| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.429 | | leniency | 0.857 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 94.71% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 946 | | 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) | |
| 78.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 946 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "throbbed" | | 1 | "pulse" | | 2 | "footsteps" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 111 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 111 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 119 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 24 | | ratio | 0 | | matches | (empty) | |
| 0.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 24 | | markdownWords | 160 | | totalWords | 938 | | ratio | 0.171 | | matches | | 0 | "The Nest" | | 1 | "Locked." | | 2 | "pop" | | 3 | "Employees Only" | | 4 | "Smelled like drowning." | | 5 | "Tomás’s work" | | 6 | "“Exchange’s invalid.”" | | 7 | "“Rules don’t work if you don’t understand the market.”" | | 8 | "The Raven’s Nest" | | 9 | "“Silas’s doing?”" | | 10 | "“He’s in with the draugr again, isn’t he? Feeding corpse prizes to his friends?”" | | 11 | "“Sir, this is beyond your jurisdiction. Your station won’t even listen when you mention them.”" | | 12 | "“My stone pushes where the wind builds its walls.”" | | 13 | "“Try again.Slowly.”" | | 14 | "“You know how they spot you? Your eyes. Look at the colors now. Change, right before the blighting of the moon.”" | | 15 | "“They take your color before your name,”" | | 16 | "“You’re not Quinn now, are you? That woman couldn’t make the first step.”" | | 17 | "Silas’s work." | | 18 | "They’re tied. Both of them." | | 19 | "“You told them about Morris. His name in the ledger. His death date unrecorded.”" | | 20 | "“His death’s not done yet.”" | | 21 | "I walked away. But they can see the coin under my shoe. I know the rules." | | 22 | "“They aren’t dead. Just waiting.”" | | 23 | "Staff Only. Still Operational 4/15" 4/15/2001, 12:00:00 AM |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 804 | | uniqueNames | 16 | | maxNameDensity | 1.62 | | worstName | "Quinn" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Quinn" | | discoveredNames | | Quinn | 13 | | Soho | 1 | | Tube | 1 | | Transit | 1 | | Police | 1 | | London | 1 | | Morris | 2 | | Veil | 2 | | Market | 3 | | Northern | 1 | | Line | 1 | | Chalk | 1 | | Farm | 1 | | Raven | 1 | | Tomás | 3 | | Operational | 1 |
| | persons | | 0 | "Quinn" | | 1 | "Morris" | | 2 | "Veil" | | 3 | "Market" | | 4 | "Raven" | | 5 | "Tomás" |
| | places | | 0 | "Soho" | | 1 | "London" | | 2 | "Chalk" | | 3 | "Farm" |
| | globalScore | 0.692 | | windowScore | 0.5 | |
| 71.88% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 64 | | glossingSentenceCount | 2 | | matches | | 0 | "Smelled like drowning.* She remembered DS" | | 1 | "appeared—glazed cracked, lighting the path" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 938 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 119 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 23 | | mean | 40.78 | | std | 43.82 | | cv | 1.074 | | sampleLengths | | 0 | 165 | | 1 | 1 | | 2 | 159 | | 3 | 87 | | 4 | 5 | | 5 | 91 | | 6 | 5 | | 7 | 33 | | 8 | 48 | | 9 | 31 | | 10 | 18 | | 11 | 18 | | 12 | 32 | | 13 | 2 | | 14 | 22 | | 15 | 11 | | 16 | 45 | | 17 | 10 | | 18 | 29 | | 19 | 37 | | 20 | 27 | | 21 | 45 | | 22 | 17 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 111 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 149 | | matches | (empty) | |
| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 119 | | ratio | 0.092 | | matches | | 0 | "The suspect’s jacket flared ahead—black wool gelled to his back in the downpour, the collar frayed like it’d been cut with a knife." | | 1 | "Her eyes locked onto the exit marked *Employees Only*—a false wall between the bar and the Tube." | | 2 | "A green bioluminescent tile appeared—glazed, cracked, lighting the path." | | 3 | "The Veil’s current location—abandoned Northern Line station at Chalk Farm." | | 4 | "Quinn felt the stares—indifferent, sharp-as-needles." | | 5 | "His left forearm bore a gash—new blood seeped through a torn gauze." | | 6 | "The shopkeeper’s fingers moved—practices." | | 7 | "*Silas’s work.* She had the briefest flash—Tomás’s hands, bloodied, careful." | | 8 | "But the Market’s lights had gone out—all save the bone token." | | 9 | "Let the Market’s patrons see her stance—*I walked away." | | 10 | "Footsteps in her wake—no." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 559 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 14 | | adverbRatio | 0.025044722719141325 | | lyAdverbCount | 1 | | lyAdverbRatio | 0.0017889087656529517 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 119 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 119 | | mean | 7.88 | | std | 4.87 | | cv | 0.618 | | sampleLengths | | 0 | 15 | | 1 | 16 | | 2 | 6 | | 3 | 23 | | 4 | 3 | | 5 | 10 | | 6 | 8 | | 7 | 14 | | 8 | 10 | | 9 | 1 | | 10 | 10 | | 11 | 8 | | 12 | 21 | | 13 | 10 | | 14 | 2 | | 15 | 8 | | 16 | 1 | | 17 | 3 | | 18 | 12 | | 19 | 6 | | 20 | 8 | | 21 | 9 | | 22 | 11 | | 23 | 2 | | 24 | 5 | | 25 | 17 | | 26 | 21 | | 27 | 9 | | 28 | 14 | | 29 | 13 | | 30 | 4 | | 31 | 15 | | 32 | 10 | | 33 | 3 | | 34 | 9 | | 35 | 5 | | 36 | 11 | | 37 | 11 | | 38 | 12 | | 39 | 9 | | 40 | 2 | | 41 | 3 | | 42 | 10 | | 43 | 12 | | 44 | 5 | | 45 | 5 | | 46 | 11 | | 47 | 19 | | 48 | 5 | | 49 | 9 |
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| 64.71% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.40336134453781514 | | totalSentences | 119 | | uniqueOpeners | 48 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 98 | | matches | (empty) | | ratio | 0 | |
| 97.55% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 30 | | totalSentences | 98 | | matches | | 0 | "Her left heel caught the" | | 1 | "She rounded the corner, skidded," | | 2 | "Her suspect hit the lobby" | | 3 | "She slid sideways, shoulder-checked the" | | 4 | "Her hand went to her" | | 5 | "Her eyes locked onto the" | | 6 | "She’d only ever seen it" | | 7 | "Her fingers found the damp" | | 8 | "She followed it down, booted" | | 9 | "Her left hand brushed the" | | 10 | "They’d come for full moon." | | 11 | "She stalked forward, joints throbbed" | | 12 | "She saw him now, broad-shouldered," | | 13 | "His left forearm bore a" | | 14 | "He dropped a bone token." | | 15 | "She aimed at his ribs" | | 16 | "His fingers twitched, brushed the" | | 17 | "Her voice was sharp as" | | 18 | "She kicked the token" | | 19 | "He left the gash unbandaged." |
| | ratio | 0.306 | |
| 51.84% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 80 | | totalSentences | 98 | | matches | | 0 | "The wet asphalt hissed under" | | 1 | "Her left heel caught the" | | 2 | "The suspect’s jacket flared ahead—black" | | 3 | "Emergency release shears, the kind" | | 4 | "Quinn’s fingers burned around her" | | 5 | "Breath came in sharp huffs," | | 6 | "She rounded the corner, skidded," | | 7 | "The figure vaulted over an" | | 8 | "Grapes sprawled across the deluge" | | 9 | "Quinn’s knee buckled but she" | | 10 | "Her suspect hit the lobby" | | 11 | "A shadow darted back to" | | 12 | "Quinn didn’t pause." | | 13 | "She slid sideways, shoulder-checked the" | | 14 | "The lock gave an audible" | | 15 | "Her hand went to her" | | 16 | "The bar stank of old" | | 17 | "A curtain of hanging herbs" | | 18 | "Her eyes locked onto the" | | 19 | "She’d only ever seen it" |
| | ratio | 0.816 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 98 | | matches | | 0 | "Now her jacket was soaked," | | 1 | "Now she had the underground" |
| | ratio | 0.02 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 7.14% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 2 | | fancyTags | | 0 | "he hissed (hiss)" | | 1 | "last breath whispered (whisper)" |
| | dialogueSentences | 14 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 1 | | effectiveRatio | 0.286 | |