| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "she said slowly [slowly]" |
| | dialogueSentences | 55 | | tagDensity | 0.345 | | leniency | 0.691 | | rawRatio | 0.053 | | effectiveRatio | 0.036 | |
| 96.90% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1613 | | totalAiIsmAdverbs | 1 | | 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) | |
| 87.60% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1613 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "chill" | | 1 | "velvet" | | 2 | "unreadable" |
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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 | 124 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 124 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 160 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1627 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 48 | | wordCount | 1021 | | uniqueNames | 9 | | maxNameDensity | 2.25 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Quinn" | | discoveredNames | | Harlow | 1 | | Quinn | 23 | | Tube | 1 | | Inspector | 1 | | Mercer | 9 | | Fen | 8 | | Aldous | 3 | | Market | 1 | | Vane | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Mercer" | | 3 | "Fen" | | 4 | "Market" |
| | places | (empty) | | globalScore | 0.374 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 72 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 0.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 4 | | per1kWords | 2.459 | | wordCount | 1627 | | matches | | 0 | "Not everyone participates, but most clear out" | | 1 | "not north, but toward rifts" | | 2 | "not fast, not loud, but with the patience of a secret being kept" | | 3 | "not loud, but with the patience of a secret being kept" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 160 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 66 | | mean | 24.65 | | std | 17.76 | | cv | 0.72 | | sampleLengths | | 0 | 51 | | 1 | 58 | | 2 | 64 | | 3 | 33 | | 4 | 39 | | 5 | 58 | | 6 | 47 | | 7 | 5 | | 8 | 10 | | 9 | 56 | | 10 | 6 | | 11 | 38 | | 12 | 3 | | 13 | 26 | | 14 | 37 | | 15 | 6 | | 16 | 13 | | 17 | 4 | | 18 | 16 | | 19 | 4 | | 20 | 1 | | 21 | 5 | | 22 | 16 | | 23 | 49 | | 24 | 24 | | 25 | 50 | | 26 | 9 | | 27 | 30 | | 28 | 24 | | 29 | 7 | | 30 | 15 | | 31 | 52 | | 32 | 16 | | 33 | 10 | | 34 | 4 | | 35 | 11 | | 36 | 57 | | 37 | 40 | | 38 | 10 | | 39 | 15 | | 40 | 5 | | 41 | 55 | | 42 | 22 | | 43 | 38 | | 44 | 14 | | 45 | 13 | | 46 | 37 | | 47 | 7 | | 48 | 44 | | 49 | 17 |
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| 88.29% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 6 | | totalSentences | 124 | | matches | | 0 | "been arranged" | | 1 | "been ripped " | | 2 | "been stripped" | | 3 | "been burned" | | 4 | "was placed" | | 5 | "being kept" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 153 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 10 | | totalSentences | 160 | | ratio | 0.063 | | matches | | 0 | "The air that bled through carried the mineral bite of old water and something else — ozone, burnt sugar, the static before a storm." | | 1 | "The victim — male, mid-thirties, hair the color of wet ash — had been arranged on his back, arms folded across his chest like a knight atop a tomb." | | 2 | "The indigo cloth on the stall had been ripped — a clean vertical tear, as if someone had sliced it with a blade, not torn it in a struggle." | | 3 | "The dust around Aldous held a single set of footprints — his own, walking from the stall to the center of the platform." | | 4 | "A small rune had been burned into the skin just below his left collarbone — a circle bisected by a jagged line, the edges still pink and raw." | | 5 | "The stool fell on its own — or was placed that way." | | 6 | "A thief would have gone for the locked drawers first — the hidden cash, the private ledgers, the premium stock." | | 7 | "She pointed to the body’s hands — folded neatly, the left over the right, but the right index finger curled inward toward the palm." | | 8 | "Somewhere beyond the edge of the light, something moved — not fast, not loud, but with the patience of a secret being kept." | | 9 | "His clouded eyes reflected the string of bulbs, and in them she saw it — a second moon, faint and silver and impossible." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1011 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 28 | | adverbRatio | 0.027695351137487636 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0019782393669634025 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 160 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 160 | | mean | 10.17 | | std | 7.32 | | cv | 0.719 | | sampleLengths | | 0 | 15 | | 1 | 12 | | 2 | 24 | | 3 | 8 | | 4 | 7 | | 5 | 21 | | 6 | 15 | | 7 | 7 | | 8 | 18 | | 9 | 29 | | 10 | 7 | | 11 | 2 | | 12 | 2 | | 13 | 6 | | 14 | 12 | | 15 | 3 | | 16 | 8 | | 17 | 10 | | 18 | 5 | | 19 | 34 | | 20 | 5 | | 21 | 11 | | 22 | 10 | | 23 | 14 | | 24 | 10 | | 25 | 8 | | 26 | 4 | | 27 | 2 | | 28 | 12 | | 29 | 29 | | 30 | 5 | | 31 | 10 | | 32 | 7 | | 33 | 16 | | 34 | 15 | | 35 | 6 | | 36 | 3 | | 37 | 9 | | 38 | 6 | | 39 | 11 | | 40 | 27 | | 41 | 3 | | 42 | 26 | | 43 | 10 | | 44 | 8 | | 45 | 12 | | 46 | 7 | | 47 | 6 | | 48 | 13 | | 49 | 4 |
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| 49.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.34375 | | totalSentences | 160 | | uniqueOpeners | 55 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 96 | | matches | | 0 | "Pale, hairless, eyes the color" | | 1 | "Too small for a ledger." | | 2 | "Too flat for a bottle." | | 3 | "Somewhere beyond the edge of" |
| | ratio | 0.042 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 15 | | totalSentences | 96 | | matches | | 0 | "She stepped down into the" | | 1 | "Her worn leather watch marked" | | 2 | "His eyes had clouded to" | | 3 | "She held two fingers an" | | 4 | "His hands were clean." | | 5 | "She stood and moved to" | | 6 | "They wore a coat sewn" | | 7 | "Their hands lay still in" | | 8 | "She eased open the collar" | | 9 | "She examined the open drawer." | | 10 | "She pointed to the body’s" | | 11 | "She crouched and scraped a" | | 12 | "she said slowly" | | 13 | "His clouded eyes reflected the" | | 14 | "She closed his eyes with" |
| | ratio | 0.156 | |
| 58.96% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 77 | | totalSentences | 96 | | matches | | 0 | "Detective Harlow Quinn pressed the" | | 1 | "The lock coughed once, then" | | 2 | "The air that bled through" | | 3 | "She stepped down into the" | | 4 | "Her worn leather watch marked" | | 5 | "The platform stretched ahead, lit" | | 6 | "Vendors had set up stalls" | | 7 | "A city of thieves holding" | | 8 | "The body lay near the" | | 9 | "The victim — male, mid-thirties," | | 10 | "His eyes had clouded to" | | 11 | "A constable stood three feet" | | 12 | "Detective Inspector Mercer." | | 13 | "Quinn had seen him at" | | 14 | "Quinn knelt beside the body." | | 15 | "She held two fingers an" | | 16 | "This was a surface chill," | | 17 | "Rigor had set in the" | | 18 | "Death had come four, maybe" | | 19 | "His hands were clean." |
| | ratio | 0.802 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 96 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 1 | | matches | | 0 | "The platform stretched ahead, lit by a string of bare bulbs that hummed at a frequency that made her fillings ache." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 19 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 55 | | tagDensity | 0.345 | | leniency | 0.691 | | rawRatio | 0.053 | | effectiveRatio | 0.036 | |