Run: 2026-07-07-01KWZ59J30CQ09HT4GZWEM94B9

Run Details

Duration:
54.2s
Cost:
$0.004311
Provider:
AionLabs

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
He didn’t notice her at first. That was the cruelest part. Aurora had been wiping down the section of bar near the window, her back half-turned to the door, when the bell chimed. She didn’t look up because it was a Tuesday, late enough that the after-work crowd had thinned to a few stubborn regulars, and the man who walked in was just another shape moving through the green neon glow bleeding through the window. She knew his shoulders before she knew his face. The same way she knew the faint crack in her favourite coffee mug before she saw it. James Collier. She almost said his name aloud. It sat on her tongue like a bad taste. He looked good. That was the second cruel thing. He’d filled out in the shoulders, lost the softness around his jaw that came from living off instant noodles and exam stress. His coat was charcoal grey, well cut, and he carried himself like a man who had somewhere to be. He didn’t look like a boy who used to borrow her lecture notes anymore. He slid onto a stool at the far end of the bar without looking in her direction, pulling out his phone. The gesture was so familiar it made her chest ache. She remembered when that same hand had held hers through a panic attack before her first mock trial in second year. The same fingers that had traced constellations in spilt beer on a sticky table. She should have slipped into the back. Let Silas handle him. But her feet were already moving, wiping the rag across the polished wood between them as if the motion could delay what was coming. “Don’t think I’ve seen you in here before.” She kept her voice neutral. He looked up. His eyes went wide—genuine surprise, not the performative kind. For a moment he looked exactly like the boy she remembered, caught off guard and vulnerable. “Rory?” The nickname hit her like a slap. She let it. “It’s Aurora these days. Or just Laila, depending on who’s asking.” He blinked, processing. She watched him do the math—the black hair still the same, pulled back in a knot at the nape of her neck. The same blue eyes, though he didn’t know about the nights they’d spent crying red and swollen. The crescent scar on her wrist was hidden under her sleeve. “What are you doing here?” he asked, and there was no accusation in it, just bewilderment. “I thought you went to London after... after everything.” *After Evan.* He didn’t say it. He didn’t have to. “I did. I am.” She gestured vaguely at the bar, the bottles lined up like soldiers behind her. “This is where I ended up.” “Working in a pub?” “It’s a bar. There’s a difference. Talk to the owner if you want the full lecture.” She smiled, but it didn’t reach her eyes. “What about you? Murder someone and need a place to hide?” He laughed, and it was the same laugh from their old flat in Cardiff, when they’d stay up too late drinking cheap wine and complaining about their module choices. Something loosened in her chest. “Passed the bar,” he said. “First attempt. I’m at a firm in Holborn now. Commercial law.” “Good for you.” She meant it. And somewhere beneath the pride, she resented him for it. Resented that he’d taken the path she’d been walking when she fled. Resented that he’d finished the race she hadn’t even started. “What happened, Rory?” His voice softened. “You were the best in our year. Everyone said you’d be a silk by thirty.” *A silk by thirty.* She almost laughed. She’d been running by twenty-two, hiding in a cramped flat above this bar, carrying containers of fried rice for Yu-Fei because the cash was untraceable and the hours let her sleep when the nightmares came. “I decided I didn’t want to be a lawyer,” she said. It was true, in its way. She'd decided the night Evan pinned her against the wall of their shared flat and told her she was nothing without him. She'd decided because she knew if she stayed she’d die. “That doesn’t sound like you.” “You don’t know me anymore, James.” The silence stretched between them. He looked down at his hands, and she noticed the wedding ring. Gold, simple. She’d never pictured him married. She’d never pictured him at all, because picturing him meant picturing everything she left behind. “I’m sorry,” he said. “I should have called. After you left. I heard what happened and I—” “You heard what?” He hesitated. “Eva told me. About Evan. About what he did.” The name turned the air solid. She gripped the edge of the bar, knuckles white. “Eva shouldn’t have done that.” “She was worried about you. We all were.” *We.* There was a we. People who cared, who had existed all along, and she had slipped through their fingers like smoke. “I’m fine.” The words came out brittle. “I handled it.” “Did you?” She looked at him, really looked. The man in front of her was a stranger wearing a familiar face. He had a life, a career, a ring on his finger. He had driven straight down the road she had abandoned. And he had no idea what it had cost her to even turn the wheel. “I changed the subject.” She poured him a whiskey without asking. He didn’t stop her. “Why are you really here, James?” He wrapped his fingers around the glass. “I was in the neighbourhood. Meeting fell through. I saw the sign outside and thought... I don’t know. It looked like the kind of place you’d like. Maps on the walls. Quiet.” She almost laughed again. “This is Silas’ place.” “Who’s Silas?” “The old man who owns it. He found me when I was sleeping in a park. Gave me a job and a room above the bar. Hired me because I reminded him of someone.” It was the most she’d told anyone in three years. She didn’t know why she told him. James set the glass down without drinking. “Rory—Aurora. Do you ever think about coming back? To Cardiff?” “No.” “Not even to see your parents? Eva?” “I talk to my parents. I see Eva when she visits.” Her voice was tighter than she wanted it to be. “I don’t need to go back.” “You’re running.” “I’m living. There’s a difference.” He stared at her, and she could see him fighting to reconcile the girl who argued circles around her professors with the woman who wiped down bars in Soho. It was a losing battle. She knew. She’d lost it herself a hundred times. “I should go,” he said, but he didn’t stand. “Probably.” He reached into his pocket and pulled out a card. Setting it on the bar between them, he slid it toward her. “If you ever change your mind. About the law, or... anything. My number’s still the same.” She looked at the card, white with gold lettering, and thought of all the things she hadn’t said. I was in love with you once. You don’t know me now. I woke up screaming last night and Silas made me tea and didn’t ask questions. I’ve built a life out of broken pieces and if I touch you—if I touch anyone from that time—I’m afraid it all falls apart. “I’ll keep that in mind,” she said. He nodded, stood, and walked toward the door. The green light fell across him like water, and then he was gone. Aurora picked up the card. She turned it over in her fingers, tracing the edges. Then she tucked it into her back pocket and went back to wiping the bar. The rag moved in steady circles, and she didn’t let herself think about the weight of time, or the sound of his laugh, or the way he’d looked at her like she was still someone worth finding. The door chimed again when a new customer walked in. She didn’t look up.
created_at"2026-07-07T20:46:11.568Z" 7/7/2026, 8:46:11 PM
model"aion-labs/aion-3.0-mini-20260707"
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external_user(null)
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cancelledfalse
latency598
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generation_time54037
tokens_prompt867
tokens_completion3035
native_tokens_prompt815
native_tokens_completion2672
native_tokens_completion_images(null)
native_tokens_reasoning1002
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
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origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
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latency598
model_permaslug"aion-labs/aion-3.0-mini-20260707"
provider_name"AionLabs"
status200
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data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount1
adverbTags
0"She gestured vaguely [vaguely]"
dialogueSentences44
tagDensity0.273
leniency0.545
rawRatio0.083
effectiveRatio0.045
92.58% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1348
totalAiIsmAdverbs2
found
0
adverb"really"
count2
highlights
0"really"
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)
66.62% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1348
totalAiIsms9
found
0
word"familiar"
count2
1
word"traced"
count1
2
word"race"
count1
3
word"silk"
count2
4
word"silence"
count1
5
word"tracing"
count1
6
word"weight"
count1
highlights
0"familiar"
1"traced"
2"race"
3"silk"
4"silence"
5"tracing"
6"weight"
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
emotionTells1
narrationSentences96
matches
0"s in love"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences96
filterMatches
0"think"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences128
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen43
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans3
markdownWords7
totalWords1344
ratio0.005
matches
0"After Evan."
1"A silk by thirty."
2"We."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions18
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions9
wordCount1018
uniqueNames7
maxNameDensity0.2
worstName"Silas"
maxWindowNameDensity1
worstWindowName"Evan"
discoveredNames
Tuesday1
Collier1
Silas2
Cardiff1
Yu-Fei1
Evan2
Soho1
persons
0"Collier"
1"Silas"
2"Evan"
places
0"Cardiff"
1"Soho"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences67
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1344
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount2
totalSentences128
matches
0"Resented that he’d"
1"Resented that he’d"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs58
mean23.17
std19.88
cv0.858
sampleLengths
011
190
22
315
464
566
635
78
833
91
1021
1153
1225
1310
1424
154
1635
1734
1816
193
2035
2121
2242
2349
245
256
2639
2717
283
2911
3020
318
3222
3310
342
3555
3621
3739
388
392
4034
4117
4217
431
447
4527
462
475
4843
499
97.95% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences96
matches
0"was hidden"
1"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs196
matches
0"were already moving"
1"was coming"
75.89% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount4
semicolonCount0
flaggedSentences3
totalSentences128
ratio0.023
matches
0"His eyes went wide—genuine surprise, not the performative kind."
1"She watched him do the math—the black hair still the same, pulled back in a knot at the nape of her neck."
2"I’ve built a life out of broken pieces and if I touch you—if I touch anyone from that time—I’m afraid it all falls apart."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1026
adjectiveStacks0
stackExamples(empty)
adverbCount27
adverbRatio0.02631578947368421
lyAdverbCount3
lyAdverbRatio0.0029239766081871343
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences128
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences128
mean10.5
std8.07
cv0.768
sampleLengths
06
15
222
342
49
517
62
76
89
93
106
1122
1219
1314
1421
1510
1621
1714
187
194
2024
218
225
233
249
2516
261
277
283
2911
303
3122
3217
3311
3416
359
366
374
3818
396
404
4124
4211
4329
445
455
4611
473
483
4910
39.84% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats14
diversityRatio0.3046875
totalSentences128
uniqueOpeners39
37.88% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences88
matches
0"Then she tucked it into"
ratio0.011
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount57
totalSentences88
matches
0"He didn’t notice her at"
1"She didn’t look up because"
2"She knew his shoulders before"
3"She almost said his name"
4"It sat on her tongue"
5"He looked good."
6"He’d filled out in the"
7"His coat was charcoal grey,"
8"He didn’t look like a"
9"He slid onto a stool"
10"She remembered when that same"
11"She should have slipped into"
12"She kept her voice neutral."
13"He looked up."
14"His eyes went wide—genuine surprise,"
15"She let it."
16"He blinked, processing."
17"She watched him do the"
18"he asked, and there was"
19"He didn’t have to."
ratio0.648
16.82% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount78
totalSentences88
matches
0"He didn’t notice her at"
1"That was the cruelest part."
2"Aurora had been wiping down"
3"She didn’t look up because"
4"She knew his shoulders before"
5"The same way she knew"
6"She almost said his name"
7"It sat on her tongue"
8"He looked good."
9"That was the second cruel"
10"He’d filled out in the"
11"His coat was charcoal grey,"
12"He didn’t look like a"
13"He slid onto a stool"
14"The gesture was so familiar"
15"She remembered when that same"
16"The same fingers that had"
17"She should have slipped into"
18"She kept her voice neutral."
19"He looked up."
ratio0.886
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences88
matches(empty)
ratio0
91.84% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences42
technicalSentenceCount3
matches
0"She didn’t look up because it was a Tuesday, late enough that the after-work crowd had thinned to a few stubborn regulars, and the man who walked in was just an…"
1"He slid onto a stool at the far end of the bar without looking in her direction, pulling out his phone."
2"But her feet were already moving, wiping the rag across the polished wood between them as if the motion could delay what was coming."
83.33% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount1
matches
0"She gestured vaguely, the bottles lined up like soldiers behind her"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount0
fancyTags(empty)
dialogueSentences44
tagDensity0.136
leniency0.273
rawRatio0
effectiveRatio0
83.4252%