| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2317 | | 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) | |
| 76.26% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2317 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "echo" | | 1 | "pulse" | | 2 | "silence" | | 3 | "trembled" | | 4 | "footsteps" | | 5 | "quickened" |
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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 | 283 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 283 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 330 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 40 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2316 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 82.05% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 62 | | wordCount | 2134 | | uniqueNames | 15 | | maxNameDensity | 1.36 | | worstName | "Rory" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Heartstone | 8 | | Rory | 29 | | Hel | 1 | | London | 1 | | Eva | 3 | | Cardiff | 2 | | Carter | 2 | | Aurora | 2 | | Christmas | 1 | | Mum | 1 | | Warm | 3 | | Bare | 3 | | One | 4 |
| | persons | | 0 | "Heartstone" | | 1 | "Rory" | | 2 | "Eva" | | 3 | "Carter" | | 4 | "Aurora" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Hel" | | 3 | "London" | | 4 | "Cardiff" | | 5 | "Mum" |
| | globalScore | 0.821 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 165 | | glossingSentenceCount | 1 | | matches | | 0 | "something like a cheek before the trunk hid" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.432 | | wordCount | 2316 | | matches | | 0 | "Not bright enough to cast light, but enough to stain her fingertips red" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 330 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 214 | | mean | 10.82 | | std | 10.8 | | cv | 0.998 | | sampleLengths | | 0 | 8 | | 1 | 43 | | 2 | 43 | | 3 | 7 | | 4 | 6 | | 5 | 21 | | 6 | 40 | | 7 | 14 | | 8 | 29 | | 9 | 30 | | 10 | 21 | | 11 | 3 | | 12 | 13 | | 13 | 4 | | 14 | 5 | | 15 | 40 | | 16 | 18 | | 17 | 29 | | 18 | 7 | | 19 | 2 | | 20 | 10 | | 21 | 12 | | 22 | 18 | | 23 | 2 | | 24 | 9 | | 25 | 2 | | 26 | 11 | | 27 | 3 | | 28 | 28 | | 29 | 39 | | 30 | 2 | | 31 | 9 | | 32 | 2 | | 33 | 7 | | 34 | 23 | | 35 | 3 | | 36 | 30 | | 37 | 11 | | 38 | 2 | | 39 | 2 | | 40 | 10 | | 41 | 4 | | 42 | 11 | | 43 | 19 | | 44 | 6 | | 45 | 18 | | 46 | 6 | | 47 | 4 | | 48 | 31 | | 49 | 2 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 283 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 356 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 1 | | flaggedSentences | 2 | | totalSentences | 330 | | ratio | 0.006 | | matches | | 0 | "Jennifer Carter’s exact laugh—one clipped breath through the nose, followed by the soft click in her throat that appeared whenever she found something funny but refused to reward it." | | 1 | "Her body wanted to run; every muscle offered a different direction." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 2138 | | adjectiveStacks | 1 | | stackExamples | | 0 | "revealing dull, milk-white orbs" |
| | adverbCount | 54 | | adverbRatio | 0.025257249766136577 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0018709073900841909 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 330 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 330 | | mean | 7.02 | | std | 5.25 | | cv | 0.749 | | sampleLengths | | 0 | 8 | | 1 | 17 | | 2 | 20 | | 3 | 2 | | 4 | 4 | | 5 | 10 | | 6 | 8 | | 7 | 11 | | 8 | 14 | | 9 | 7 | | 10 | 6 | | 11 | 7 | | 12 | 2 | | 13 | 2 | | 14 | 10 | | 15 | 16 | | 16 | 2 | | 17 | 10 | | 18 | 12 | | 19 | 14 | | 20 | 29 | | 21 | 6 | | 22 | 13 | | 23 | 11 | | 24 | 8 | | 25 | 13 | | 26 | 3 | | 27 | 8 | | 28 | 5 | | 29 | 4 | | 30 | 5 | | 31 | 20 | | 32 | 9 | | 33 | 11 | | 34 | 8 | | 35 | 10 | | 36 | 13 | | 37 | 2 | | 38 | 3 | | 39 | 11 | | 40 | 7 | | 41 | 2 | | 42 | 6 | | 43 | 4 | | 44 | 8 | | 45 | 4 | | 46 | 14 | | 47 | 4 | | 48 | 2 | | 49 | 9 |
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| 44.07% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 20 | | diversityRatio | 0.3009118541033435 | | totalSentences | 329 | | uniqueOpeners | 99 | |
| 81.97% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 244 | | matches | | 0 | "Even the drone of traffic" | | 1 | "Too fast to belong to" | | 2 | "Then a third to her" | | 3 | "Bright blue eyes caught the" | | 4 | "Even the thin silver watch" | | 5 | "Then Rory’s own voice whispered" |
| | ratio | 0.025 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 64 | | totalSentences | 244 | | matches | | 0 | "Their trunks rose thick and" | | 1 | "She tucked the phone into" | | 2 | "Her voice struck the ring" | | 3 | "She had come because of" | | 4 | "It had warmed during the" | | 5 | "She slipped two fingers beneath" | | 6 | "She stepped between them." | | 7 | "Their colours persisted under the" | | 8 | "She kept to the edge" | | 9 | "She pulled her phone out" | | 10 | "She stood still." | | 11 | "Her other hand found the" | | 12 | "Its beam cut across the" | | 13 | "She swept back." | | 14 | "They looked identical." | | 15 | "She could no longer tell" | | 16 | "She turned, arm raised." | | 17 | "Their bells hung open, black" | | 18 | "Her heartbeat kicked once, hard" | | 19 | "She lowered the beam by" |
| | ratio | 0.262 | |
| 64.51% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 193 | | totalSentences | 244 | | matches | | 0 | "The last oak stood where" | | 1 | "Aurora stopped beneath its stripped" | | 2 | "The blue location dot floated" | | 3 | "The time read 23:18." | | 4 | "Their trunks rose thick and" | | 5 | "None carried a leaf, though" | | 6 | "She tucked the phone into" | | 7 | "Her voice struck the ring" | | 8 | "She had come because of" | | 9 | "Rory had spent an hour" | | 10 | "The Heartstone rested beneath her" | | 11 | "It had warmed during the" | | 12 | "She slipped two fingers beneath" | | 13 | "The crimson stone glowed on" | | 14 | "A breeze slid across the" | | 15 | "The standing oaks remained still." | | 16 | "She stepped between them." | | 17 | "Wildflowers covered the clearing beyond" | | 18 | "Their colours persisted under the" | | 19 | "Dew jewelled every stem, though" |
| | ratio | 0.791 | |
| 20.49% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 244 | | matches | | | ratio | 0.004 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 80 | | technicalSentenceCount | 4 | | matches | | 0 | "Wildflowers covered the clearing beyond the boundary: foxgloves, bluebells, primroses, poppies, blooms from seasons that had no business sharing soil." | | 1 | "Nobody except Eva knew the name had ever belonged to her, and even Eva used it only when dragging up childhood punishments, summer dares and the private languag…" | | 2 | "Jennifer Carter’s exact laugh—one clipped breath through the nose, followed by the soft click in her throat that appeared whenever she found something funny but…" | | 3 | "It pressed both hands against empty air, its fingers flattening as if against glass." |
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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 | |