matches | | 0 | "Then a third time in" | | 1 | "Still silent in that attentive" | | 2 | "Then she turned." |
| | ratio | 0.039 | |
| 67.37% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 76 | | matches | | 0 | "She'd been given a note." | | 1 | "It had been slipped under" | | 2 | "It named the grove." | | 3 | "It named a time." | | 4 | "It named her, not as" | | 5 | "She stopped at the boundary." | | 6 | "She pressed her hand flat" | | 7 | "She stepped between two of" | | 8 | "It wasn't silence exactly —" | | 9 | "It paid attention." | | 10 | "It didn't move." | | 11 | "She watched it for a" | | 12 | "It didn't move, didn't twitch" | | 13 | "She looked away." | | 14 | "She stood very still and" | | 15 | "They were pointing at the" | | 16 | "Her torchlight didn't reach far" | | 17 | "She turned off the torch." | | 18 | "It took three or four" | | 19 | "She slowed it." |
| | ratio | 0.382 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 76 | | matches | | 0 | "Richmond Park after midnight was" | | 1 | "Rory had read that once," | | 2 | "The deer were the first" | | 3 | "The park held roughly six" | | 4 | "The park breathed and held" | | 5 | "She'd been given a note." | | 6 | "That was why she was" | | 7 | "It had been slipped under" | | 8 | "It named the grove." | | 9 | "It named a time." | | 10 | "It named her, not as" | | 11 | "Someone who knew that name" | | 12 | "The standing stones were easier" | | 13 | "The grove sat in a" | | 14 | "A person could walk the" | | 15 | "She stopped at the boundary." | | 16 | "The wildflowers were blooming." | | 17 | "The flowers didn't know that," | | 18 | "The Heartstone pendant sat against" | | 19 | "A full, deliberate pulse, like" |
| | ratio | 0.75 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | 0 | "Now she walked the outer" |
| | ratio | 0.013 | |
| 69.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 39 | | technicalSentenceCount | 4 | | matches | | 0 | "It had been slipped under the door of her flat three days ago, written on paper that felt heavier than paper should, in ink the colour of old tea." | | 1 | "But tonight the path opened ahead of Rory as though it had been waiting, and the eight stones rose from the grass in a rough circle, each one oak, each one olde…" | | 2 | "A full, deliberate pulse, like a second heartbeat that had fallen slightly out of sync with her own." | | 3 | "She counted again, taking her time, pointing at each in sequence." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |