| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 4 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1654 | | 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) | |
| 66.75% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1654 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "pulsed" | | 3 | "footsteps" | | 4 | "measured" | | 5 | "familiar" | | 6 | "sense of" | | 7 | "pulse" | | 8 | "vibrated" |
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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 | 201 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 201 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 211 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 26 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1654 | | ratio | 0 | | matches | (empty) | |
| 83.33% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 1 | | matches | | 0 | "From somewhere between the trees, Eva called her name." |
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| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 53 | | wordCount | 1611 | | uniqueNames | 9 | | maxNameDensity | 2.05 | | worstName | "Rory" | | maxWindowNameDensity | 4 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 33 | | Richmond | 2 | | Park | 2 | | Eva | 9 | | Fae-touched | 1 | | Evan | 1 | | Cardiff | 1 | | London | 1 | | One | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Evan" | | 3 | "One" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 0.476 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 123 | | glossingSentenceCount | 2 | | matches | | 0 | "as if naming it settled the matter" | | 1 | "sounded like Eva" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1654 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 211 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 103 | | mean | 16.06 | | std | 13.43 | | cv | 0.836 | | sampleLengths | | 0 | 9 | | 1 | 49 | | 2 | 15 | | 3 | 14 | | 4 | 20 | | 5 | 10 | | 6 | 32 | | 7 | 41 | | 8 | 24 | | 9 | 8 | | 10 | 32 | | 11 | 10 | | 12 | 3 | | 13 | 66 | | 14 | 11 | | 15 | 27 | | 16 | 5 | | 17 | 5 | | 18 | 24 | | 19 | 1 | | 20 | 14 | | 21 | 54 | | 22 | 14 | | 23 | 38 | | 24 | 13 | | 25 | 14 | | 26 | 22 | | 27 | 5 | | 28 | 21 | | 29 | 43 | | 30 | 14 | | 31 | 9 | | 32 | 29 | | 33 | 3 | | 34 | 27 | | 35 | 6 | | 36 | 9 | | 37 | 14 | | 38 | 2 | | 39 | 9 | | 40 | 12 | | 41 | 10 | | 42 | 29 | | 43 | 3 | | 44 | 39 | | 45 | 2 | | 46 | 3 | | 47 | 13 | | 48 | 36 | | 49 | 1 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 201 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 268 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 211 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1615 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 46 | | adverbRatio | 0.02848297213622291 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.002476780185758514 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 211 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 211 | | mean | 7.84 | | std | 5.12 | | cv | 0.653 | | sampleLengths | | 0 | 9 | | 1 | 16 | | 2 | 8 | | 3 | 6 | | 4 | 19 | | 5 | 5 | | 6 | 2 | | 7 | 8 | | 8 | 12 | | 9 | 1 | | 10 | 1 | | 11 | 4 | | 12 | 4 | | 13 | 12 | | 14 | 10 | | 15 | 20 | | 16 | 12 | | 17 | 8 | | 18 | 19 | | 19 | 14 | | 20 | 6 | | 21 | 9 | | 22 | 9 | | 23 | 8 | | 24 | 2 | | 25 | 4 | | 26 | 18 | | 27 | 8 | | 28 | 10 | | 29 | 3 | | 30 | 17 | | 31 | 17 | | 32 | 4 | | 33 | 2 | | 34 | 26 | | 35 | 11 | | 36 | 3 | | 37 | 5 | | 38 | 2 | | 39 | 17 | | 40 | 5 | | 41 | 5 | | 42 | 2 | | 43 | 18 | | 44 | 4 | | 45 | 1 | | 46 | 9 | | 47 | 5 | | 48 | 5 | | 49 | 26 |
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| 42.42% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.22748815165876776 | | totalSentences | 211 | | uniqueOpeners | 48 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 8 | | totalSentences | 184 | | matches | | 0 | "Then the same bark came" | | 1 | "Only the wind answered, stirring" | | 2 | "Once, at the edge of" | | 3 | "Instead, Rory felt the silence" | | 4 | "Then the figure tilted its" | | 5 | "Just enough to make the" | | 6 | "Then it dropped." | | 7 | "Only a hollow where one" |
| | ratio | 0.043 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 184 | | matches | | 0 | "She stopped beneath the iron" | | 1 | "She looked at her phone." | | 2 | "She’d sent the message an" | | 3 | "She rubbed it once with" | | 4 | "She had the pendant in" | | 5 | "Its silver chain had knotted" | | 6 | "Their branches knitted overhead, blotting" | | 7 | "she said, as if naming" | | 8 | "She kept walking." | | 9 | "She chose the left path." | | 10 | "She faced the trees." | | 11 | "She watched the path and" | | 12 | "She knew because a strip" | | 13 | "She’d noticed it on the" | | 14 | "She stared at the display," | | 15 | "Its crimson surface caught a" | | 16 | "They nodded in a wind" | | 17 | "She set her delivery bag" | | 18 | "She felt it in her" | | 19 | "She backed away from the" |
| | ratio | 0.299 | |
| 60.54% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 147 | | totalSentences | 184 | | matches | | 0 | "The gate stood open when" | | 1 | "She stopped beneath the iron" | | 2 | "The park had gone quiet" | | 3 | "She looked at her phone." | | 4 | "The message from Eva sat" | | 5 | "Rory had called twice." | | 6 | "Eva hadn’t picked up." | | 7 | "She’d sent the message an" | | 8 | "The phone’s light showed a" | | 9 | "She rubbed it once with" | | 10 | "She had the pendant in" | | 11 | "Its silver chain had knotted" | | 12 | "The park path sloped between" | | 13 | "Their branches knitted overhead, blotting" | | 14 | "Rory heard a fox bark" | | 15 | "The path lay empty." | | 16 | "A line of lamps had" | | 17 | "she said, as if naming" | | 18 | "She kept walking." | | 19 | "Eva had once told her" |
| | ratio | 0.799 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 5 | | totalSentences | 184 | | matches | | 0 | "If you still have the" | | 1 | "Now the little crimson stone" | | 2 | "Now Eva had sent her" | | 3 | "Now the tape hung in" | | 4 | "Now a wall of roots" |
| | ratio | 0.027 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 57 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 4 | | uselessAdditionCount | 1 | | matches | | 0 | "she said, as if naming it settled the matter" |
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| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Rory murmured (murmur)" | | 1 | "Rory whispered (whisper)" |
| | dialogueSentences | 14 | | tagDensity | 0.286 | | leniency | 0.571 | | rawRatio | 0.5 | | effectiveRatio | 0.286 | |