Run: 2026-02-17-01KHMSFNYYBY5NCFTYMTKSHADS

Run Details

Duration:
18.3s
Cost:
$0.003655

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<codex> <character id="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> </codex> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary.

Model response

AI
The green neon sign flickered like a half-remembered promise as Aurora pushed open the heavy wooden door of The Raven's Nest. Dust motes danced in the amber bar light, settling on old maps and faded photographs that lined the walls. She'd lived above this place for months, but tonight felt different. Something electric hummed beneath her skin. Silas was polishing glasses behind the bar, his grey-streaked auburn hair catching the low light. He looked up, recognition softening the sharp edges of his face. Before she could speak, a voice cut through the low murmur of conversation. "Rory?" She froze. That voice. Daniel. He sat in a corner booth, looking both exactly the same and completely transformed. The Daniel she remembered had been all soft edges and hesitation. This version was harder, his shoulders squared, a thin scar tracking along his jawline that hadn't existed before. Aurora's hand instinctively touched the small crescent-shaped scar on her own wrist—a nervous habit from childhood. "Daniel," she said, more a statement than a greeting. He gestured to the empty seat across from him. Not a request. An expectation. Silas caught her eye, a silent question in his hazel gaze. She gave an almost imperceptible shake of her head. This was something she would handle. The booth's leather was cracked, sticky with decades of spilled drinks and unspoken stories. Aurora sat, her black hair falling across her bright blue eyes. Daniel watched her, sizing her up like a stranger. "You look different," he said. "People change," Aurora replied, her Cardiff accent sharper than she intended. A lifetime ago, they had been something—not quite lovers, not quite friends. University colleagues who understood each other in the way damaged people sometimes do. He had been studying theoretical physics; she had been reluctantly pursuing pre-law, always more interested in the gaps between rules than the rules themselves. Daniel's fingers traced the rim of his whiskey glass. "Not always for the better." The accusation hung between them, heavy with history. Aurora felt the weight of unresolved conversations, of paths not taken, of the person she had been before London, before Eva, before she learned to cut toxic people from her life like diseased branches. "What do you want, Daniel?" Her voice was cool, controlled. He laughed. Not the soft chuckle she remembered, but something harder. Brittle. "Want? I'm just catching up with an old friend." Silas moved closer, his slight limp barely perceptible. A silent guardian, reading the tension like another language. The bar's ambient noise—glasses clinking, low conversations, the distant hum of a vintage radio—created a backdrop to their silent battle. Two people who once knew each other intimately, now separated by years and unspoken betrayals. "Catching up," Aurora repeated. "Is that what we're calling this?" Daniel's hand trembled almost imperceptibly as he lifted his glass. Something lurked behind his eyes—fear, regret, something unresolved that time had not softened. And in that moment, Aurora understood. Some connections never truly dissolve. They simply wait, patient and dangerous, for the right moment to resurface.
total_cost0.0036552

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences9
tagDensity0.444
leniency0.889
rawRatio0
effectiveRatio0
70.53% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount509
totalAiIsmAdverbs3
found
0
adverb"completely"
count1
1
adverb"reluctantly"
count1
2
adverb"truly"
count1
highlights
0"completely"
1"reluctantly"
2"truly"
100.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
21.41% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount509
totalAiIsms8
found
0
word"flickered"
count1
1
word"electric"
count1
2
word"unspoken"
count2
3
word"traced"
count1
4
word"weight"
count1
5
word"tension"
count1
6
word"trembled"
count1
highlights
0"flickered"
1"electric"
2"unspoken"
3"traced"
4"weight"
5"tension"
6"trembled"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences46
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences46
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences50
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen34
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords504
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
75.53% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount470
uniqueNames8
maxNameDensity1.49
worstName"Aurora"
maxWindowNameDensity2
worstWindowName"Aurora"
discoveredNames
Aurora7
Raven1
Nest1
Daniel5
Cardiff1
London1
Eva1
Silas3
persons
0"Aurora"
1"Raven"
2"Daniel"
3"Eva"
4"Silas"
places
0"Cardiff"
1"London"
globalScore0.755
windowScore1
78.57% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences35
glossingSentenceCount1
matches
0"not quite lovers, not quite friends"
1"not quite friends"
1.59% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords1.984
wordCount504
matches
0"Not the soft chuckle she remembered, but something harder"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences50
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs21
mean24
std15.31
cv0.638
sampleLengths
057
139
21
35
443
525
614
726
834
95
1011
1149
1214
1342
1410
1521
1617
1735
1810
1923
2023
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences46
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs77
matches
0"was polishing"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount5
semicolonCount1
flaggedSentences5
totalSentences50
ratio0.1
matches
0"Aurora's hand instinctively touched the small crescent-shaped scar on her own wrist—a nervous habit from childhood."
1"A lifetime ago, they had been something—not quite lovers, not quite friends."
2"He had been studying theoretical physics; she had been reluctantly pursuing pre-law, always more interested in the gaps between rules than the rules themselves."
3"The bar's ambient noise—glasses clinking, low conversations, the distant hum of a vintage radio—created a backdrop to their silent battle."
4"Something lurked behind his eyes—fear, regret, something unresolved that time had not softened."
88.73% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount478
adjectiveStacks1
stackExamples
0"small crescent-shaped scar"
adverbCount22
adverbRatio0.04602510460251046
lyAdverbCount9
lyAdverbRatio0.01882845188284519
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences50
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences50
mean10.08
std6.38
cv0.633
sampleLengths
021
119
211
36
415
511
613
71
82
92
101
1114
1211
1318
1416
159
169
173
182
1911
209
216
2214
2311
249
255
2611
2712
2813
2924
309
315
328
3334
3410
352
369
371
389
398
409
4120
4215
434
446
4510
4613
476
485
4912
90.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.54
totalSentences50
uniqueOpeners27
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences38
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount9
totalSentences38
matches
0"She'd lived above this place"
1"He looked up, recognition softening"
2"He sat in a corner"
3"she said, more a statement"
4"He gestured to the empty"
5"She gave an almost imperceptible"
6"He had been studying theoretical"
7"Her voice was cool, controlled"
8"They simply wait, patient and"
ratio0.237
25.79% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount33
totalSentences38
matches
0"The green neon sign flickered"
1"Dust motes danced in the"
2"She'd lived above this place"
3"Something electric hummed beneath her"
4"Silas was polishing glasses behind"
5"He looked up, recognition softening"
6"He sat in a corner"
7"The Daniel she remembered had"
8"This version was harder, his"
9"Aurora's hand instinctively touched the"
10"she said, more a statement"
11"He gestured to the empty"
12"Silas caught her eye, a"
13"She gave an almost imperceptible"
14"This was something she would"
15"The booth's leather was cracked,"
16"Aurora sat, her black hair"
17"Daniel watched her, sizing her"
18"Aurora replied, her Cardiff accent"
19"A lifetime ago, they had"
ratio0.868
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences38
matches
0"Before she could speak, a"
ratio0.026
77.92% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences22
technicalSentenceCount2
matches
0"Dust motes danced in the amber bar light, settling on old maps and faded photographs that lined the walls."
1"University colleagues who understood each other in the way damaged people sometimes do."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount1
matches
0"Aurora replied, her Cardiff accent sharper than she intended"
38.89% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount1
fancyTags
0"Aurora repeated (repeat)"
dialogueSentences9
tagDensity0.444
leniency0.889
rawRatio0.25
effectiveRatio0.222
75.6321%