| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1075 | | 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) | |
| 53.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1075 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "warmth" | | 1 | "pulse" | | 2 | "unsettled" | | 3 | "footsteps" | | 4 | "echo" | | 5 | "jaw clenched" | | 6 | "resolved" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "jaw/fists clenched" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 86 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 86 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 92 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1089 | | ratio | 0 | | matches | (empty) | |
| 83.33% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 1 | | matches | | 0 | "When she looked away, it breathed." |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 9 | | wordCount | 1063 | | uniqueNames | 8 | | maxNameDensity | 0.19 | | worstName | "November" | | maxWindowNameDensity | 0.5 | | worstWindowName | "November" | | discoveredNames | | Park | 1 | | Roehampton | 1 | | Barnes | 1 | | Heathrow | 1 | | Labradors | 1 | | November | 2 | | Silas | 1 | | Evan | 1 |
| | persons | | | places | | 0 | "Park" | | 1 | "Roehampton" | | 2 | "November" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 58 | | 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 | 1089 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 33 | | std | 25.99 | | cv | 0.788 | | sampleLengths | | 0 | 42 | | 1 | 15 | | 2 | 79 | | 3 | 41 | | 4 | 79 | | 5 | 6 | | 6 | 46 | | 7 | 6 | | 8 | 50 | | 9 | 40 | | 10 | 48 | | 11 | 96 | | 12 | 22 | | 13 | 65 | | 14 | 29 | | 15 | 1 | | 16 | 7 | | 17 | 14 | | 18 | 28 | | 19 | 12 | | 20 | 1 | | 21 | 52 | | 22 | 19 | | 23 | 79 | | 24 | 30 | | 25 | 25 | | 26 | 17 | | 27 | 9 | | 28 | 66 | | 29 | 40 | | 30 | 19 | | 31 | 1 | | 32 | 5 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 86 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 170 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 14 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 92 | | ratio | 0.12 | | matches | | 0 | "She went over the gate the way she used to go over the fence of the lido as a kid — one foot on the crossbar, up, drop." | | 1 | "Even here, a mile from the nearest lit window, the city laid a hum beneath everything — the A3, aircraft stacking for Heathrow, the bark of a fox working the verges." | | 2 | "Richmond deer tolerated everything — joggers, drones, off-lead Labradors." | | 3 | "She glanced down at the pendant — half a second, no more — and when the beam came up again the treeline stood empty." | | 4 | "And she stepped into a clearing her head had no map for — she had cycled this park's perimeter a hundred times, she knew its gates and its ponds the way she knew the delivery grid, and there was no clearing here." | | 5 | "Wildflowers crowded the circle's floor — campion, cow parsley, things with white faces she had no names for — blooming in November, weeks after the frost should have taken them." | | 6 | "The smell of high summer — cut grass, and beneath it something sweeter, fruit gone soft in the sun." | | 7 | "Grass-hush, grass-hush — and beneath each, a half-beat late, grass-hush." | | 8 | "She stood in the warm summer air with her jaw clenched and listened to the list in her head — echo, wind, tiredness, the blood in her own ears — and crossed each one off as it failed." | | 9 | "But at the edge of her vision the ring moved — the gaps between the stones widening and closing, slow as gills working." | | 10 | "Crimson light bled through her shirt and threw the clearing red — and in that light she saw the flowers." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1056 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.026515151515151516 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.002840909090909091 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 92 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 92 | | mean | 11.84 | | std | 10.34 | | cv | 0.874 | | sampleLengths | | 0 | 7 | | 1 | 3 | | 2 | 32 | | 3 | 7 | | 4 | 8 | | 5 | 9 | | 6 | 22 | | 7 | 22 | | 8 | 26 | | 9 | 28 | | 10 | 5 | | 11 | 8 | | 12 | 8 | | 13 | 4 | | 14 | 31 | | 15 | 6 | | 16 | 30 | | 17 | 3 | | 18 | 3 | | 19 | 15 | | 20 | 9 | | 21 | 18 | | 22 | 2 | | 23 | 2 | | 24 | 6 | | 25 | 24 | | 26 | 2 | | 27 | 7 | | 28 | 17 | | 29 | 40 | | 30 | 3 | | 31 | 3 | | 32 | 42 | | 33 | 27 | | 34 | 2 | | 35 | 11 | | 36 | 12 | | 37 | 30 | | 38 | 3 | | 39 | 2 | | 40 | 9 | | 41 | 22 | | 42 | 11 | | 43 | 1 | | 44 | 19 | | 45 | 4 | | 46 | 30 | | 47 | 4 | | 48 | 2 | | 49 | 23 |
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| 66.30% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.45054945054945056 | | totalSentences | 91 | | uniqueOpeners | 41 | |
| 91.32% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 73 | | matches | | 0 | "Then her footsteps began to" | | 1 | "Then a fourth." |
| | ratio | 0.027 | |
| 99.45% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 22 | | totalSentences | 73 | | matches | | 0 | "she told the empty road" | | 1 | "She went over the gate" | | 2 | "She thumbed on her phone" | | 3 | "Her torch cut a tunnel" | | 4 | "She let it." | | 5 | "She found the deer at" | | 6 | "She glanced down at the" | | 7 | "She filed it under things" | | 8 | "She rubbed the crescent scar" | | 9 | "Her breath stopped pluming." | | 10 | "Her phone read 23:47." | | 11 | "She walked the ring's inside" | | 12 | "Her voice came back flat," | | 13 | "She took three quick steps" | | 14 | "She stood in the warm" | | 15 | "She refused to look at" | | 16 | "Her eyes ached from not" | | 17 | "She hummed to keep herself" | | 18 | "Her hands had gone steady," | | 19 | "She turned for the gap" |
| | ratio | 0.301 | |
| 69.59% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 73 | | matches | | 0 | "Richmond Park shut its gates" | | 1 | "Rory knew this." | | 2 | "The knowing sat under her" | | 3 | "she told the empty road" | | 4 | "The pendant had worn a" | | 5 | "Tonight, riding back from a" | | 6 | "She went over the gate" | | 7 | "She thumbed on her phone" | | 8 | "The wrongness found her before" | | 9 | "London never went quiet." | | 10 | "Tonight the park gave back" | | 11 | "Her torch cut a tunnel" | | 12 | "The pendant led." | | 13 | "She let it." | | 14 | "She found the deer at" | | 15 | "Richmond deer tolerated everything —" | | 16 | "These stood with their heads" | | 17 | "She glanced down at the" | | 18 | "A dozen animals, gone without" | | 19 | "She filed it under things" |
| | ratio | 0.781 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 73 | | matches | | 0 | "By the time she reached" | | 1 | "Even here, a mile from" |
| | ratio | 0.027 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 36 | | technicalSentenceCount | 2 | | matches | | 0 | "Her torch cut a tunnel through the dark and the dark closed behind it, seamless, as if the beam were the only thing keeping the world unrolled ahead of her." | | 1 | "The pendant's burn eased into a low, contented heat, the purr of a cat that has got what it wanted, and that unsettled her more than the burning ever had." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 9 | | tagDensity | 0.222 | | leniency | 0.444 | | rawRatio | 0 | | effectiveRatio | 0 | |