| 88.89% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 1 | | adverbTags | | 0 | "She clapped once [once]" |
| | dialogueSentences | 18 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.125 | | effectiveRatio | 0.111 | |
| 92.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1342 | | totalAiIsmAdverbs | 2 | | found | | | highlights | | |
| 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) | |
| 70.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1342 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "echo" | | 1 | "pulse" | | 2 | "pulsed" | | 3 | "stomach" | | 4 | "absolutely" | | 5 | "silence" |
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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 | 97 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 97 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 105 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 8 | | totalWords | 1357 | | ratio | 0.006 | | matches | | 0 | "go home, get the bus, ring Silas" | | 1 | "cariad" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 13 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1260 | | uniqueNames | 16 | | maxNameDensity | 0.56 | | worstName | "Rory" | | maxWindowNameDensity | 1 | | worstWindowName | "Rory" | | discoveredNames | | Sheen | 1 | | Cross | 1 | | Rory | 7 | | Park | 1 | | Kingston | 1 | | Sawyer | 1 | | Hill | 1 | | September | 1 | | Eva | 1 | | Cardiff | 1 | | January | 1 | | Richmond | 2 | | Jennifer | 1 | | Carter | 1 | | Bridgend | 1 | | Two | 1 |
| | persons | | 0 | "Cross" | | 1 | "Rory" | | 2 | "Sawyer" | | 3 | "Eva" | | 4 | "Jennifer" | | 5 | "Carter" |
| | places | | 0 | "Sheen" | | 1 | "Park" | | 2 | "Kingston" | | 3 | "September" | | 4 | "Cardiff" | | 5 | "January" | | 6 | "Richmond" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 55 | | 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 | 1357 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 105 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 47 | | mean | 28.87 | | std | 24.27 | | cv | 0.841 | | sampleLengths | | 0 | 33 | | 1 | 85 | | 2 | 23 | | 3 | 36 | | 4 | 9 | | 5 | 57 | | 6 | 3 | | 7 | 89 | | 8 | 6 | | 9 | 23 | | 10 | 18 | | 11 | 71 | | 12 | 21 | | 13 | 17 | | 14 | 3 | | 15 | 53 | | 16 | 41 | | 17 | 4 | | 18 | 68 | | 19 | 20 | | 20 | 7 | | 21 | 9 | | 22 | 54 | | 23 | 7 | | 24 | 54 | | 25 | 37 | | 26 | 18 | | 27 | 7 | | 28 | 6 | | 29 | 54 | | 30 | 46 | | 31 | 3 | | 32 | 3 | | 33 | 17 | | 34 | 58 | | 35 | 42 | | 36 | 27 | | 37 | 4 | | 38 | 6 | | 39 | 15 | | 40 | 7 | | 41 | 67 | | 42 | 11 | | 43 | 62 | | 44 | 36 | | 45 | 8 | | 46 | 12 |
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| 94.41% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 97 | | matches | | 0 | "been chained" | | 1 | "was headed" | | 2 | "was gone" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 209 | | matches | | 0 | "was eating" | | 1 | "was looking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 2 | | flaggedSentences | 9 | | totalSentences | 105 | | ratio | 0.086 | | matches | | 0 | "The dark had swallowed the paths and put something else in their place — long grey slopes, black stands of oak, the far-off orange bruise of Kingston glowing over the treeline like a fire someone had forgotten to put out." | | 1 | "That was the first thing that struck her as wrong, and she couldn't say why for a good thirty seconds — then she got it." | | 2 | "They were all facing the same direction — northwest, toward the trees she was headed for — with the stiff, cocked attention of dogs at a door." | | 3 | "She stood in the hawthorn for a long moment, and the honest part of her brain said *go home, get the bus, ring Silas*, and the other part — the part that had got her out of Cardiff with two bags and a train ticket — pushed the branches aside and stepped through." | | 4 | "Of course they were; they always were." | | 5 | "The gap she'd come through had closed itself into a solid wall of thorn — no, that was panic, that was her eyes; she found the gap two feet left of where she'd thought it was, a black ragged mouth in the hedge." | | 6 | "It came from underneath — under the flowers, under the soil — and it was so ordinary that her stomach turned over." | | 7 | "She got up too fast and her heel caught and she went down on one hand into the flowers, and something under the petals gave beneath her palm — dry, jointed, hollow — and she snatched her hand back and did not look, absolutely refused to look, and stood up with her fist closed tight." | | 8 | "Rory reached up and closed her hand around the crimson stone, and felt it pulse, and behind her — close, close enough that the hair moved on the back of her neck — something breathed out." |
