| 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 | 1314 | | 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) | |
| 69.56% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1314 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "flicker" | | 1 | "pulsed" | | 2 | "footfall" | | 3 | "echoed" | | 4 | "silence" | | 5 | "weight" | | 6 | "perfect" | | 7 | "throbbed" |
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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 | 123 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 123 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 162 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1324 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 16.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 50 | | wordCount | 974 | | uniqueNames | 12 | | maxNameDensity | 1.85 | | worstName | "Rory" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | September | 1 | | Rory | 18 | | Heartstone | 1 | | Cardiff | 1 | | Nyx | 8 | | Isolde | 5 | | Welsh | 1 | | Moss | 3 | | Light | 3 | | Cold | 5 | | Violet | 3 |
| | persons | | 0 | "Rory" | | 1 | "Heartstone" | | 2 | "Nyx" | | 3 | "Isolde" | | 4 | "Moss" | | 5 | "Light" | | 6 | "Cold" | | 7 | "Violet" |
| | places | | 0 | "Richmond" | | 1 | "September" | | 2 | "Cardiff" |
| | globalScore | 0.576 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 70 | | 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 | 1324 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 162 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 16.97 | | std | 17.35 | | cv | 1.022 | | sampleLengths | | 0 | 8 | | 1 | 56 | | 2 | 4 | | 3 | 35 | | 4 | 8 | | 5 | 45 | | 6 | 8 | | 7 | 11 | | 8 | 3 | | 9 | 9 | | 10 | 19 | | 11 | 13 | | 12 | 33 | | 13 | 4 | | 14 | 5 | | 15 | 12 | | 16 | 44 | | 17 | 2 | | 18 | 38 | | 19 | 3 | | 20 | 48 | | 21 | 5 | | 22 | 68 | | 23 | 1 | | 24 | 15 | | 25 | 3 | | 26 | 4 | | 27 | 66 | | 28 | 7 | | 29 | 19 | | 30 | 9 | | 31 | 14 | | 32 | 7 | | 33 | 1 | | 34 | 17 | | 35 | 2 | | 36 | 3 | | 37 | 19 | | 38 | 4 | | 39 | 23 | | 40 | 6 | | 41 | 31 | | 42 | 29 | | 43 | 1 | | 44 | 5 | | 45 | 54 | | 46 | 6 | | 47 | 15 | | 48 | 4 | | 49 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 123 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 184 | | matches | (empty) | |
| 1.76% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 8 | | totalSentences | 162 | | ratio | 0.049 | | matches | | 0 | "The odour hit — green sap, crushed petals, wet earth, honey thick enough to chew." | | 1 | "Birdsong layered wrong — nightingale phrase, then a trill no field guide held, then silence with teeth." | | 2 | "Flowers burned in drifts — white, gold, blood red." | | 3 | "Eyes opened, pale lavender, bright blue gone from Rory's sight for a second — Rory forgot her own blue, forgot black hair stuck to her neck, forgot everything but those eyes." | | 4 | "Rory checked — her own trainers left deep dents, Nyx left a smear like soot dragged by wind, Isolde left nothing." | | 5 | "Scent burst — blackberry, iron, frost." | | 6 | "Isolde crouched — no, hovered — beside a drift of primrose." | | 7 | "Somewhere left, hoofbeats crossed stone — three beats, stop, three beats — no deer showed." |
| |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 968 | | adjectiveStacks | 2 | | stackExamples | | 0 | "thumbnail-small, deep crimson" | | 1 | "Cool settled over her," |
| | adverbCount | 20 | | adverbRatio | 0.02066115702479339 | | lyAdverbCount | 0 | | lyAdverbRatio | 0 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 162 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 162 | | mean | 8.17 | | std | 6.06 | | cv | 0.741 | | sampleLengths | | 0 | 8 | | 1 | 17 | | 2 | 5 | | 3 | 17 | | 4 | 4 | | 5 | 5 | | 6 | 8 | | 7 | 4 | | 8 | 8 | | 9 | 2 | | 10 | 15 | | 11 | 9 | | 12 | 1 | | 13 | 8 | | 14 | 19 | | 15 | 8 | | 16 | 10 | | 17 | 8 | | 18 | 8 | | 19 | 9 | | 20 | 2 | | 21 | 3 | | 22 | 9 | | 23 | 4 | | 24 | 15 | | 25 | 13 | | 26 | 8 | | 27 | 15 | | 28 | 5 | | 29 | 5 | | 30 | 4 | | 31 | 5 | | 32 | 12 | | 33 | 3 | | 34 | 7 | | 35 | 4 | | 36 | 15 | | 37 | 15 | | 38 | 2 | | 39 | 2 | | 40 | 11 | | 41 | 17 | | 42 | 8 | | 43 | 3 | | 44 | 2 | | 45 | 5 | | 46 | 5 | | 47 | 19 | | 48 | 17 | | 49 | 5 |
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| 84.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 4 | | diversityRatio | 0.5217391304347826 | | totalSentences | 161 | | uniqueOpeners | 84 | |
| 91.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 109 | | matches | | 0 | "Somewhere beyond the ring a" | | 1 | "Somewhere left, hoofbeats crossed stone" | | 2 | "Somewhere right, a voice hummed" |
| | ratio | 0.028 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 109 | | matches | | 0 | "She swept her torch beam" | | 1 | "She stepped forward." | | 2 | "Her torch beam shortened, swallowed" | | 3 | "Her footfall made no crunch." | | 4 | "She glanced back." | | 5 | "Her mobile showed 21:47." | | 6 | "Her scar throbbed." | | 7 | "She knelt by a bramble" | | 8 | "She set edge to the" | | 9 | "Their reflection failed to appear." | | 10 | "She moved deeper." |
| | ratio | 0.101 | |
| 60.92% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 87 | | totalSentences | 109 | | matches | | 0 | "Rory ducked under the low" | | 1 | "The oaks rose ahead in" | | 2 | "Turf ended at the ring." | | 3 | "Moss took its place, thick" | | 4 | "Primrose brushed against foxglove." | | 5 | "Dog violet tangled with meadowsweet." | | 6 | "Colour rioted where leaf rot" | | 7 | "She swept her torch beam" | | 8 | "London hum died two steps" | | 9 | "A violet flicker lit the" | | 10 | "Nyx stood tall over her," | | 11 | "Edges bled when Rory stared" | | 12 | "Eyes burned in the hollow" | | 13 | "Each word came thin, wind" | | 14 | "Rory touched the crescent scar" | | 15 | "Nyx lifted a hand." | | 16 | "Shadow stretched too long for" | | 17 | "Rory pulled the chain from" | | 18 | "The Heartstone hung thumbnail-small, deep" | | 19 | "Skin under it stayed cool." |
| | ratio | 0.798 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 109 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 33 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 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 | |