| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1171 | | 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) | |
| 44.49% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1171 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "silence" | | 1 | "footsteps" | | 2 | "echo" | | 3 | "affection" | | 4 | "wavered" | | 5 | "pulse" |
| |
| 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 | 99 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 99 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 106 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1183 | | ratio | 0 | | matches | (empty) | |
| 41.67% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 2 | | matches | | 0 | "The bag strap, she told herself." | | 1 | "When she checked the phone again, it said 02:16, and the moon had crossed the sky to agree with it." |
| |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1095 | | uniqueNames | 15 | | maxNameDensity | 0.37 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Richmond | 1 | | Park | 1 | | Rory | 4 | | Peckham | 1 | | Petersham | 1 | | Gate | 1 | | Heathrow | 1 | | Heartstone | 2 | | Eel | 1 | | Pie | 1 | | Island | 1 | | October | 1 | | Eva | 2 | | Aurora | 2 | | Frost | 3 |
| | persons | | 0 | "Rory" | | 1 | "Heartstone" | | 2 | "Eva" | | 3 | "Frost" |
| | places | | 0 | "Richmond" | | 1 | "Park" | | 2 | "Peckham" | | 3 | "Petersham" | | 4 | "Heathrow" | | 5 | "Eel" | | 6 | "Pie" | | 7 | "Island" | | 8 | "October" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | 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 | 1183 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 106 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 37 | | mean | 31.97 | | std | 20.25 | | cv | 0.633 | | sampleLengths | | 0 | 47 | | 1 | 57 | | 2 | 24 | | 3 | 85 | | 4 | 36 | | 5 | 9 | | 6 | 32 | | 7 | 35 | | 8 | 4 | | 9 | 56 | | 10 | 51 | | 11 | 20 | | 12 | 32 | | 13 | 35 | | 14 | 42 | | 15 | 16 | | 16 | 17 | | 17 | 25 | | 18 | 35 | | 19 | 44 | | 20 | 13 | | 21 | 46 | | 22 | 79 | | 23 | 10 | | 24 | 25 | | 25 | 47 | | 26 | 10 | | 27 | 5 | | 28 | 44 | | 29 | 2 | | 30 | 4 | | 31 | 44 | | 32 | 59 | | 33 | 38 | | 34 | 27 | | 35 | 21 | | 36 | 7 |
| |
| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 99 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 169 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 3 | | flaggedSentences | 10 | | totalSentences | 106 | | ratio | 0.094 | | matches | | 0 | "London hummed at night — she had lived above Silas' bar long enough to know the hum came up through the floorboards and into your sleep if you let it." | | 1 | "Under her coat and jumper, the Heartstone had gone warm on the bus over — she'd noticed it at the traffic lights by Eel Pie Island and blamed the heated seats." | | 2 | "The park crawled with them; she'd braked for a stag in October and sworn at him with affection." | | 3 | "One ring, then voicemail — strange; Eva slept with the phone under her pillow." | | 4 | "Frost ended in a clean line at the ring's edge — one step, and the grass outside wore white; the next, green and dark and growing." | | 5 | "Pleasant, even — a woman's voice, unhurried, the kind that took your order at a counter." | | 6 | "The app showed the restaurant and her first name, Aurora, and nobody — nobody — read Aurora off a delivery ticket and came back with Rory." | | 7 | "She yanked the chain out from under her collar with a hiss — the silver had gone hot, and the gem in it sat deep crimson in her palm, its inner light beating." | | 8 | "Narrow, human-length, pressed deep, a full circuit of the ring's inside — and the nearest prints had not been there when she crossed the line." | | 9 | "No frost to crackle under them — they fell soft on the flowers, and the flowers did not bend." |
| |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 266 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 3 | | adverbRatio | 0.011278195488721804 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0037593984962406013 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 106 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 106 | | mean | 11.16 | | std | 8.51 | | cv | 0.763 | | sampleLengths | | 0 | 6 | | 1 | 18 | | 2 | 6 | | 3 | 1 | | 4 | 11 | | 5 | 5 | | 6 | 5 | | 7 | 6 | | 8 | 16 | | 9 | 30 | | 10 | 20 | | 11 | 4 | | 12 | 5 | | 13 | 23 | | 14 | 30 | | 15 | 6 | | 16 | 21 | | 17 | 9 | | 18 | 27 | | 19 | 2 | | 20 | 7 | | 21 | 9 | | 22 | 12 | | 23 | 8 | | 24 | 3 | | 25 | 6 | | 26 | 8 | | 27 | 21 | | 28 | 4 | | 29 | 31 | | 30 | 7 | | 31 | 13 | | 32 | 2 | | 33 | 3 | | 34 | 11 | | 35 | 9 | | 36 | 1 | | 37 | 18 | | 38 | 4 | | 39 | 8 | | 40 | 14 | | 41 | 6 | | 42 | 10 | | 43 | 7 | | 44 | 15 | | 45 | 6 | | 46 | 29 | | 47 | 4 | | 48 | 16 | | 49 | 2 |
| |
| 64.47% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.44339622641509435 | | totalSentences | 106 | | uniqueOpeners | 47 | |
| 38.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 86 | | matches | | 0 | "Then there was nothing." |
| | ratio | 0.012 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 16 | | totalSentences | 86 | | matches | | 0 | "I will come to" | | 1 | "Her boots went across it," | | 2 | "She turned the torch on" | | 3 | "She shrugged the bag off" | | 4 | "It was the one thing" | | 5 | "She stood there until the" | | 6 | "Her phone said 23:52." | | 7 | "she told the dark, and" | | 8 | "She rang Eva." | | 9 | "She lifted the phone from" | | 10 | "Her own breathing, half a" | | 11 | "Her breath stopped fogging the" | | 12 | "She held the bag out" | | 13 | "Her thumb found the crescent" | | 14 | "She yanked the chain out" | | 15 | "She looked down." |
| | ratio | 0.186 | |
| 99.53% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 62 | | totalSentences | 86 | | matches | | 0 | "The order came through at" | | 1 | "The note said:" | | 2 | "I will come to" | | 3 | "Rory had taken stranger orders." | | 4 | "A penthouse with a shark" | | 5 | "A lock-up in Peckham where" | | 6 | "The pedestrian gate screeched when" | | 7 | "London hummed at night —" | | 8 | "The hum stopped at the" | | 9 | "The silence past the railings" | | 10 | "Frost sugared every blade of" | | 11 | "Her boots went across it," | | 12 | "The second set stopped one" | | 13 | "She turned the torch on" | | 14 | "Nothing to hide behind, nothing" | | 15 | "Frost didn't echo." | | 16 | "The bag strap, she told" | | 17 | "The strap slapping her back" | | 18 | "She shrugged the bag off" | | 19 | "The footsteps carried on." |
| | ratio | 0.721 | |
| 58.14% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 86 | | matches | | | ratio | 0.012 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 1 | | matches | | 0 | "Wildflowers stood open in the dark, celandine and violet and pale things she had no names for, every bloom lifted as if the sun sat somewhere beneath the ground…" |
| |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 10 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0 | | effectiveRatio | 0 | |