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| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1253 | | adjectiveStacks | 2 | | stackExamples | | 0 | "far-off orange bruise" | | 1 | "great many small things" |
| | adverbCount | 34 | | adverbRatio | 0.02713487629688747 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.0031923383878691143 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 105 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 105 | | mean | 12.92 | | std | 12.96 | | cv | 1.003 | | sampleLengths | | 0 | 33 | | 1 | 17 | | 2 | 28 | | 3 | 40 | | 4 | 4 | | 5 | 19 | | 6 | 7 | | 7 | 2 | | 8 | 27 | | 9 | 3 | | 10 | 6 | | 11 | 4 | | 12 | 25 | | 13 | 2 | | 14 | 2 | | 15 | 24 | | 16 | 3 | | 17 | 6 | | 18 | 24 | | 19 | 3 | | 20 | 29 | | 21 | 27 | | 22 | 4 | | 23 | 2 | | 24 | 2 | | 25 | 8 | | 26 | 13 | | 27 | 18 | | 28 | 14 | | 29 | 6 | | 30 | 34 | | 31 | 17 | | 32 | 3 | | 33 | 18 | | 34 | 9 | | 35 | 8 | | 36 | 3 | | 37 | 53 | | 38 | 7 | | 39 | 7 | | 40 | 27 | | 41 | 4 | | 42 | 5 | | 43 | 26 | | 44 | 37 | | 45 | 2 | | 46 | 18 | | 47 | 4 | | 48 | 1 | | 49 | 2 |
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| 66.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.44761904761904764 | | totalSentences | 105 | | uniqueOpeners | 47 | |
| 43.29% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 77 | | matches | | 0 | "Of course they were; they" |
| | ratio | 0.013 | |
| 53.77% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 77 | | matches | | 0 | "She'd walked it a dozen" | | 1 | "Her phone said 1:37." | | 2 | "Her phone also said no" | | 3 | "Her voice went nowhere." | | 4 | "She kept walking." | | 5 | "She found them in a" | | 6 | "They stood in a rough" | | 7 | "They were all facing the" | | 8 | "She clapped once" | | 9 | "Their eyes caught what little" | | 10 | "She was fairly sure of" | | 11 | "She'd come in daylight with" | | 12 | "It pulsed again." | | 13 | "She stood in the hawthorn" | | 14 | "They leaned east, held, came" | | 15 | "She lifted her hand and" | | 16 | "She turned fast." | | 17 | "It was fine." | | 18 | "She could get out." | | 19 | "She stood very still and" |
| | ratio | 0.416 | |
| 83.38% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 58 | | totalSentences | 77 | | matches | | 0 | "The gate at Sheen Cross" | | 1 | "Richmond Park at half one" | | 2 | "She'd walked it a dozen" | | 3 | "The dark had swallowed the" | | 4 | "Her phone said 1:37." | | 5 | "Her phone also said no" | | 6 | "The pendant sat warm against" | | 7 | "Her voice went nowhere." | | 8 | "That was the first thing" | | 9 | "She kept walking." | | 10 | "The deer were the second" | | 11 | "She found them in a" | | 12 | "They stood in a rough" | | 13 | "They were all facing the" | | 14 | "She clapped once" | | 15 | "A hind's ear twitched and" | | 16 | "Their eyes caught what little" | | 17 | "Rory went around them, wide," | | 18 | "The grove sat behind a" | | 19 | "She was fairly sure of" |
| | ratio | 0.753 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 77 | | matches | | 0 | "Now the hawthorn came to" | | 1 | "Now the four black trunks" |
| | ratio | 0.026 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 38 | | technicalSentenceCount | 1 | | matches | | 0 | "Warm the way a mug goes warm when you've left it too long, that just-above-blood heat that made her keep touching it to check it hadn't cooled." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 94.44% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 7 | | fancyCount | 1 | | fancyTags | | 0 | "she whispered (whisper)" |
| | dialogueSentences | 18 | | tagDensity | 0.389 | | leniency | 0.778 | | rawRatio | 0.143 | | effectiveRatio | 0.111 | |